From 13e8d7db2d068103654021b4d14d7c9370f2f09d Mon Sep 17 00:00:00 2001 From: gururaj1512 Date: Mon, 14 Jul 2025 10:23:09 +0000 Subject: [PATCH 01/11] feat: add `stats/array/nanstdevch` --- 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 --- --- .../@stdlib/stats/array/nanstdevch/README.md | 191 ++++++++++ .../array/nanstdevch/benchmark/benchmark.js | 104 ++++++ ...on_corrected_sample_standard_deviation.svg | 73 ++++ .../docs/img/equation_population_mean.svg | 42 +++ ...equation_population_standard_deviation.svg | 66 ++++ .../docs/img/equation_sample_mean.svg | 43 +++ .../stats/array/nanstdevch/docs/repl.txt | 39 ++ .../array/nanstdevch/docs/types/index.d.ts | 52 +++ .../stats/array/nanstdevch/docs/types/test.ts | 76 ++++ .../stats/array/nanstdevch/examples/index.js | 37 ++ .../stats/array/nanstdevch/lib/index.js | 42 +++ .../stats/array/nanstdevch/lib/main.js | 81 ++++ .../stats/array/nanstdevch/package.json | 71 ++++ .../stats/array/nanstdevch/test/test.js | 351 ++++++++++++++++++ 14 files changed, 1268 insertions(+) create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/README.md create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_corrected_sample_standard_deviation.svg create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_standard_deviation.svg create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_sample_mean.svg create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/examples/index.js create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/lib/index.js create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/lib/main.js create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/package.json create mode 100644 lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md new file mode 100644 index 000000000000..1fddbfe341db --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -0,0 +1,191 @@ + + +# nanstdevch + +> Calculate the [standard deviation][standard-deviation] of an array ignoring `NaN` values and using a one-pass trial mean 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 nanstdevch = require( '@stdlib/stats/array/nanstdevch' ); +``` + +#### nanstdevch( x\[, correction] ) + +Computes the [standard deviation][standard-deviation] of an array ignoring `NaN` values and using a one-pass trial mean algorithm. + +```javascript +var x = [ 1.0, -2.0, NaN, 2.0 ]; + +var v = nanstdevch( x ); +// returns ~2.0817 +``` + +The function has the following parameters: + +- **x**: input array. +- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `N` corresponds to the number of array elements 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 unbiased 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). Default: `1.0`. + +By default, the function computes the sample [standard deviation][standard-deviation]. To adjust the degrees of freedom when computing the [standard deviation][standard-deviation], provide a `correction` argument. + +```javascript +var x = [ 1.0, -2.0, NaN, 2.0 ]; + +var v = nanstdevch( x, 0.0 ); +// returns ~1.6997 +``` + +
+ + + +
+ +## Notes + +- If provided an empty array, the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). +- The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var nanstdevch = require( '@stdlib/stats/array/nanstdevch' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'generic', rand ); +console.log( x ); + +var v = nanstdevch( x ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js new file mode 100644 index 000000000000..d8f4ea2f6288 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var pkg = require( './../package.json' ).name; +var nanstdevch = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = filledarrayBy( len, 'generic', rand ); + return benchmark; + + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = nanstdevch( x, 1.0 ); + 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( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_corrected_sample_standard_deviation.svg b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_corrected_sample_standard_deviation.svg new file mode 100644 index 000000000000..6af85c9d5732 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_corrected_sample_standard_deviation.svg @@ -0,0 +1,73 @@ + +s equals StartRoot StartFraction 1 Over n minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_mean.svg b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_mean.svg new file mode 100644 index 000000000000..4bbdf0d2a56f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_mean.svg @@ -0,0 +1,42 @@ + +mu equals StartFraction 1 Over upper N EndFraction sigma-summation Underscript i equals 0 Overscript upper N minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_standard_deviation.svg b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_standard_deviation.svg new file mode 100644 index 000000000000..ad431efeff2a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_population_standard_deviation.svg @@ -0,0 +1,66 @@ + +sigma equals StartRoot StartFraction 1 Over upper N EndFraction sigma-summation Underscript i equals 0 Overscript upper N minus 1 Endscripts left-parenthesis x Subscript i Baseline minus mu right-parenthesis squared EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/img/equation_sample_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/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/array/nanstdevch/docs/repl.txt b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt new file mode 100644 index 000000000000..ce85db082d6b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt @@ -0,0 +1,39 @@ + +{{alias}}( x[, correction] ) + Computes the standard deviation of an array ignoring `NaN` values and using + a one-pass trial mean algorithm. + + If provided an empty array, the function returns `NaN`. + + Parameters + ---------- + x: Array|TypedArray + Input array. + + correction: number (optional) + Degrees of freedom adjustment. Setting this parameter to a value other + than `0` has the effect of adjusting the divisor during the calculation + of the standard deviation according to `N-c` where `N` corresponds to + the number of array elements 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 unbiased 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). Default: `1.0`. + + Returns + ------- + out: number + The standard deviation. + + Examples + -------- + > var x = [ 1.0, -2.0, NaN, 2.0 ]; + > {{alias}}( x, 1.0 ) + ~2.0817 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts new file mode 100644 index 000000000000..252cb33a0f26 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Computes the standard deviation of an array ignoring `NaN` values and using a one-pass trial mean algorithm. +* +* ## Notes +* +* - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). +* +* @param x - input array +* @param correction - degrees of freedom adjustment +* @returns standard deviation +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nanstdevch( x, 1.0 ); +* // returns ~2.0817 +*/ +declare function nanstdevch( x: InputArray, correction?: number ): number; + + +// EXPORTS // + +export = nanstdevch; diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/test.ts b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/test.ts new file mode 100644 index 000000000000..72c1ad0d60c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/test.ts @@ -0,0 +1,76 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 AccessorArray = require( '@stdlib/array/base/accessor' ); +import nanstdevch = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + nanstdevch( x ); // $ExpectType number + nanstdevch( new AccessorArray( x ) ); // $ExpectType number + + nanstdevch( x, 1.0 ); // $ExpectType number + nanstdevch( new AccessorArray( x ), 1.0 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a numeric array... +{ + nanstdevch( 10 ); // $ExpectError + nanstdevch( '10' ); // $ExpectError + nanstdevch( true ); // $ExpectError + nanstdevch( false ); // $ExpectError + nanstdevch( null ); // $ExpectError + nanstdevch( undefined ); // $ExpectError + nanstdevch( {} ); // $ExpectError + nanstdevch( ( x: number ): number => x ); // $ExpectError + + nanstdevch( 10, 1.0 ); // $ExpectError + nanstdevch( '10', 1.0 ); // $ExpectError + nanstdevch( true, 1.0 ); // $ExpectError + nanstdevch( false, 1.0 ); // $ExpectError + nanstdevch( null, 1.0 ); // $ExpectError + nanstdevch( undefined, 1.0 ); // $ExpectError + nanstdevch( {}, 1.0 ); // $ExpectError + nanstdevch( ( x: number ): number => x, 1.0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + nanstdevch( x, '10' ); // $ExpectError + nanstdevch( x, true ); // $ExpectError + nanstdevch( x, false ); // $ExpectError + nanstdevch( x, null ); // $ExpectError + nanstdevch( x, [] ); // $ExpectError + nanstdevch( x, {} ); // $ExpectError + nanstdevch( x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + nanstdevch(); // $ExpectError + nanstdevch( x, 1.0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/examples/index.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/examples/index.js new file mode 100644 index 000000000000..8bc5bec95fd2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var nanstdevch = require( './../lib' ); + +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); +} + +var x = filledarrayBy( 10, 'generic', rand ); +console.log( x ); + +var v = nanstdevch( x ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/index.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/index.js new file mode 100644 index 000000000000..f6b54d7cf490 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 an array ignoring `NaN` values and using a one-pass trial mean algorithm. +* +* @module @stdlib/stats/array/nanstdevch +* +* @example +* var nanstdevch = require( '@stdlib/stats/array/nanstdevch' ); +* +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nanstdevch( x, 1.0 ); +* // returns ~2.0817 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/main.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/main.js new file mode 100644 index 000000000000..65a57183ea13 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 isCollection = require( '@stdlib/assert/is-collection' ); +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var dtypes = require( '@stdlib/array/dtypes' ); +var dtype = require( '@stdlib/array/dtype' ); +var contains = require( '@stdlib/array/base/assert/contains' ); +var join = require( '@stdlib/array/base/join' ); +var strided = require( '@stdlib/stats/base/nanstdevch' ).ndarray; +var format = require( '@stdlib/string/format' ); + + +// VARIABLES // + +var IDTYPES = dtypes( 'real_and_generic' ); +var GENERIC_DTYPE = 'generic'; + + +// MAIN // + +/** +* Computes the standard deviation of an array ignoring `NaN` values and using a one-pass trial mean algorithm. +* +* @param {NumericArray} x - input array +* @param {number} [correction=1.0] - degrees of freedom adjustment +* @throws {TypeError} first argument must have a supported data type +* @throws {TypeError} first argument must be an array-like object +* @throws {TypeError} second argument must be an number +* @returns {number} standard deviation +* +* @example +* var x = [ 1.0, -2.0, NaN, 2.0 ]; +* +* var v = nanstdevch( x, 1.0 ); +* // returns ~2.0817 +*/ +function nanstdevch( x ) { + var correction; + var dt; + if ( !isCollection( x ) ) { + throw new TypeError( format( 'invalid argument. First argument must be an array-like object. Value: `%s`.', x ) ); + } + dt = dtype( x ) || GENERIC_DTYPE; + if ( !contains( IDTYPES, dt ) ) { + throw new TypeError( format( 'invalid argument. First argument must have one of the following data types: "%s". Data type: `%s`.', join( IDTYPES, '", "' ), dt ) ); + } + if ( arguments.length > 1 ) { + correction = arguments[ 1 ]; + if ( !isNumber( correction ) ) { + throw new TypeError( format( 'invalid argument. Second argument must be a number. Value: `%s`.', correction ) ); + } + } else { + correction = 1.0; + } + return strided( x.length, correction, x, 1, 0 ); +} + + +// EXPORTS // + +module.exports = nanstdevch; diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json new file mode 100644 index 000000000000..5d214e285d60 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/array/nanstdevch", + "version": "0.0.0", + "description": "Calculate the standard deviation of an array ignoring `NaN` values and using a one-pass trial mean 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", + "stdev", + "std", + "array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js new file mode 100644 index 000000000000..e5371a0ead48 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js @@ -0,0 +1,351 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* 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 toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var BooleanArray = require( '@stdlib/array/bool' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var nanstdevch = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nanstdevch, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( nanstdevch.length, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an array-like object', 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() { + nanstdevch( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an array-like object (correction)', 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() { + nanstdevch( value, 1.0 ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which has an unsupported data type', function test( t ) { + var values; + var i; + + values = [ + new BooleanArray( 4 ), + new Complex128Array( 4 ) + ]; + 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() { + nanstdevch( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which has an unsupported data type (correction)', function test( t ) { + var values; + var i; + + values = [ + new BooleanArray( 4 ), + new Complex128Array( 4 ) + ]; + 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() { + nanstdevch( value, 1.0 ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not a number', function test( t ) { + var values; + var i; + + values = [ + '5', + 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() { + nanstdevch( [ 1, 2, 3 ], value ); + }; + } +}); + +tape( 'the function calculates the population standard deviation of an array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( x, 0.0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( x, 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = nanstdevch( x, 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the population standard deviation of an array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( toAccessorArray( x ), 0.0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( toAccessorArray( x ), 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = nanstdevch( toAccessorArray( x ), 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the population standard deviation of an array (ignoring `NaN` values) (array-like object)', function test( t ) { + var x; + var v; + + x = { + 'length': 7, + '0': 1.0, + '1': -2.0, + '2': -4.0, + '3': 5.0, + '4': NaN, + '5': 0.0, + '6': 3.0 + }; + v = nanstdevch( x, 0.0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample standard deviation of an array (ignoring `NaN` values) (default)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( x ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( x ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = nanstdevch( x ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample standard deviation of an array (ignoring `NaN` values) (default, accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( toAccessorArray( x ) ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( toAccessorArray( x ) ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = nanstdevch( toAccessorArray( x ) ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample standard deviation of an array (ignoring `NaN` values)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( x, 1.0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( x, 1.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = nanstdevch( x, 1.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample standard deviation of an array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + v = nanstdevch( toAccessorArray( x ), 1.0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = nanstdevch( toAccessorArray( x ), 1.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + v = nanstdevch( toAccessorArray( x ), 1.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty array, the function returns `NaN`', function test( t ) { + var v = nanstdevch( [] ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an empty array, the function returns `NaN` (accessors)', function test( t ) { + var v = nanstdevch( toAccessorArray( [] ) ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an array containing a single element, the function returns `0` when computing the population standard deviation', function test( t ) { + var v = nanstdevch( [ 1.0 ], 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an array containing a single element, the function returns `0` when computing the population standard deviation (accessors)', function test( t ) { + var v = nanstdevch( toAccessorArray( [ 1.0 ] ), 0.0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `correction` parameter which is greater than or equal to the input array length, the function returns `NaN`', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; + + v = nanstdevch( x, x.length ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = nanstdevch( x, x.length+1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `correction` parameter which is greater than or equal to the input array length, the function returns `NaN` (accessors)', function test( t ) { + var x; + var v; + + x = toAccessorArray( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); + + v = nanstdevch( x, x.length ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = nanstdevch( x, x.length+1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); From 9c405c4b29c1b0394beea08376b43c0fdcf83b83 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:03:02 -0700 Subject: [PATCH 02/11] docs: update description Signed-off-by: Athan --- .../@stdlib/stats/array/nanstdevch/docs/types/index.d.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts index 252cb33a0f26..804aac19f184 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts @@ -35,7 +35,7 @@ type InputArray = NumericArray | Collection | AccessorArrayLike; * - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). * * @param x - input array -* @param correction - degrees of freedom adjustment +* @param correction - degrees of freedom adjustment (default: 1.0) * @returns standard deviation * * @example From 9553c8d4865fe2c6da4e6f0dff417dc7141bdb6a Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:07:19 -0700 Subject: [PATCH 03/11] docs: update note Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md index 1fddbfe341db..558cc4cf82aa 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -132,7 +132,7 @@ var v = nanstdevch( x, 0.0 ); ## Notes - If provided an empty array, the function returns `NaN`. -- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), the function returns `NaN`. +- If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), the function returns `NaN`. - The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). From 1095724beed4d8f7f321bbf664147b6b719103ce Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:08:44 -0700 Subject: [PATCH 04/11] docs: fix description Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md index 558cc4cf82aa..6c1a146725f5 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -112,7 +112,7 @@ var v = nanstdevch( x ); The function has the following parameters: - **x**: input array. -- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `N` corresponds to the number of array elements 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 unbiased 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). Default: `1.0`. +- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `N` corresponds to the number of non-`NaN` array elements 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 unbiased 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). Default: `1.0`. By default, the function computes the sample [standard deviation][standard-deviation]. To adjust the degrees of freedom when computing the [standard deviation][standard-deviation], provide a `correction` argument. From 01c7371faa23e1271d078b78248d49fa2f37e1c9 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:08:54 -0700 Subject: [PATCH 05/11] docs: fix description Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md index 6c1a146725f5..4f5cfa321db4 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -132,7 +132,7 @@ var v = nanstdevch( x, 0.0 ); ## Notes - If provided an empty array, the function returns `NaN`. -- If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of non-`NaN` indexed elements), the function returns `NaN`. - The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). From b4951054545dd28325de06d3f6e7937d221c33c9 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:09:55 -0700 Subject: [PATCH 06/11] docs: fix description Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt index ce85db082d6b..b89c538dbc64 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/repl.txt @@ -14,7 +14,7 @@ Degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `N` corresponds to - the number of array elements and `c` corresponds to the provided + the number of non-NaN array elements 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 From ce0f12a78dd977f05b84dacbd58b5390234ed183 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:11:33 -0700 Subject: [PATCH 07/11] docs: update description Signed-off-by: Athan --- .../@stdlib/stats/array/nanstdevch/docs/types/index.d.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts index 804aac19f184..2e413db8883e 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts @@ -32,7 +32,7 @@ type InputArray = NumericArray | Collection | AccessorArrayLike; * * ## Notes * -* - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). +* - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `N` corresponds to the number of non-`NaN` elements and `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). * * @param x - input array * @param correction - degrees of freedom adjustment (default: 1.0) From 2532e50c4d678e44a0fd7e00acffd8da263b5bef Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:12:29 -0700 Subject: [PATCH 08/11] docs: update note Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md index 4f5cfa321db4..db9fcbfd3e03 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -132,7 +132,7 @@ var v = nanstdevch( x, 0.0 ); ## Notes - If provided an empty array, the function returns `NaN`. -- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of non-`NaN` indexed elements), the function returns `NaN`. +- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of non-`NaN` array elements), the function returns `NaN`. - The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). From b0ca3876c8a1d2f70d3ebd550e7817915bab3e6f Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:13:28 -0700 Subject: [PATCH 09/11] test: update descriptions Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js b/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js index e5371a0ead48..e8120e810a49 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/test/test.js @@ -320,7 +320,7 @@ tape( 'if provided an array containing a single element, the function returns `0 t.end(); }); -tape( 'if provided a `correction` parameter which is greater than or equal to the input array length, the function returns `NaN`', function test( t ) { +tape( 'if provided a `correction` parameter yielding a correction term less than or equal to `0`, the function returns `NaN`', function test( t ) { var x; var v; @@ -335,7 +335,7 @@ tape( 'if provided a `correction` parameter which is greater than or equal to th t.end(); }); -tape( 'if provided a `correction` parameter which is greater than or equal to the input array length, the function returns `NaN` (accessors)', function test( t ) { +tape( 'if provided a `correction` parameter yielding a correction term less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) { var x; var v; From 98d9c2b8e396e6335896343701809c84a66fe8a0 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:30:51 -0700 Subject: [PATCH 10/11] docs: fix note Signed-off-by: Athan --- lib/node_modules/@stdlib/stats/array/nanstdevch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md index db9fcbfd3e03..64e8b9945e9e 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/README.md @@ -134,7 +134,7 @@ var v = nanstdevch( x, 0.0 ); - If provided an empty array, the function returns `NaN`. - If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of non-`NaN` array elements), the function returns `NaN`. - The function supports array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). -- The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). +- The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the standard deviation is invariant with respect to changes in the location parameter, the underlying algorithm uses the first array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value). From bfbc845ada42ce3022be4a1d24d32d6e20512ad3 Mon Sep 17 00:00:00 2001 From: Athan Date: Tue, 15 Jul 2025 16:32:20 -0700 Subject: [PATCH 11/11] docs: update note Signed-off-by: Athan --- .../@stdlib/stats/array/nanstdevch/docs/types/index.d.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts index 2e413db8883e..f05bf2e57370 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/docs/types/index.d.ts @@ -32,7 +32,7 @@ type InputArray = NumericArray | Collection | AccessorArrayLike; * * ## Notes * -* - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `N` corresponds to the number of non-`NaN` elements and `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). +* - Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `N` corresponds to the number of non-`NaN` array elements and `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction 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 the correction 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). * * @param x - input array * @param correction - degrees of freedom adjustment (default: 1.0)