feat: add stats/base/ndarray/snanstdev

lib/node_modules/@stdlib/stats/base/ndarray/snanstdev/README.md

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+<!--
+
+@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.
+
+-->
+
+# snanstdev
+
+> Compute the standard deviation of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.
+
+<section class="intro">
+
+This package provides an ndarray interface for computing the standard deviation of a one-dimensional 
+single-precision floating-point ndarray while ignoring `NaN` values.
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var snanstdev = require( '@stdlib/stats/base/ndarray/snanstdev' );
+```
+
+#### snanstdev( arrays )
+
+Computes the standard deviation of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ 1.0, 3.0, NaN, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var c = new ndarray( 'generic', [ 1 ], [], [ 0 ], 0, 'row-major' );
+
+var v = snanstdev( [ x, c ] );
+// returns ~1.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing:
+    -   a one-dimensional input ndarray
+    -   a zero-dimensional ndarray specifying a degrees of freedom adjustment
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var snanstdev = require( '@stdlib/stats/base/ndarray/snanstdev' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float32', rand );
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+
+var c = new ndarray( 'generic', [ 1 ], [], [ 0 ], 0, 'row-major' );
+
+var v = snanstdev( [ x, c ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/stats/base/ndarray/snanstdev/benchmark/benchmark.js

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+/**
+* @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 isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+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 snanstdev = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// 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;
+
+	/**
+	* Runs a benchmark.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = snanstdev( [ x, correction ] );
+			if ( isnanf( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+
+		if ( isnanf( 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();

lib/node_modules/@stdlib/stats/base/ndarray/snanstdev/docs/repl.txt

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+
+{{alias}}( arrays )
+    Computes the standard deviation of a one-dimensional single-precision
+    floating-point ndarray, ignoring `NaN` values.
+
+    If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+    If the number of non-NaN elements minus the degrees of freedom adjustment
+    is less than or equal to `0`, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        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
+        non-NaN 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. When computing the corrected sample standard deviation,
+        setting this parameter to `1` is the standard choice (commonly referred
+        to as Bessel's correction).
+
+    Returns
+    -------
+    out: number
+        The standard deviation.
+
+    Examples
+    --------
+    // Create input ndarray:
+    > var xbuf = new {{alias:@stdlib/array/float32}}(
+    ...   [ 1.0, -2.0, NaN, 2.0 ]
+    ... );
+    > var dt = 'float32';
+    > 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
+    --------
+

lib/node_modules/@stdlib/stats/base/ndarray/snanstdev/docs/types/index.d.ts

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+/*
+* @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
+
+/// <reference types="@stdlib/types"/>
+
+import { float32ndarray, ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the standard deviation of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @param arrays - array-like object containing a one-dimensional input ndarray and a zero-dimensional ndarray specifying a degrees of freedom adjustment
+* @returns computed standard deviation
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* // Degrees of freedom adjustment:
+* var c = new ndarray( 'generic', [ 1 ], [], [ 0 ], 0, 'row-major' );
+*
+* var v = snanstdev( [ x, c ] );
+* // returns 1.0
+*/
+declare function snanstdev( arrays: [ float32ndarray, ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = snanstdev;