From e585affbe9276460c966da3648c1eefde67b46c2 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Mon, 5 Jan 2026 17:30:25 +0000 Subject: [PATCH 1/4] feat(stats): add sstdevwd ndarray support --- 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/dstdevwd/README.md | 187 ++++++++++++++ .../ndarray/dstdevwd/benchmark/benchmark.js | 106 ++++++++ .../docs/img/equation_sample_mean.svg | 43 ++++ .../stats/base/ndarray/dstdevwd/docs/repl.txt | 54 +++++ .../ndarray/dstdevwd/docs/types/index.d.ts | 52 ++++ .../base/ndarray/dstdevwd/docs/types/test.ts | 64 +++++ .../base/ndarray/dstdevwd/examples/index.js | 37 +++ .../stats/base/ndarray/dstdevwd/lib/index.js | 55 +++++ .../stats/base/ndarray/dstdevwd/lib/main.js | 69 ++++++ .../stats/base/ndarray/dstdevwd/package.json | 76 ++++++ .../stats/base/ndarray/dstdevwd/test/test.js | 228 ++++++++++++++++++ 11 files changed, 971 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/img/equation_sample_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md new file mode 100644 index 000000000000..5df061d9b69f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md @@ -0,0 +1,187 @@ + + +# dstdevwd + +> Calculate the [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. + +
+ +The population [standard deviation][standard-deviation] of a finite size population of size `N` is given by + + + +```math +\sigma = \sqrt{\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 [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation], the result is biased and yields an **uncorrected sample standard deviation**. To compute a **corrected sample standard deviation** for a sample of size `n`, + + + +```math +s = \sqrt{\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 standard deviation and population standard deviation. 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 dstdevwd = require( '@stdlib/stats/base/ndarray/dstdevwd' ); +``` + +#### dstdevwd( arrays ) + +Computes the [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +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 = dstdevwd( [ x, correction ] ); +// returns ~2.0817 +``` + +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 [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation] 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 [standard deviation][standard-deviation], 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 dstdevwd = require( '@stdlib/stats/base/ndarray/dstdevwd' ); + +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 = dstdevwd( [ x, correction ] ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js new file mode 100644 index 000000000000..4738c734fd11 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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 dstdevwd = 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 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 = dstdevwd( [ 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/dstdevwd/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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/dstdevwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt new file mode 100644 index 000000000000..c4ddcc935882 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Computes the standard deviation of a one-dimensional double-precision + floating-point ndarray. + + 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 standard + deviation 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 standard deviation 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 standard deviation, 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 standard deviation. + + Examples + -------- + // Create input ndarray: + > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var dt = 'float64'; + > 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 standard deviation: + > {{alias}}( [ x, correction ] ) + ~2.0817 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts new file mode 100644 index 000000000000..45a5500669d3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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 { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray. +* +* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment +* @returns standard deviation +* +* @example +* var ndarray = require( '@stdlib/ndarray/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 = dstdevwd( [ x, correction ] ); +* // returns ~2.0817 +*/ +declare function dstdevwd = typedndarray>( arrays: [ float64ndarray, T ] ): number; + + +// EXPORTS // + +export = dstdevwd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/test.ts new file mode 100644 index 000000000000..4c0d15ba6d84 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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 dstdevwd = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const correction = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + dstdevwd( [ x, correction ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dstdevwd( '10' ); // $ExpectError + dstdevwd( 10 ); // $ExpectError + dstdevwd( true ); // $ExpectError + dstdevwd( false ); // $ExpectError + dstdevwd( null ); // $ExpectError + dstdevwd( undefined ); // $ExpectError + dstdevwd( [] ); // $ExpectError + dstdevwd( {} ); // $ExpectError + dstdevwd( ( 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' + }); + + dstdevwd(); // $ExpectError + dstdevwd( [ x, correction ], 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/examples/index.js new file mode 100644 index 000000000000..4d1d59946dae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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 dstdevwd = 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 = dstdevwd( [ x, correction ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js new file mode 100644 index 000000000000..e171e58ac0e6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js @@ -0,0 +1,55 @@ +/** +* @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 standard deviation of a one-dimensional double-precision floating-point ndarray. +* +* @module @stdlib/stats/base/ndarray/dstdevwd +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var dstdevwd = require( '@stdlib/stats/base/ndarray/dstdevwd' ); +* +* var opts = { +* 'dtype': 'float64' +* }; +* +* // Define a one-dimensional input ndarray: +* var xbuf = new Float64Array( [ 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 standard deviation: +* var v = dstdevwd( [ x, correction ] ); +* // returns ~2.0817 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/main.js new file mode 100644 index 000000000000..128b32786112 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/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/dstdevwd' ).ndarray; + + +// MAIN // + +/** +* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray using Welford's 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} standard deviation +* +* @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 = dstdevwd( [ x, correction ] ); +* // returns 2.5 +*/ +function dstdevwd( 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 = dstdevwd; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json new file mode 100644 index 000000000000..a0db43ca1684 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/base/ndarray/dstdevwd", + "version": "0.0.0", + "description": "Compute the standard deviation 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", + "standard deviation", + "variance", + "var", + "deviation", + "dispersion", + "spread", + "sample standard deviation", + "unbiased", + "dstdevwd", + "std", + "ndarray", + "float64", + "double", + "double-precision", + "typed", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/test/test.js new file mode 100644 index 000000000000..c1fa509771c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/test/test.js @@ -0,0 +1,228 @@ +/** +* @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 sqrt = require( '@stdlib/math/base/special/sqrt' ); +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 dstdevwd = 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 dstdevwd, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dstdevwd.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the standard deviation 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 = dstdevwd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = sqrt( 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 = dstdevwd( [ vector( x, x.length, 1, 0 ), correction ] ); + expected = sqrt( 0.5 ); + t.strictEqual( v, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN ] ); + correction = scalar2ndarray( 1.0, opts ); + + v = dstdevwd( [ 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 = dstdevwd( [ 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 = dstdevwd( [ 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 = dstdevwd( [ 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 = dstdevwd( [ vector( x, 4, 2, 0 ), correction ] ); + expected = 2.5; + 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 = dstdevwd( [ vector( x, 4, -2, 6 ), correction ] ); + expected = 2.5; + 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 = dstdevwd( [ vector( x, 4, 2, 1 ), correction ] ); + expected = 2.5; + t.strictEqual( v, expected, 'returns expected value' ); + + t.end(); +}); From a8aec4df15a9f7d949d11b5b87c4768e315062ca Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Mon, 5 Jan 2026 18:47:51 +0000 Subject: [PATCH 2/4] feat(stats): fix dstdevwd ndarray json --- 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 --- --- .../stats/base/ndarray/dstdevwd/package.json | 148 +++++++++--------- 1 file changed, 74 insertions(+), 74 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json index a0db43ca1684..262b68bf82ac 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/package.json @@ -1,76 +1,76 @@ { - "name": "@stdlib/stats/base/ndarray/dstdevwd", - "version": "0.0.0", - "description": "Compute the standard deviation 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", - "standard deviation", - "variance", - "var", - "deviation", - "dispersion", - "spread", - "sample standard deviation", - "unbiased", - "dstdevwd", - "std", - "ndarray", - "float64", - "double", - "double-precision", - "typed", - "float64array" - ], - "__stdlib__": {} + "name": "@stdlib/stats/base/ndarray/dstdevwd", + "version": "0.0.0", + "description": "Compute the standard deviation 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", + "standard deviation", + "variance", + "var", + "deviation", + "dispersion", + "spread", + "sample standard deviation", + "unbiased", + "dstdevwd", + "std", + "ndarray", + "float64", + "double", + "double-precision", + "typed", + "float64array" + ], + "__stdlib__": {} } From 94367bbc0dac6f49259b62f4233f76196eda62b5 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Sat, 10 Jan 2026 06:53:23 +0000 Subject: [PATCH 3/4] chores --- lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md | 2 +- .../@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt | 2 +- .../@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts | 2 +- .../@stdlib/stats/base/ndarray/dstdevwd/lib/index.js | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md index 5df061d9b69f..f7b4bd148a8c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/README.md @@ -100,7 +100,7 @@ var dstdevwd = require( '@stdlib/stats/base/ndarray/dstdevwd' ); #### dstdevwd( arrays ) -Computes the [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray. +Computes the [standard deviation][standard-deviation] of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. ```javascript var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt index c4ddcc935882..09080c77c5a5 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/repl.txt @@ -1,7 +1,7 @@ {{alias}}( arrays ) Computes the standard deviation of a one-dimensional double-precision - floating-point ndarray. + floating-point ndarray using Welford's algorithm. If provided an empty one-dimensional ndarray, the function returns `NaN`. diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts index 45a5500669d3..9a639f2a6397 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/docs/types/index.d.ts @@ -23,7 +23,7 @@ import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; /** -* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray. +* Computes the standard deviation of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. * * @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment * @returns standard deviation diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js index e171e58ac0e6..e528fe82669a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Compute the standard deviation of a one-dimensional double-precision floating-point ndarray. +* Compute the standard deviation of a one-dimensional double-precision floating-point ndarray using Welford's algorithm. * * @module @stdlib/stats/base/ndarray/dstdevwd * From 9a057d7931e245b8c8bb6b7a694b5bd9186154a7 Mon Sep 17 00:00:00 2001 From: DivyanshuVorrtex Date: Mon, 12 Jan 2026 15:24:43 +0000 Subject: [PATCH 4/4] style: add structure to benchmark --- 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: na - 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: 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: na - task: lint_license_headers status: passed --- --- .../stats/base/ndarray/dstdevwd/benchmark/benchmark.js | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js index 4738c734fd11..b79d3ba7d3f9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dstdevwd/benchmark/benchmark.js @@ -58,6 +58,12 @@ function createBenchmark( len ) { return benchmark; + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ function benchmark( b ) { var v; var i;