From 751824c37f4f71ea69455abc2ddde84290d58967 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Thu, 13 Aug 2026 13:06:40 +0530 Subject: [PATCH 1/4] feat: add stats/base/ndarray/dvariancewd --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: passed - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: passed - task: lint_repl_help status: passed - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: passed - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: passed - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: passed - task: lint_license_headers status: passed --- --- .../stats/base/ndarray/dvariancewd/README.md | 203 ++++++++++++++++ .../dvariancewd/benchmark/benchmark.js | 109 +++++++++ .../docs/img/equation_sample_mean.svg | 43 ++++ .../base/ndarray/dvariancewd/docs/repl.txt | 44 ++++ .../ndarray/dvariancewd/docs/types/index.d.ts | 57 +++++ .../ndarray/dvariancewd/docs/types/test.ts | 64 +++++ .../ndarray/dvariancewd/examples/index.js | 35 +++ .../base/ndarray/dvariancewd/lib/index.js | 49 ++++ .../base/ndarray/dvariancewd/lib/main.js | 74 ++++++ .../base/ndarray/dvariancewd/package.json | 76 ++++++ .../base/ndarray/dvariancewd/test/test.js | 227 ++++++++++++++++++ 11 files changed, 981 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md new file mode 100644 index 000000000000..c13dd977790f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md @@ -0,0 +1,203 @@ + + +# dvariancewd + +> Calculate the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. + +
+ +The population [variance][variance] of a finite size population of size `N` is given by + + + +```math +\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 +``` + + + + + +where the population mean is given by + + + +```math +\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i +``` + + + + + +Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 +``` + + + + + +where the sample mean is given by + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. + +
+ + + +
+ +## Usage + +```javascript +var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); +``` + +#### dvariancewd( arrays ) + +Computes the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = dvariancewd( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -50, 50, opts ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = dvariancewd( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## References + +- Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022][@welford:1962a]. +- van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961][@vanreeken:1968a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022 + +[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js new file mode 100644 index 000000000000..7ee053a1a8c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dvariancewd = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var x; + + x = uniform( [ len ], -10.0, 10.0, options ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = dvariancewd( [ x, correction ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt new file mode 100644 index 000000000000..427c169dd433 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt @@ -0,0 +1,44 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional double-precision floating-point + ndarray using Welford's algorithm. + + If provided an empty one-dimensional ndarray, the function returns `NaN`. + + If `N - c` is less than or equal to `0` (where `N` corresponds to the number + of elements in the input ndarray and `c` corresponds to the provided degrees + of freedom adjustment), the function returns `NaN`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray specifying the degrees of freedom + adjustment. Providing a non-zero degrees of freedom adjustment has the + effect of adjusting the divisor during the calculation of the variance + according to `N-c` where `N` is the number of elements in the input + ndarray and `c` corresponds to the provided degrees of freedom + adjustment. When computing the variance of a population, setting this + parameter to `0` is the standard choice (i.e., the provided array + contains data constituting an entire population). When computing the + corrected sample variance, setting this parameter to `1` is the standard + choice (i.e., the provided array contains data sampled from a larger + population; this is commonly referred to as Bessel's correction). + + Returns + ------- + out: number + The variance. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var opts = { 'dtype': 'float64' }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > {{alias}}( [ x, correction ] ) + ~4.3333 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts new file mode 100644 index 000000000000..3fe395c5f337 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. +* +* @param arrays - array-like object containing ndarrays +* @returns variance +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ +declare function dvariancewd( arrays: [ float64ndarray, typedndarray ] ): number; + + +// EXPORTS // + +export = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts new file mode 100644 index 000000000000..e6bd585f9a83 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dvariancewd = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + dvariancewd( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dvariancewd( '10' ); // $ExpectError + dvariancewd( 10 ); // $ExpectError + dvariancewd( true ); // $ExpectError + dvariancewd( false ); // $ExpectError + dvariancewd( null ); // $ExpectError + dvariancewd( undefined ); // $ExpectError + dvariancewd( [] ); // $ExpectError + dvariancewd( {} ); // $ExpectError + dvariancewd( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + dvariancewd(); // $ExpectError + dvariancewd( [ x, correction ], 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js new file mode 100644 index 000000000000..b6885553882b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dvariancewd = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -50, 50, opts ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = dvariancewd( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js new file mode 100644 index 000000000000..53946a87e73e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* @module @stdlib/stats/base/ndarray/dvariancewd +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js new file mode 100644 index 000000000000..a4beb3fc2662 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/stats/strided/dvariancewd' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {number} variance +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = dvariancewd( [ x, correction ] ); +* // returns ~4.3333 +*/ +function dvariancewd( arrays ) { + var correction; + var x; + + x = arrays[ 0 ]; + correction = ndarraylike2scalar( arrays[ 1 ] ); + + return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json new file mode 100644 index 000000000000..3cdefb50c777 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/base/ndarray/dvariancewd", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "variance", + "var", + "deviation", + "dispersion", + "spread", + "sample variance", + "unbiased", + "dvariancewd", + "std", + "ndarray", + "float64", + "double", + "double-precision", + "typed", + "float64array", + "welford" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js new file mode 100644 index 000000000000..171c44fe7609 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dvariancewd = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dvariancewd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dvariancewd.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 53.5 / (x.length-1); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ -4.0, -5.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = 0.5; + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 0, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { + var correction; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array( [ 1.0 ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 1, 1, 0 ), correction ] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var expected; + var opts; + var x; + var v; + + opts = { + 'dtype': 'float64' + }; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + correction = scalar2ndarray( 1.0, opts ); + + v = dvariancewd( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); From 9d1b8155102e416271e6b4d4383a1b9de48f4929 Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Thu, 13 Aug 2026 13:08:31 +0530 Subject: [PATCH 2/4] Revert "feat: add stats/base/ndarray/dvariancewd" This reverts commit 751824c37f4f71ea69455abc2ddde84290d58967. --- .../stats/base/ndarray/dvariancewd/README.md | 203 ---------------- .../dvariancewd/benchmark/benchmark.js | 109 --------- .../docs/img/equation_sample_mean.svg | 43 ---- .../base/ndarray/dvariancewd/docs/repl.txt | 44 ---- .../ndarray/dvariancewd/docs/types/index.d.ts | 57 ----- .../ndarray/dvariancewd/docs/types/test.ts | 64 ----- .../ndarray/dvariancewd/examples/index.js | 35 --- .../base/ndarray/dvariancewd/lib/index.js | 49 ---- .../base/ndarray/dvariancewd/lib/main.js | 74 ------ .../base/ndarray/dvariancewd/package.json | 76 ------ .../base/ndarray/dvariancewd/test/test.js | 227 ------------------ 11 files changed, 981 deletions(-) delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json delete mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md deleted file mode 100644 index c13dd977790f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/README.md +++ /dev/null @@ -1,203 +0,0 @@ - - -# dvariancewd - -> Calculate the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. - -
- -The population [variance][variance] of a finite size population of size `N` is given by - - - -```math -\sigma^2 = \frac{1}{N} \sum_{i=0}^{N-1} (x_i - \mu)^2 -``` - - - - - -where the population mean is given by - - - -```math -\mu = \frac{1}{N} \sum_{i=0}^{N-1} x_i -``` - - - - - -Often in the analysis of data, the true population [variance][variance] is not known _a priori_ and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population [variance][variance], the result is biased and yields an **uncorrected sample variance**. To compute a **corrected sample variance** for a sample of size `n`, - - - -```math -s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 -``` - - - - - -where the sample mean is given by - - - -```math -\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i -``` - - - - - -The use of the term `n-1` is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample variance and population variance. Depending on the characteristics of the population distribution, other correction factors (e.g., `n-1.5`, `n+1`, etc) can yield better estimators. - -
- - - -
- -## Usage - -```javascript -var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); -``` - -#### dvariancewd( arrays ) - -Computes the [variance][variance] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. - -```javascript -var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -var correction = scalar2ndarray( 1.0, opts ); - -var v = dvariancewd( [ x, correction ] ); -// returns ~4.3333 -``` - -The function has the following parameters: - -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. - - a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `N` is the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - -
- - - -
- -## Notes - -- If provided an empty one-dimensional ndarray, the function returns `NaN`. -- If `N - c` is less than or equal to `0` (where `N` corresponds to the number of elements in the input ndarray and `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. - -
- - - -
- -## Examples - - - -```javascript -var discreteUniform = require( '@stdlib/random/discrete-uniform' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); -var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = discreteUniform( [ 10 ], -50, 50, opts ); -console.log( ndarray2array( x ) ); - -var correction = scalar2ndarray( 1.0, opts ); -var v = dvariancewd( [ x, correction ] ); -console.log( v ); -``` - -
- - - -* * * - -
- -## References - -- Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022][@welford:1962a]. -- van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961][@vanreeken:1968a]. - -
- - - - - -
- -
- - - - - -
- -[variance]: https://en.wikipedia.org/wiki/Variance - -[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022 - -[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961 - -
- - diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js deleted file mode 100644 index 7ee053a1a8c9..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/benchmark/benchmark.js +++ /dev/null @@ -1,109 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var format = require( '@stdlib/string/format' ); -var pkg = require( './../package.json' ).name; -var dvariancewd = require( './../lib' ); - - -// VARIABLES // - -var options = { - 'dtype': 'float64' -}; - - -// FUNCTIONS // - -/** -* Creates a benchmark function. -* -* @private -* @param {PositiveInteger} len - array length -* @returns {Function} benchmark function -*/ -function createBenchmark( len ) { - var correction; - var x; - - x = uniform( [ len ], -10.0, 10.0, options ); - correction = scalar2ndarray( 1.0, options ); - - return benchmark; - - /** - * Benchmark function. - * - * @private - * @param {Benchmark} b - benchmark instance - */ - function benchmark( b ) { - var v; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - v = dvariancewd( [ x, correction ] ); - if ( isnan( v ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( v ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); - } -} - - -// MAIN // - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - var len; - var min; - var max; - var f; - var i; - - min = 1; // 10^min - max = 6; // 10^max - - for ( i = min; i <= max; i++ ) { - len = pow( 10, i ); - f = createBenchmark( len ); - bench( format( '%s:len=%d', pkg, len ), f ); - } -} - -main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg deleted file mode 100644 index aea7a5f6687a..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/img/equation_sample_mean.svg +++ /dev/null @@ -1,43 +0,0 @@ - -x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i - - - \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt deleted file mode 100644 index 427c169dd433..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/repl.txt +++ /dev/null @@ -1,44 +0,0 @@ - -{{alias}}( arrays ) - Computes the variance of a one-dimensional double-precision floating-point - ndarray using Welford's algorithm. - - If provided an empty one-dimensional ndarray, the function returns `NaN`. - - If `N - c` is less than or equal to `0` (where `N` corresponds to the number - of elements in the input ndarray and `c` corresponds to the provided degrees - of freedom adjustment), the function returns `NaN`. - - Parameters - ---------- - arrays: ArrayLikeObject - Array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. - - a zero-dimensional ndarray specifying the degrees of freedom - adjustment. Providing a non-zero degrees of freedom adjustment has the - effect of adjusting the divisor during the calculation of the variance - according to `N-c` where `N` is the number of elements in the input - ndarray and `c` corresponds to the provided degrees of freedom - adjustment. When computing the variance of a population, setting this - parameter to `0` is the standard choice (i.e., the provided array - contains data constituting an entire population). When computing the - corrected sample variance, setting this parameter to `1` is the standard - choice (i.e., the provided array contains data sampled from a larger - population; this is commonly referred to as Bessel's correction). - - Returns - ------- - out: number - The variance. - - Examples - -------- - > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var opts = { 'dtype': 'float64' }; - > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); - > {{alias}}( [ x, correction ] ) - ~4.3333 - - See Also - -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts deleted file mode 100644 index 3fe395c5f337..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/index.d.ts +++ /dev/null @@ -1,57 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -// TypeScript Version: 4.1 - -/// - -import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; - -/** -* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* ## Notes -* -* - The function expects the following ndarrays: -* -* - a one-dimensional input ndarray. -* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. -* -* @param arrays - array-like object containing ndarrays -* @returns variance -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ -declare function dvariancewd( arrays: [ float64ndarray, typedndarray ] ): number; - - -// EXPORTS // - -export = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts deleted file mode 100644 index e6bd585f9a83..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/docs/types/test.ts +++ /dev/null @@ -1,64 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable space-in-parens */ - -import zeros = require( '@stdlib/ndarray/zeros' ); -import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -import dvariancewd = require( './index' ); - - -// TESTS // - -// The function returns a number... -{ - const x = zeros( [ 10 ], { - 'dtype': 'float64' - }); - const correction = scalar2ndarray( 1.0, { - 'dtype': 'float64' - }); - - dvariancewd( [ x, correction ] ); // $ExpectType number -} - -// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... -{ - dvariancewd( '10' ); // $ExpectError - dvariancewd( 10 ); // $ExpectError - dvariancewd( true ); // $ExpectError - dvariancewd( false ); // $ExpectError - dvariancewd( null ); // $ExpectError - dvariancewd( undefined ); // $ExpectError - dvariancewd( [] ); // $ExpectError - dvariancewd( {} ); // $ExpectError - dvariancewd( ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an unsupported number of arguments... -{ - const x = zeros( [ 10 ], { - 'dtype': 'float64' - }); - const correction = scalar2ndarray( 1.0, { - 'dtype': 'float64' - }); - - dvariancewd(); // $ExpectError - dvariancewd( [ x, correction ], 10 ); // $ExpectError -} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js deleted file mode 100644 index b6885553882b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/examples/index.js +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var discreteUniform = require( '@stdlib/random/discrete-uniform' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray2array = require( '@stdlib/ndarray/to-array' ); -var dvariancewd = require( './../lib' ); - -var opts = { - 'dtype': 'float64' -}; - -var x = discreteUniform( [ 10 ], -50, 50, opts ); -console.log( ndarray2array( x ) ); - -var correction = scalar2ndarray( 1.0, opts ); -var v = dvariancewd( [ x, correction ] ); -console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js deleted file mode 100644 index 53946a87e73e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/index.js +++ /dev/null @@ -1,49 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* @module @stdlib/stats/base/ndarray/dvariancewd -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* var dvariancewd = require( '@stdlib/stats/base/ndarray/dvariancewd' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ - -// MODULES // - -var main = require( './main.js' ); - - -// EXPORTS // - -module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js deleted file mode 100644 index a4beb3fc2662..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/lib/main.js +++ /dev/null @@ -1,74 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); -var getStride = require( '@stdlib/ndarray/base/stride' ); -var getOffset = require( '@stdlib/ndarray/base/offset' ); -var getData = require( '@stdlib/ndarray/base/data-buffer' ); -var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); -var strided = require( '@stdlib/stats/strided/dvariancewd' ).ndarray; - - -// MAIN // - -/** -* Computes the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. -* -* ## Notes -* -* - The function expects the following ndarrays: -* -* - a one-dimensional input ndarray. -* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. -* -* @param {ArrayLikeObject} arrays - array-like object containing ndarrays -* @returns {number} variance -* -* @example -* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); -* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -* -* var opts = { -* 'dtype': 'float64' -* }; -* -* var x = new Float64Vector( [ 1.0, -2.0, 2.0 ] ); -* -* var correction = scalar2ndarray( 1.0, opts ); -* -* var v = dvariancewd( [ x, correction ] ); -* // returns ~4.3333 -*/ -function dvariancewd( arrays ) { - var correction; - var x; - - x = arrays[ 0 ]; - correction = ndarraylike2scalar( arrays[ 1 ] ); - - return strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = dvariancewd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json deleted file mode 100644 index 3cdefb50c777..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/package.json +++ /dev/null @@ -1,76 +0,0 @@ -{ - "name": "@stdlib/stats/base/ndarray/dvariancewd", - "version": "0.0.0", - "description": "Compute the variance of a one-dimensional double-precision floating-point ndarray using Welford's algorithm.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "benchmark": "./benchmark", - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdmath", - "statistics", - "stats", - "mathematics", - "math", - "variance", - "var", - "deviation", - "dispersion", - "spread", - "sample variance", - "unbiased", - "dvariancewd", - "std", - "ndarray", - "float64", - "double", - "double-precision", - "typed", - "float64array", - "welford" - ], - "__stdlib__": {} -} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js deleted file mode 100644 index 171c44fe7609..000000000000 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dvariancewd/test/test.js +++ /dev/null @@ -1,227 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2026 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. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var Float64Array = require( '@stdlib/array/float64' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); -var dvariancewd = require( './../lib' ); - - -// FUNCTIONS // - -/** -* Returns a one-dimensional ndarray. -* -* @private -* @param {Collection} buffer - underlying data buffer -* @param {NonNegativeInteger} length - number of indexed elements -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - index offset -* @returns {ndarray} one-dimensional ndarray -*/ -function vector( buffer, length, stride, offset ) { - return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); -} - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof dvariancewd, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( dvariancewd.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the variance of a one-dimensional ndarray', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - expected = 53.5 / (x.length-1); - t.strictEqual( v, expected, 'returns expected value' ); - - x = new Float64Array( [ -4.0, -5.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - expected = 0.5; - t.strictEqual( v, expected, 'returns expected value' ); - - x = new Float64Array( [ NaN ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - x = new Float64Array( [ NaN, NaN ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, x.length, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var correction; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 0, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided a correction argument yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) { - var correction; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array( [ 1.0 ] ); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 1, 1, 0 ), correction ] ); - t.strictEqual( isnan( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, 2, 0 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, -2, 6 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var correction; - var expected; - var opts; - var x; - var v; - - opts = { - 'dtype': 'float64' - }; - - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - correction = scalar2ndarray( 1.0, opts ); - - v = dvariancewd( [ vector( x, 4, 2, 1 ), correction ] ); - expected = 6.25; - t.strictEqual( v, expected, 'returns expected value' ); - - t.end(); -}); From e9446cfe58483ac266570305126ed77c2275a23a Mon Sep 17 00:00:00 2001 From: 0PrashantYadav0 Date: Tue, 18 Aug 2026 10:16:02 +0530 Subject: [PATCH 3/4] feat: add @stdlib/blas/ext/base/nannsum/results/struct-factory --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: passed - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: passed - task: lint_repl_help status: passed - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: passed - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: passed - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: passed - task: lint_license_headers status: passed --- --- .../nannsum/results/struct-factory/README.md | 127 ++++++++++++++++++ .../struct-factory/benchmark/benchmark.js | 54 ++++++++ .../results/struct-factory/docs/repl.txt | 25 ++++ .../struct-factory/docs/types/index.d.ts | 104 ++++++++++++++ .../results/struct-factory/docs/types/test.ts | 54 ++++++++ .../results/struct-factory/examples/index.js | 45 +++++++ .../results/struct-factory/lib/index.js | 43 ++++++ .../results/struct-factory/lib/main.js | 62 +++++++++ .../results/struct-factory/package.json | 68 ++++++++++ .../results/struct-factory/test/test.js | 112 +++++++++++++++ 10 files changed, 694 insertions(+) create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/package.json create mode 100644 lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md new file mode 100644 index 000000000000..6dec0a9e1081 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md @@ -0,0 +1,127 @@ + + +# structFactory + +> Create a new [`struct`][@stdlib/dstructs/struct] constructor tailored to a specified floating-point data type. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var structFactory = require( '@stdlib/blas/ext/base/nannsum/results/struct-factory' ); +``` + +#### structFactory( dtype ) + +Returns a new [`struct`][@stdlib/dstructs/struct] constructor tailored to a specified floating-point data type. + +```javascript +var Struct = structFactory( 'float64' ); +// returns + +var s = new Struct(); +// returns +``` + +The function supports the following parameters: + +- **dtype**: floating-point data type for storing floating-point results. Must be either `'float64'` or `'float32'`. + +
+ + + + + +
+ +## Notes + +- A [`struct`][@stdlib/dstructs/struct] provides a fixed-width composite data structure for storing NaN-aware summation results and provides an ABI-stable data layout for JavaScript-C interoperation. + +
+ + + + + +
+ +## Examples + + + +```javascript +var structFactory = require( '@stdlib/blas/ext/base/nannsum/results/struct-factory' ); +var BigInt = require( '@stdlib/bigint/ctor' ); + +var Struct = structFactory( 'float64' ); +var results = new Struct({ + 'sum': 11.7586, + 'count': BigInt( 5 ) +}); + +var str = results.toString({ + 'format': 'linear' +}); +console.log( str ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/dstructs/struct]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/dstructs/struct + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js new file mode 100644 index 000000000000..638c34148207 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isFunction = require( '@stdlib/assert/is-function' ); +var pkg = require( './../package.json' ).name; +var factory = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var v; + var i; + + values = [ + 'float64', + 'float32' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = factory( values[ i%values.length ] ); + if ( typeof v !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( !isFunction( v ) ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/repl.txt new file mode 100644 index 000000000000..e6a0c632d678 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( dtype ) + Returns a new struct constructor tailored to a specified floating-point data + type. + + Parameters + ---------- + dtype: string + Floating-point data type for storing floating-point results. + + Returns + ------- + fcn: Function + Struct constructor. + + Examples + -------- + > var S = {{alias}}( 'float64' ); + > var r = new S(); + > r.toString() + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts new file mode 100644 index 000000000000..7ba249124222 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts @@ -0,0 +1,104 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing NaN-aware summation results. +*/ +interface Results { + /** + * Sum of non-NaN elements. + */ + sum?: number; + + /** + * Number of non-NaN elements. + */ + count?: bigint; +} + +/** +* Interface describing a struct data structure. +*/ +declare class Struct { + /** + * Struct constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns struct + */ + constructor( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ); + + /** + * Sum of non-NaN elements. + */ + sum: number; + + /** + * Number of non-NaN elements. + */ + count: bigint; +} + +/** +* Interface defining a struct constructor which is both "newable" and "callable". +*/ +interface StructConstructor { + /** + * Struct constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns struct + */ + new( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ): Struct; + + /** + * Struct constructor. + * + * @param arg - buffer or data object + * @param byteOffset - byte offset + * @param byteLength - maximum byte length + * @returns struct + */ + ( arg?: ArrayBuffer | Results, byteOffset?: number, byteLength?: number ): Struct; +} + +/** +* Returns a new struct constructor tailored to a specified floating-point data type. +* +* @param dtype - floating-point data type for storing floating-point results +* @returns struct constructor +* +* @example +* var Struct = structFactory( 'float64' ); +* // returns +* +* var s = new Struct(); +* // returns +*/ +declare function structFactory( dtype: 'float64' | 'float32' ): StructConstructor; + + +// EXPORTS // + +export = structFactory; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts new file mode 100644 index 000000000000..cc8113b73996 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts @@ -0,0 +1,54 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import structFactory = require( './index' ); + + +// TESTS // + +// The function returns a function... +{ + structFactory( 'float64' ); // $ExpectType StructConstructor + structFactory( 'float32' ); // $ExpectType StructConstructor +} + +// The compiler throws an error if not provided a supported data type... +{ + structFactory( 10 ); // $ExpectError + structFactory( true ); // $ExpectError + structFactory( false ); // $ExpectError + structFactory( null ); // $ExpectError + structFactory( undefined ); // $ExpectError + structFactory( [] ); // $ExpectError + structFactory( {} ); // $ExpectError + structFactory( ( x: number ): number => x ); // $ExpectError +} + +// The function returns a function which returns a struct object... +{ + const Struct = structFactory( 'float64' ); + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const s1 = new Struct( new ArrayBuffer( 80 ) ); // $ExpectType Struct + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const s2 = new Struct( new ArrayBuffer( 80 ), 8 ); // $ExpectType Struct + + // eslint-disable-next-line @typescript-eslint/no-unused-vars + const s3 = new Struct( new ArrayBuffer( 80 ), 8, 16 ); // $ExpectType Struct +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js new file mode 100644 index 000000000000..989a3aadb2bb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var BigInt = require( '@stdlib/bigint/ctor' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var structFactory = require( './../lib' ); + +var Struct = structFactory( 'float64' ); +var results = new Struct({ + 'sum': 11.7586, + 'count': BigInt( 5 ) +}); + +var str = results.toString({ + 'format': 'linear' +}); +console.log( str ); + +Struct = structFactory( 'float32' ); +results = new Struct({ + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) +}); + +str = results.toString({ + 'format': 'linear' +}); +console.log( str ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js new file mode 100644 index 000000000000..db61c12910ac --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Create a new struct constructor tailored to a specified floating-point data type. +* +* @module @stdlib/blas/ext/base/nannsum/results/struct-factory +* +* @example +* var structFactory = require( '@stdlib/blas/ext/base/nannsum/results/struct-factory' ); +* +* var Struct = structFactory( 'float64' ); +* // returns +* +* var s = new Struct(); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js new file mode 100644 index 000000000000..a880376c6183 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var struct = require( '@stdlib/dstructs/struct' ); + + +// MAIN // + +/** +* Returns a new struct constructor tailored to a specified floating-point data type. +* +* @param {string} dtype - floating-point data type +* @returns {Function} struct constructor +* +* @example +* var Struct = factory( 'float64' ); +* // returns +* +* var s = new Struct(); +* // returns +*/ +function factory( dtype ) { + var schema = [ + { + 'name': 'sum', + 'description': 'sum of non-NaN elements', + 'type': dtype, + 'castingMode': 'mostly-safe' + }, + { + 'name': 'count', + 'description': 'number of non-NaN elements', + 'type': 'int64', + 'castingMode': 'none' + } + ]; + return struct( schema ); +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/package.json b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/package.json new file mode 100644 index 000000000000..1ab6d8ad052e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/blas/ext/base/nannsum/results/struct-factory", + "version": "0.0.0", + "description": "Create a new struct constructor tailored to a specified floating-point data type.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "linear", + "algebra", + "linalg", + "nannsum", + "nan", + "sum", + "utilities", + "utility", + "utils", + "util", + "struct", + "results" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js new file mode 100644 index 000000000000..0ef12a0abfc7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 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. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var BigInt = require( '@stdlib/bigint/ctor' ); +var Number = require( '@stdlib/number/ctor' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var structFactory = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof structFactory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not a supported data type', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + structFactory( value ); + }; + } +}); + +tape( 'the function returns a constructor for creating a fixed-width results object (dtype=float64)', function test( t ) { + var expected; + var actual; + var Struct; + + Struct = structFactory( 'float64' ); + t.strictEqual( typeof Struct, 'function', 'returns expected value' ); + + actual = new Struct({ + 'sum': 11.7586, + 'count': BigInt( 5 ) + }); + + expected = { + 'sum': 11.7586, + 'count': 5 + }; + + t.strictEqual( actual instanceof Struct, true, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a constructor for creating a fixed-width results object (dtype=float32)', function test( t ) { + var expected; + var actual; + var Struct; + + Struct = structFactory( 'float32' ); + t.strictEqual( typeof Struct, 'function', 'returns expected value' ); + + actual = new Struct({ + 'sum': f32( 11.7586 ), + 'count': BigInt( 5 ) + }); + + expected = { + 'sum': f32( 11.7586 ), + 'count': 5 + }; + + t.strictEqual( actual instanceof Struct, true, 'returns expected value' ); + t.strictEqual( actual.sum, expected.sum, 'returns expected value' ); + t.strictEqual( Number( actual.count ), expected.count, 'returns expected value' ); + t.end(); +}); From 55706a023fe5e33aaa17bec2dee40d80b1dfedfc Mon Sep 17 00:00:00 2001 From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> Date: Tue, 18 Aug 2026 05:01:07 +0000 Subject: [PATCH 4/4] chore: update copyright years --- .../blas/ext/base/nannsum/results/struct-factory/README.md | 2 +- .../base/nannsum/results/struct-factory/benchmark/benchmark.js | 2 +- .../base/nannsum/results/struct-factory/docs/types/index.d.ts | 2 +- .../ext/base/nannsum/results/struct-factory/docs/types/test.ts | 2 +- .../ext/base/nannsum/results/struct-factory/examples/index.js | 2 +- .../blas/ext/base/nannsum/results/struct-factory/lib/index.js | 2 +- .../blas/ext/base/nannsum/results/struct-factory/lib/main.js | 2 +- .../blas/ext/base/nannsum/results/struct-factory/test/test.js | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md index 6dec0a9e1081..6e77e76187a8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2020 The Stdlib Authors. +Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js index 638c34148207..f06fde75adee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts index 7ba249124222..b98507319b9a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/index.d.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts index cc8113b73996..6f4e27ee6e2a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/docs/types/test.ts @@ -1,7 +1,7 @@ /* * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js index 989a3aadb2bb..f535cfbf93b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js index db61c12910ac..8b7b11ce9c89 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js index a880376c6183..66a9280edbf4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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. diff --git a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js index 0ef12a0abfc7..f2124b53ac21 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js +++ b/lib/node_modules/@stdlib/blas/ext/base/nannsum/results/struct-factory/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2026 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.