diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/README.md b/lib/node_modules/@stdlib/stats/array/stdevpn/README.md
new file mode 100644
index 000000000000..441dd31494d7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/README.md
@@ -0,0 +1,183 @@
+
+
+# stdevpn
+
+> Calculate the [standard deviation][standard-deviation] of an array using a two-pass 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 stdevpn = require( '@stdlib/stats/array/stdevpn' );
+```
+
+#### stdevpn( x\[, correction] )
+
+Computes the [standard deviation][standard-deviation] of an array using a two-pass algorithm.
+
+```javascript
+var x = [ 1.0, -2.0, 2.0 ];
+
+var v = stdevpn( 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, 2.0 ];
+
+var v = stdevpn( 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), both functions return `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]).
+
+
+
+
+
+
+
+## Examples
+
+
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var stdevpn = require( '@stdlib/stats/array/stdevpn' );
+
+var x = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
+console.log( x );
+
+var v = stdevpn( 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/stdevpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/array/stdevpn/benchmark/benchmark.js
new file mode 100644
index 000000000000..c4a272463194
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/benchmark/benchmark.js
@@ -0,0 +1,96 @@
+/**
+* @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/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var stdevpn = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+ var x = uniform( len, -10, 10, options );
+ return benchmark;
+
+ function benchmark( b ) {
+ var v;
+ var i;
+
+ b.tic();
+ for ( i = 0; i < b.iterations; i++ ) {
+ v = stdevpn( 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/stdevpn/docs/img/equation_corrected_sample_standard_deviation.svg b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_corrected_sample_standard_deviation.svg
new file mode 100644
index 000000000000..6af85c9d5732
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_corrected_sample_standard_deviation.svg
@@ -0,0 +1,73 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_mean.svg b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_mean.svg
new file mode 100644
index 000000000000..4bbdf0d2a56f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_mean.svg
@@ -0,0 +1,42 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_standard_deviation.svg b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_standard_deviation.svg
new file mode 100644
index 000000000000..ad431efeff2a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_population_standard_deviation.svg
@@ -0,0 +1,66 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_sample_mean.svg b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_sample_mean.svg
new file mode 100644
index 000000000000..aea7a5f6687a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/img/equation_sample_mean.svg
@@ -0,0 +1,43 @@
+
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/repl.txt b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/repl.txt
new file mode 100644
index 000000000000..b183d4b8632d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/repl.txt
@@ -0,0 +1,38 @@
+
+{{alias}}( x[, correction] )
+ Computes the standard deviation of an array using a two-pass 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, 2.0 ];
+ > {{alias}}( x, 1.0 )
+ ~2.0817
+
+ See Also
+ --------
+
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/types/index.d.ts
new file mode 100644
index 000000000000..d4a00423ecde
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/types/index.d.ts
@@ -0,0 +1,48 @@
+/*
+* @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 using a two-pass algorithm.
+*
+* @param x - input array
+* @param correction - degrees of freedom adjustment (default: 1.0)
+* @returns standard deviation
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = stdevpn( x, 1.0 );
+* // returns ~2.0817
+*/
+declare function stdevpn( x: InputArray, correction?: number ): number;
+
+
+// EXPORTS //
+
+export = stdevpn;
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/docs/types/test.ts b/lib/node_modules/@stdlib/stats/array/stdevpn/docs/types/test.ts
new file mode 100644
index 000000000000..6b3bb4aa488d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/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 stdevpn = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+ const x = new Float64Array( 10 );
+
+ stdevpn( x ); // $ExpectType number
+ stdevpn( new AccessorArray( x ) ); // $ExpectType number
+
+ stdevpn( x, 1.0 ); // $ExpectType number
+ stdevpn( 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...
+{
+ stdevpn( 10 ); // $ExpectError
+ stdevpn( '10' ); // $ExpectError
+ stdevpn( true ); // $ExpectError
+ stdevpn( false ); // $ExpectError
+ stdevpn( null ); // $ExpectError
+ stdevpn( undefined ); // $ExpectError
+ stdevpn( {} ); // $ExpectError
+ stdevpn( ( x: number ): number => x ); // $ExpectError
+
+ stdevpn( 10, 1.0 ); // $ExpectError
+ stdevpn( '10', 1.0 ); // $ExpectError
+ stdevpn( true, 1.0 ); // $ExpectError
+ stdevpn( false, 1.0 ); // $ExpectError
+ stdevpn( null, 1.0 ); // $ExpectError
+ stdevpn( undefined, 1.0 ); // $ExpectError
+ stdevpn( {}, 1.0 ); // $ExpectError
+ stdevpn( ( 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 );
+
+ stdevpn( x, '10' ); // $ExpectError
+ stdevpn( x, true ); // $ExpectError
+ stdevpn( x, false ); // $ExpectError
+ stdevpn( x, null ); // $ExpectError
+ stdevpn( x, [] ); // $ExpectError
+ stdevpn( x, {} ); // $ExpectError
+ stdevpn( 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 );
+
+ stdevpn(); // $ExpectError
+ stdevpn( x, 1.0, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/examples/index.js b/lib/node_modules/@stdlib/stats/array/stdevpn/examples/index.js
new file mode 100644
index 000000000000..523abd1743ac
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/examples/index.js
@@ -0,0 +1,30 @@
+/**
+* @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 discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var stdevpn = require( './../lib' );
+
+var x = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
+console.log( x );
+
+var v = stdevpn( x );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/lib/index.js b/lib/node_modules/@stdlib/stats/array/stdevpn/lib/index.js
new file mode 100644
index 000000000000..6cff835d3265
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/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 using a two-pass algorithm.
+*
+* @module @stdlib/stats/array/stdevpn
+*
+* @example
+* var stdevpn = require( '@stdlib/stats/array/stdevpn' );
+*
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = stdevpn( 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/stdevpn/lib/main.js b/lib/node_modules/@stdlib/stats/array/stdevpn/lib/main.js
new file mode 100644
index 000000000000..fa109395811b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/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/stdevpn' ).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 using a two-pass algorithm.
+*
+* @param {NumericArray} x - input array
+* @param {number} correction - 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, 2.0 ];
+*
+* var v = stdevpn( x, 1.0 );
+* // returns ~2.0817
+*/
+function stdevpn( 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 = stdevpn;
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/package.json b/lib/node_modules/@stdlib/stats/array/stdevpn/package.json
new file mode 100644
index 000000000000..912da870accd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/package.json
@@ -0,0 +1,71 @@
+{
+ "name": "@stdlib/stats/array/stdevpn",
+ "version": "0.0.0",
+ "description": "Calculate the standard deviation of an array using a two-pass algorithm.",
+ "license": "Apache-2.0",
+ "author": {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ },
+ "contributors": [
+ {
+ "name": "The Stdlib Authors",
+ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+ }
+ ],
+ "main": "./lib",
+ "directories": {
+ "benchmark": "./benchmark",
+ "doc": "./docs",
+ "example": "./examples",
+ "lib": "./lib",
+ "test": "./test"
+ },
+ "types": "./docs/types",
+ "scripts": {},
+ "homepage": "https://github.com/stdlib-js/stdlib",
+ "repository": {
+ "type": "git",
+ "url": "git://github.com/stdlib-js/stdlib.git"
+ },
+ "bugs": {
+ "url": "https://github.com/stdlib-js/stdlib/issues"
+ },
+ "dependencies": {},
+ "devDependencies": {},
+ "engines": {
+ "node": ">=0.10.0",
+ "npm": ">2.7.0"
+ },
+ "os": [
+ "aix",
+ "darwin",
+ "freebsd",
+ "linux",
+ "macos",
+ "openbsd",
+ "sunos",
+ "win32",
+ "windows"
+ ],
+ "keywords": [
+ "stdlib",
+ "stdmath",
+ "statistics",
+ "stats",
+ "mathematics",
+ "math",
+ "standard deviation",
+ "variance",
+ "var",
+ "deviation",
+ "dispersion",
+ "spread",
+ "sample standard deviation",
+ "unbiased",
+ "stdev",
+ "std",
+ "array"
+ ],
+ "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/array/stdevpn/test/test.js b/lib/node_modules/@stdlib/stats/array/stdevpn/test/test.js
new file mode 100644
index 000000000000..184d7474f236
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/array/stdevpn/test/test.js
@@ -0,0 +1,350 @@
+/**
+* @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 stdevpn = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+ t.ok( true, __filename );
+ t.strictEqual( typeof stdevpn, 'function', 'main export is a function' );
+ t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+ t.strictEqual( stdevpn.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() {
+ stdevpn( 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() {
+ stdevpn( 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() {
+ stdevpn( 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() {
+ stdevpn( 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() {
+ stdevpn( [ 1, 2, 3 ], value );
+ };
+ }
+});
+
+tape( 'the function calculates the population standard deviation of an array', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( x, 0.0 );
+ t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( x, 0.0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = stdevpn( x, 0.0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the population standard deviation of an array (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( toAccessorArray( x ), 0.0 );
+ t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( toAccessorArray( x ), 0.0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = stdevpn( toAccessorArray( x ), 0.0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the population standard deviation of an array (array-like object)', function test( t ) {
+ var x;
+ var v;
+
+ x = {
+ 'length': 6,
+ '0': 1.0,
+ '1': -2.0,
+ '2': -4.0,
+ '3': 5.0,
+ '4': 0.0,
+ '5': 3.0
+ };
+ v = stdevpn( x, 0.0 );
+ t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample standard deviation of an array (default)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( x );
+ t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( x );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = stdevpn( x );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample standard deviation of an array (default, accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( toAccessorArray( x ) );
+ t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( toAccessorArray( x ) );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, NaN ];
+ v = stdevpn( toAccessorArray( x ) );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample standard deviation of an array', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( x, 1.0 );
+ t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( x, 1.0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = stdevpn( x, 1.0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function calculates the sample standard deviation of an array (accessors)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = stdevpn( toAccessorArray( x ), 1.0 );
+ t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = stdevpn( toAccessorArray( x ), 1.0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, NaN ];
+ v = stdevpn( 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 = stdevpn( [] );
+ 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 = stdevpn( 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 = stdevpn( [ 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 = stdevpn( 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 = stdevpn( x, x.length );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = stdevpn( 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 = stdevpn( x, x.length );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ v = stdevpn( x, x.length+1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});