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Merge branch 'master' into feat-libfasttransforms
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.travis.yml

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- linux
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- osx
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julia:
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- 0.6
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- 0.7
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- 1.0
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- 1.1
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- 1.2
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- nightly
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matrix:
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allow_failures:
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- julia: nightly
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- julia: nightly
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notifications:
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email: false
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after_success:

LICENSE.md

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The FastTransforms.jl package is licensed under the MIT "Expat" License:
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> Copyright (c) 2016-2018: Richard Mikael Slevinsky and other contributors:
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> Copyright (c) 2016-2019: Richard Mikael Slevinsky and other contributors:
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>
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> https://github.com/MikaelSlevinsky/FastTransforms.jl/graphs/contributors
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> https://github.com/JuliaApproximation/FastTransforms.jl/graphs/contributors
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>
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> Permission is hereby granted, free of charge, to any person obtaining
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> a copy of this software and associated documentation files (the

Project.toml

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name = "FastTransforms"
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uuid = "057dd010-8810-581a-b7be-e3fc3b93f78c"
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version = "0.5"
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[deps]
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AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
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Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
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DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2"
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FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
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HierarchicalMatrices = "7c893195-952b-5c83-bb6e-be12f22eed51"
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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LowRankApprox = "898213cb-b102-5a47-900c-97e73b919f73"
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ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
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SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
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ToeplitzMatrices = "c751599d-da0a-543b-9d20-d0a503d91d24"
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[compat]
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AbstractFFTs = "≥ 0.3.1"
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Compat = "≥ 0.17.0"
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DSP = "≥ 0.4.0"
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FFTW = "≥ 0.0.4"
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HierarchicalMatrices = "≥ 0.1.1"
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LowRankApprox = "≥ 0.1.1"
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ProgressMeter = "≥ 0.3.4"
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SpecialFunctions = "≥ 0.3.4"
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ToeplitzMatrices = "≥ 0.4.0"
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julia = "0.7, 1"

README.md

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# FastTransforms.jl
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[![Travis](https://travis-ci.org/MikaelSlevinsky/FastTransforms.jl.svg?branch=master)](https://travis-ci.org/MikaelSlevinsky/FastTransforms.jl) [![AppVeyor](https://ci.appveyor.com/api/projects/status/oba9qush15q3x8pb/branch/master?svg=true)](https://ci.appveyor.com/project/MikaelSlevinsky/fasttransforms-jl/branch/master) [![codecov](https://codecov.io/gh/MikaelSlevinsky/FastTransforms.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/MikaelSlevinsky/FastTransforms.jl) [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://MikaelSlevinsky.github.io/FastTransforms.jl/stable) [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://MikaelSlevinsky.github.io/FastTransforms.jl/latest)
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[![Travis](https://travis-ci.org/JuliaApproximation/FastTransforms.jl.svg?branch=master)](https://travis-ci.org/JuliaApproximation/FastTransforms.jl) [![AppVeyor](https://ci.appveyor.com/api/projects/status/oba9qush15q3x8pb/branch/master?svg=true)](https://ci.appveyor.com/project/MikaelSlevinsky/fasttransforms-jl/branch/master) [![codecov](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaApproximation/FastTransforms.jl) [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/stable) [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://JuliaApproximation.github.io/FastTransforms.jl/latest)
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`FastTransforms.jl` allows the user to conveniently work with orthogonal polynomials with degrees well into the millions.
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REQUIRE

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appveyor.yml

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environment:
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matrix:
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- JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.6/julia-0.6-latest-win32.exe"
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- JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.6/julia-0.6-latest-win64.exe"
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- JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x86/julia-latest-win32.exe"
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- JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x64/julia-latest-win64.exe"
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- julia_version: 0.7
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- julia_version: 1.0
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- julia_version: 1.1
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- julia_version: 1.2
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- julia_version: nightly
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platform:
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- x86 # 32-bit
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- x64 # 64-bit
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# # Uncomment the following lines to allow failures on nightly julia
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# # (tests will run but not make your overall status red)
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matrix:
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allow_failures:
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- JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x86/julia-latest-win32.exe"
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- JULIA_URL: "https://julialangnightlies-s3.julialang.org/bin/winnt/x64/julia-latest-win64.exe"
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- julia_version: nightly
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branches:
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only:
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on_build_status_changed: false
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install:
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- ps: "[System.Net.ServicePointManager]::SecurityProtocol = [System.Net.SecurityProtocolType]::Tls12"
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# If there's a newer build queued for the same PR, cancel this one
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- ps: if ($env:APPVEYOR_PULL_REQUEST_NUMBER -and $env:APPVEYOR_BUILD_NUMBER -ne ((Invoke-RestMethod `
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https://ci.appveyor.com/api/projects/$env:APPVEYOR_ACCOUNT_NAME/$env:APPVEYOR_PROJECT_SLUG/history?recordsNumber=50).builds | `
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Where-Object pullRequestId -eq $env:APPVEYOR_PULL_REQUEST_NUMBER)[0].buildNumber) { `
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throw "There are newer queued builds for this pull request, failing early." }
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# Download most recent Julia Windows binary
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- ps: (new-object net.webclient).DownloadFile(
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$env:JULIA_URL,
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"C:\projects\julia-binary.exe")
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# Run installer silently, output to C:\projects\julia
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- C:\projects\julia-binary.exe /S /D=C:\projects\julia
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- ps: iex ((new-object net.webclient).DownloadString("https://raw.githubusercontent.com/JuliaCI/Appveyor.jl/version-1/bin/install.ps1"))
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build_script:
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# Need to convert from shallow to complete for Pkg.clone to work
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- IF EXIST .git\shallow (git fetch --unshallow)
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- C:\projects\julia\bin\julia -e "versioninfo();
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Pkg.clone(pwd(), \"FastTransforms\"); Pkg.build(\"FastTransforms\")"
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- echo "%JL_BUILD_SCRIPT%"
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- C:\julia\bin\julia -e "%JL_BUILD_SCRIPT%"
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test_script:
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- C:\projects\julia\bin\julia --check-bounds=yes -e "Pkg.test(\"FastTransforms\")"
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- echo "%JL_TEST_SCRIPT%"
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- C:\julia\bin\julia -e "%JL_TEST_SCRIPT%"
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# # Uncomment to support code coverage upload. Should only be enabled for packages
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# # which would have coverage gaps without running on Windows
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# on_success:
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# - echo "%JL_CODECOV_SCRIPT%"
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# - C:\julia\bin\julia -e "%JL_CODECOV_SCRIPT%"

docs/make.jl

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deploydocs(
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repo = "github.com/MikaelSlevinsky/FastTransforms.jl.git",
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repo = "github.com/JuliaApproximation/FastTransforms.jl.git",
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latest = "master",
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julia = "0.6",
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osname = "linux",

src/ChebyshevUltrasphericalPlan.jl

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tempsinλm = similar(tempsinλ)
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# Initialize normalizing constant
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cnλ = Cnλ(0:N,λ)
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cnλ = Cnλ.(0:N,λ)
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cnmλ = similar(cnλ)
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# Get indices
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# Initialize normalizing constant
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cnλ = Cnλ(0:2N,λ)
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cnλ = Cnλ.(0:2N,λ)
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# Initialize orthonormality constants

src/fejer.jl

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plan_fejer1(μ) = FFTW.plan_r2r!(μ, FFTW.REDFT01)
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"""
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Compute nodes of Fejer's first quadrature rule.
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"""
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"""
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Compute nodes of Fejer's second quadrature rule.
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"""
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fejernodes2(::Type{T}, N::Int) where T = T[cospi((k+one(T))/(N+one(T))) for k=0:N-1]
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fejernodes2(::Type{T}, N::Int) where T = T[sinpi((N-2k-one(T))/(2N+two(T))) for k=0:N-1]
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"""
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Compute weights of Fejer's second quadrature rule with modified Chebyshev moments of the second kind ``\\mu``.

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