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126 changes: 126 additions & 0 deletions 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 -->
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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;

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();
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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
--------

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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;
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