From 0b507d5cec7a44b1139171b6c4ddca4e43eeb61c Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Thu, 8 Jan 2026 18:40:23 +0000 Subject: [PATCH 1/5] feat(variancech): add a package stats/base/ndarray/variancech --- 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 status: passed - 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/variancech/README.md | 206 ++++++++++++++++ .../ndarray/variancech/benchmark/benchmark.js | 106 ++++++++ .../docs/img/equation_sample_mean.svg | 43 ++++ .../base/ndarray/variancech/docs/repl.txt | 55 +++++ .../ndarray/variancech/docs/types/index.d.ts | 52 ++++ .../ndarray/variancech/docs/types/test.ts | 65 +++++ .../base/ndarray/variancech/examples/index.js | 37 +++ .../base/ndarray/variancech/lib/index.js | 54 +++++ .../stats/base/ndarray/variancech/lib/main.js | 69 ++++++ .../base/ndarray/variancech/package.json | 71 ++++++ .../base/ndarray/variancech/test/test.js | 227 ++++++++++++++++++ 11 files changed, 985 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/img/equation_sample_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/variancech/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md new file mode 100644 index 000000000000..0048317cd355 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md @@ -0,0 +1,206 @@ + + +# variancech + +> Calculate the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. + +
+ +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 variancech = require( '@stdlib/stats/base/ndarray/variancech' ); +``` + +#### variancech( arrays ) + +Computes the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. + +```javascript +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var opts = { + 'dtype': 'generic' +}; + +var xbuf = [ 1.0, -2.0, 2.0 ]; +var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +var correction = scalar2ndarray( 1.0, opts ); + +var v = variancech( [ x, correction ] ); +// returns ~4.3333 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing two elements: a one-dimensional input ndarray and 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/array/discrete-uniform' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancech = require( '@stdlib/stats/base/ndarray/variancech' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancech( [ x, correction ] ); +console.log( v ); +``` + +
+ + + +* * * + +
+ +## 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][@neely:1966a]. +- Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis: 242–47. doi:[10.1080/00031305.1983.10483115][@chan:1983a]. +- Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." in _SSDBM '18: Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. Association for Computing Machinery. doi:[10.1145/3221664.3221674][@schubert:2018a]. + +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[@neely:1966a]: https://doi.org/10.1145/365719.365958 + +[@chan:1983a]: https://doi.org/10.1080/00031305.1983.10483115 + +[@schubert:2018a]: https://doi.org/10.1145/3221664.3221674 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/benchmark/benchmark.js new file mode 100644 index 000000000000..d9c5c0efc592 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @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/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var variancech = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var correction; + var xbuf; + var x; + + xbuf = uniform( len, -10.0, 10.0, options ); + x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); + correction = scalar2ndarray( 1.0, options ); + + return benchmark; + + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = variancech( [ 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/variancech/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/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/variancech/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/repl.txt new file mode 100644 index 000000000000..0b45711ef497 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/repl.txt @@ -0,0 +1,55 @@ + +{{alias}}( arrays ) + Computes the variance of a one-dimensional ndarray using a + one-pass trial mean 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 two elements: a one-dimensional input + ndarray and 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 + -------- + // Create input ndarray: + > var xbuf = [ 1.0, -2.0, 2.0 ]; + > var dt = 'generic'; + > var sh = [ xbuf.length ]; + > var st = [ 1 ]; + > var oo = 0; + > var ord = 'row-major'; + > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord ); + + // Create correction ndarray: + > var opts = { 'dtype': dt }; + > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + // Compute the variance: + > {{alias}}( [ x, correction ] ) + ~4.333 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/index.d.ts new file mode 100644 index 000000000000..e835d720458c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @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 { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the variance of a one-dimensional ndarray using a one-pass trial mean algorithm. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns variance +* +* @example +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancech( [ x, correction ] ); +* // returns ~4.333 +*/ +declare function variancech = typedndarray>( arrays: [ T, T ] ): number; + + +// EXPORTS // + +export = variancech; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/test.ts new file mode 100644 index 000000000000..ac651503fc7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/docs/types/test.ts @@ -0,0 +1,65 @@ +/* +* @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 variancech = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + variancech( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + variancech( '10' ); // $ExpectError + variancech( 10 ); // $ExpectError + variancech( true ); // $ExpectError + variancech( false ); // $ExpectError + variancech( null ); // $ExpectError + variancech( undefined ); // $ExpectError + variancech( [] ); // $ExpectError + variancech( {} ); // $ExpectError + variancech( ( 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' + }); + + variancech(); // $ExpectError + variancech( [ x, correction ], 10 ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/examples/index.js new file mode 100644 index 000000000000..5829b7cb908c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/examples/index.js @@ -0,0 +1,37 @@ +/** +* @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/array/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var variancech = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var xbuf = discreteUniform( 10, -50, 50, opts ); +var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' ); +console.log( ndarray2array( x ) ); + +var correction = scalar2ndarray( 1.0, opts ); +var v = variancech( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js new file mode 100644 index 000000000000..cfce2b3c69c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js @@ -0,0 +1,54 @@ +/** +* @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 ndarray using a two-pass algorithm proposed by Chan et al. +* +* @module @stdlib/stats/base/ndarray/variancech +* +* @example +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var variancech = require( '@stdlib/stats/base/ndarray/variancech' ); +* +* var opts = { +* 'dtype': 'generic' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = [ 1.0, -2.0, 2.0 ]; +* var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' ); +* +* // Specify the degrees of freedom adjustment: +* var correction = scalar2ndarray( 1.0, opts ); +* +* // Compute the variance: +* var v = variancech( [ 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/variancech/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js new file mode 100644 index 000000000000..dcc70ba55064 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js @@ -0,0 +1,69 @@ +/** +* @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/variancech' ).ndarray; + + +// MAIN // + +/** +* Computes the variance of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. +* +* @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns {number} variance +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/base/ctor' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* var xbuf = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var x = new ndarray( opts.dtype, xbuf, [ 4 ], [ 2 ], 1, 'row-major' ); +* +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = variancech( [ x, correction ] ); +* // returns 6.25 +*/ +function variancech( 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 = variancech; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json new file mode 100644 index 000000000000..529dcea29ff9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/base/ndarray/variancech", + "version": "0.0.0", + "description": "Compute the variance of a one-dimensional ndarray using a two-pass 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", + "var", + "deviation", + "dispersion", + "spread", + "sample variance", + "unbiased", + "variance", + "std", + "ndarray", + "typed", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/test/test.js new file mode 100644 index 000000000000..8cea716fb983 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/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 variancech = 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 variancech, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( variancech.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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ 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 = variancech( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 6.25; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); From f887c931a4c094eb1e96a468ac3402b45db8db7e Mon Sep 17 00:00:00 2001 From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> Date: Thu, 8 Jan 2026 18:44:10 +0000 Subject: [PATCH 2/5] chore: update copyright years --- .../@stdlib/stats/base/ndarray/variancech/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md index 0048317cd355..43845465ac95 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2025 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. From 847879bbfc0ee45a815e8e503fc2c5b7625fc276 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Fri, 9 Jan 2026 04:10:34 +0000 Subject: [PATCH 3/5] fix(variancech): fixing a package stats/base/ndarray/variancech --- 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 status: passed - task: lint_package_json status: na - task: lint_repl_help status: na - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: na - task: lint_javascript_benchmarks status: na - 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: na - task: lint_license_headers status: passed --- --- .../@stdlib/stats/base/ndarray/variancech/README.md | 4 ++-- .../@stdlib/stats/base/ndarray/variancech/lib/index.js | 2 +- .../@stdlib/stats/base/ndarray/variancech/lib/main.js | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md index 43845465ac95..d90560491b64 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/README.md @@ -20,7 +20,7 @@ limitations under the License. # variancech -> Calculate the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. +> Calculate the [variance][variance] of a one-dimensional ndarray using a one-pass trial mean algorithm.
@@ -100,7 +100,7 @@ var variancech = require( '@stdlib/stats/base/ndarray/variancech' ); #### variancech( arrays ) -Computes the [variance][variance] of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. +Computes the [variance][variance] of a one-dimensional ndarray using a one-pass trial mean algorithm. ```javascript var ndarray = require( '@stdlib/ndarray/base/ctor' ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js index cfce2b3c69c4..f6af997308b9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Compute the variance of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. +* Compute the variance of a one-dimensional ndarray using a one-pass trial mean algorithm. * * @module @stdlib/stats/base/ndarray/variancech * diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js index dcc70ba55064..e82c2c9055ff 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/lib/main.js @@ -31,7 +31,7 @@ var strided = require( '@stdlib/stats/strided/variancech' ).ndarray; // MAIN // /** -* Computes the variance of a one-dimensional ndarray using a two-pass algorithm proposed by Chan et al. +* Computes the variance of a one-dimensional ndarray using a one-pass trial mean algorithm. * * @param {ArrayLikeObject} arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment * @returns {number} variance From c96ace8c04561dbd2572bef64f29aa4322af1b44 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Fri, 9 Jan 2026 04:19:50 +0000 Subject: [PATCH 4/5] fix(variancech): fixing a package stats/base/ndarray/variancech --- 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 status: na - task: lint_package_json status: passed - task: lint_repl_help status: na - task: lint_javascript_src status: na - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: na - task: lint_javascript_benchmarks status: na - 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: na - task: lint_license_headers status: passed --- --- .../@stdlib/stats/base/ndarray/variancech/package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json index 529dcea29ff9..44325b3ab286 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/variancech", "version": "0.0.0", - "description": "Compute the variance of a one-dimensional ndarray using a two-pass algorithm.", + "description": "Compute the variance of a one-dimensional ndarray ndarray using a one-pass trial mean algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", From 03ed8d8861c66819cc16c4a8c1ec89da471add71 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Fri, 9 Jan 2026 04:25:16 +0000 Subject: [PATCH 5/5] fix(variancech): fixing a package stats/base/ndarray/variancech --- .../@stdlib/stats/base/ndarray/variancech/package.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json index 44325b3ab286..2e6c5402f665 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/variancech/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/variancech", "version": "0.0.0", - "description": "Compute the variance of a one-dimensional ndarray ndarray using a one-pass trial mean algorithm.", + "description": "Compute the variance of a one-dimensional ndarray using a one-pass trial mean algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors",