diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/README.md b/lib/node_modules/@stdlib/stats/base/nanmeanpn/README.md index 4a48a17f883d..6606c121a2a9 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/README.md +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/README.md @@ -67,62 +67,52 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); +var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ]; -var N = floor( x.length / 2 ); - -var v = nanmeanpn( N, x, 2 ); +var v = nanmeanpn( 5, x, 2 ); // returns 1.25 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - + ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = nanmeanpn( N, x1, 2 ); +var v = nanmeanpn( 5, x1, 2 ); // returns 1.25 ``` -#### nanmeanpn.ndarray( N, x, stride, offset ) +#### nanmeanpn.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = nanmeanpn.ndarray( N, x, 1, 0 ); +var v = nanmeanpn.ndarray( 4, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - -var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ]; -var N = floor( x.length / 2 ); +var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var v = nanmeanpn.ndarray( N, x, 2, 1 ); +var v = nanmeanpn.ndarray( 5, x, 2, 1 ); // returns 1.25 ``` @@ -135,8 +125,9 @@ var v = nanmeanpn.ndarray( N, x, 2, 1 ); ## Notes - If `N <= 0`, both functions return `NaN`. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - If every indexed element is `NaN`, both functions return `NaN`. -- Depending on the environment, the typed versions ([`dnanmeanpn`][@stdlib/stats/base/dnanmeanpn], [`snanmeanpn`][@stdlib/stats/base/snanmeanpn], etc.) are likely to be significantly more performant. +- Depending on the environment, the typed versions ([`dnanmeanpn`][@stdlib/stats/strided/dnanmeanpn], [`snanmeanpn`][@stdlib/stats/strided/snanmeanpn], etc.) are likely to be significantly more performant. @@ -149,22 +140,19 @@ var v = nanmeanpn.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var nanmeanpn = require( '@stdlib/stats/base/nanmeanpn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'generic', rand ); console.log( x ); var v = nanmeanpn( x.length, x, 1 ); @@ -196,10 +184,10 @@ console.log( v ); ## See Also -- [`@stdlib/stats/base/dnanmeanpn`][@stdlib/stats/base/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm. +- [`@stdlib/stats/strided/dnanmeanpn`][@stdlib/stats/strided/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm. - [`@stdlib/stats/base/meanpn`][@stdlib/stats/base/meanpn]: calculate the arithmetic mean of a strided array using a two-pass error correction algorithm. - [`@stdlib/stats/base/nanmean`][@stdlib/stats/base/nanmean]: calculate the arithmetic mean of a strided array, ignoring NaN values. -- [`@stdlib/stats/base/snanmeanpn`][@stdlib/stats/base/snanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm. +- [`@stdlib/stats/strided/snanmeanpn`][@stdlib/stats/strided/snanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using a two-pass error correction algorithm. @@ -221,13 +209,15 @@ console.log( v ); -[@stdlib/stats/base/dnanmeanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmeanpn +[@stdlib/stats/strided/dnanmeanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dnanmeanpn [@stdlib/stats/base/meanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/meanpn [@stdlib/stats/base/nanmean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanmean -[@stdlib/stats/base/snanmeanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/snanmeanpn +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/stats/strided/snanmeanpn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/snanmeanpn diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.js index 103d03070e0d..6cdd7e8e84bc 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.js @@ -21,15 +21,30 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; -var nanmeanpn = require( './../lib/nanmeanpn.js' ); +var nanmeanpn = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var nanmeanpn = require( './../lib/nanmeanpn.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*20.0 ) - 10.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.ndarray.js index 33a36b8ecc9c..6c58f0e7f66b 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var nanmeanpn = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var nanmeanpn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*20.0 ) - 10.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/repl.txt index c0982525c1af..38744d4f7987 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -21,8 +21,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -33,25 +33,22 @@ -------- // Standard Usage: > var x = [ 1.0, -2.0, NaN, 2.0 ]; - > {{alias}}( x.length, x, 1 ) + > {{alias}}( 4, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm and alternative indexing semantics. @@ -68,10 +65,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -83,13 +80,12 @@ -------- // Standard Usage: > var x =[ 1.0, -2.0, NaN, 2.0 ]; - > {{alias}}.ndarray( x.length, x, 1, 0 ) + > {{alias}}.ndarray( 4, x, 1, 0 ) ~0.3333 // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/index.d.ts index 1a71ed0d573b..dd602f218912 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/index.d.ts @@ -20,7 +20,12 @@ /// -import { NumericArray } from '@stdlib/types/array'; +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; /** * Interface describing `nanmeanpn`. @@ -31,7 +36,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -40,15 +45,15 @@ interface Routine { * var v = nanmeanpn( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: InputArray, strideX: number ): number; /** * Computes the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +62,7 @@ interface Routine { * var v = nanmeanpn.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: InputArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +70,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/test.ts index ff5d63254cde..57ab036104fa 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/test.ts +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/docs/types/test.ts @@ -16,6 +16,7 @@ * limitations under the License. */ +import AccessorArray = require( '@stdlib/array/base/accessor' ); import nanmeanpn = require( './index' ); @@ -26,6 +27,7 @@ import nanmeanpn = require( './index' ); const x = new Float64Array( 10 ); nanmeanpn( x.length, x, 1 ); // $ExpectType number + nanmeanpn( x.length, new AccessorArray( x ), 1 ); // $ExpectType number } // The compiler throws an error if the function is provided a first argument which is not a number... @@ -85,6 +87,7 @@ import nanmeanpn = require( './index' ); const x = new Float64Array( 10 ); nanmeanpn.ndarray( x.length, x, 1, 0 ); // $ExpectType number + nanmeanpn.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number } // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/examples/index.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/examples/index.js index ed9f17951022..293b4d4fcbe0 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var nanmeanpn = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'generic', rand ); console.log( x ); var v = nanmeanpn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/nanmeanpn.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/accessors.js similarity index 67% rename from lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/nanmeanpn.js rename to lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/accessors.js index d100a5198038..c3e8e687a3a5 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/nanmeanpn.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/accessors.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -33,49 +33,53 @@ * - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). * * @param {PositiveInteger} N - number of indexed elements -* @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example -* var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); * -* var v = nanmeanpn( N, x, 1 ); -* // returns ~0.3333 +* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); +* +* var v = nanmeanpn( 4, arraylike2object( x ), 2, 1 ); +* // returns 1.25 */ -function nanmeanpn( N, x, stride ) { +function nanmeanpn( N, x, strideX, offsetX ) { + var xbuf; + var xget; var ix; var v; var s; var t; var n; var i; - var o; - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; + // Cache references to array data: + xbuf = x.data; + + // Cache references to element accessors: + xget = x.accessors[ 0 ]; + + if ( N === 1 || strideX === 0 ) { + return xget( xbuf, offsetX ); } - o = ix; + ix = offsetX; // Compute an estimate for the mean... s = 0.0; n = 0; for ( i = 0; i < N; i++ ) { - v = x[ ix ]; + v = xget( xbuf, ix ); if ( v === v ) { n += 1; s += v; } - ix += stride; + ix += strideX; } if ( n === 0 ) { return NaN; @@ -83,14 +87,14 @@ function nanmeanpn( N, x, stride ) { s /= n; // Compute an error term... + ix = offsetX; t = 0.0; - ix = o; for ( i = 0; i < N; i++ ) { - v = x[ ix ]; + v = xget( xbuf, ix ); if ( v === v ) { t += v - s; } - ix += stride; + ix += strideX; } return s + (t/n); } diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/index.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/index.js index a02684ec4b69..b47729de96db 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/index.js @@ -27,25 +27,29 @@ * var nanmeanpn = require( '@stdlib/stats/base/nanmeanpn' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = nanmeanpn( N, x, 1 ); +* var v = nanmeanpn( 4, x, 1 ); * // returns ~0.3333 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var nanmeanpn = require( '@stdlib/stats/base/nanmeanpn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = nanmeanpn.ndarray( N, x, 2, 1 ); +* var v = nanmeanpn.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ // MODULES // +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/main.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/main.js index ef999d8428a5..7c161bff3390 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/main.js @@ -20,14 +20,38 @@ // MODULES // -var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var nanmeanpn = require( './nanmeanpn.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var ndarray = require( './ndarray.js' ); // MAIN // -setReadOnly( nanmeanpn, 'ndarray', ndarray ); +/** +* Computes the arithmetic mean of a strided array, ignoring `NaN` values and using a two-pass error correction algorithm. +* +* ## Method +* +* - This implementation uses a two-pass approach, as suggested by Neely (1966). +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - stride length +* @returns {number} arithmetic mean +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nanmeanpn( 4, x, 1 ); +* // returns ~0.3333 +*/ +function nanmeanpn( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); +} // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/ndarray.js index c3ea7b575822..8df6800f993b 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/lib/ndarray.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + // MAIN // /** @@ -34,34 +40,36 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = nanmeanpn( N, x, 2, 1 ); +* var v = nanmeanpn( 4, x, 2, 1 ); * // returns 1.25 */ -function nanmeanpn( N, x, stride, offset ) { +function nanmeanpn( N, x, strideX, offsetX ) { var ix; var v; var s; var t; var n; var i; + var o; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, o, strideX, offsetX ); + } + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; // Compute an estimate for the mean... s = 0.0; @@ -72,7 +80,7 @@ function nanmeanpn( N, x, stride, offset ) { n += 1; s += v; } - ix += stride; + ix += strideX; } if ( n === 0 ) { return NaN; @@ -80,14 +88,14 @@ function nanmeanpn( N, x, stride, offset ) { s /= n; // Compute an error term... - ix = offset; + ix = offsetX; t = 0.0; for ( i = 0; i < N; i++ ) { v = x[ ix ]; if ( v === v ) { t += v - s; } - ix += stride; + ix += strideX; } return s + (t/n); } diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.nanmeanpn.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.main.js similarity index 61% rename from lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.nanmeanpn.js rename to lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.main.js index 2176c2aef076..8d2e5b374737 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.nanmeanpn.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.main.js @@ -21,10 +21,10 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); -var nanmeanpn = require( './../lib/nanmeanpn.js' ); +var nanmeanpn = require( './../lib/main.js' ); // TESTS // @@ -62,6 +62,28 @@ tape( 'the function calculates the arithmetic mean of a strided array', function t.end(); }); +tape( 'the function calculates the arithmetic mean of a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.5, 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, -4.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { var x; var v; @@ -90,7 +112,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -107,15 +128,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = nanmeanpn( N, x, 2 ); + v = nanmeanpn( 5, x, 2 ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessor)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nanmeanpn( 5, toAccessorArray( x ), 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -132,8 +174,30 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN ]; - N = floor( x.length / 2 ); - v = nanmeanpn( N, x, -2 ); + v = nanmeanpn( 5, x, -2 ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 4 + 2.0, + 2.0, // 3 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 1 + 2.0, + NaN, // 0 + NaN + ]; + + v = nanmeanpn( 5, toAccessorArray( x ), -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -151,10 +215,21 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f t.end(); }); +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -172,9 +247,35 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = nanmeanpn( N, x1, 2 ); + v = nanmeanpn( 5, x1, 2 ); + t.strictEqual( v, 1.25, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets (accessors)', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = nanmeanpn( 5, toAccessorArray( x1 ), 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.ndarray.js index c491fb88a624..d79cba633591 100644 --- a/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanmeanpn/test/test.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var nanmeanpn = require( './../lib/ndarray.js' ); @@ -61,6 +61,28 @@ tape( 'the function calculates the arithmetic mean of a strided array', function t.end(); }); +tape( 'the function calculates the arithmetic mean of a strided array (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.5, 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, -4.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { var x; var v; @@ -89,7 +111,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -106,15 +127,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = nanmeanpn( N, x, 2, 0 ); + v = nanmeanpn( 5, x, 2, 0 ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nanmeanpn( 5, toAccessorArray( x ), 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,8 +173,30 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN ]; - N = floor( x.length / 2 ); - v = nanmeanpn( N, x, -2, 8 ); + v = nanmeanpn( 5, x, -2, 8 ); + + t.strictEqual( v, 1.25, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 4 + 2.0, + 2.0, // 3 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 1 + 2.0, + NaN, // 0 + NaN + ]; + + v = nanmeanpn( 5, toAccessorArray( x ), -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -150,8 +214,19 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f t.end(); }); +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nanmeanpn( x.length, toAccessorArray( x ), 0, 0 ); + t.strictEqual( v, 1.0, 'returns expected value' ); + + t.end(); +}); + tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -167,9 +242,31 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = nanmeanpn( N, x, 2, 1 ); + v = nanmeanpn( 5, x, 2, 1 ); + t.strictEqual( v, 1.25, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]; + + v = nanmeanpn( 5, toAccessorArray( x ), 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end();