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137 changes: 137 additions & 0 deletions lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/README.md
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<!--

@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.

-->

# dnanmskmax

> Compute the maximum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var dnanmskmax = require( '@stdlib/stats/base/ndarray/dnanmskmax' );
```

#### dnanmskmax( arrays )

Computes the maximum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.

```javascript
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );

var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var maskbuf = new Uint8Array( [ 0, 0, 0, 0 ] );
var mask = new ndarray( 'uint8', maskbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = dnanmskmax( [ x, mask ] );
// returns 2.0
```

The function has the following parameters:

- **arrays**: array-like object containing a one-dimensional input ndarray and a one-dimensional mask ndarray.

If a `mask` array element is `0`, the corresponding element in the input ndarray is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in the input ndarray is considered invalid/missing and **excluded** from computation.


</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 ndarray2array = require( '@stdlib/ndarray/to-array' );
var dnanmskmax = require( '@stdlib/stats/base/ndarray/dnanmskmax' );

function rand() {
if ( bernoulli( 0.2 ) < 1 ) {
return NaN;
}
return uniform( -50.0, 50.0 );
}

function randMask() {
if ( bernoulli( 0.1 ) < 1 ) {
return 1;
}
return 0;
}

var xbuf = filledarrayBy( 10, 'float64', rand );
var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var maskbuf = filledarrayBy( xbuf.length, 'uint8', randMask );
var mask = new ndarray( 'uint8', maskbuf, [ maskbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( mask ) );

var v = dnanmskmax( [ x, mask ] );
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) 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 ndarray = require( '@stdlib/ndarray/base/ctor' );
var pkg = require( './../package.json' ).name;
var dnanmskmax = require( './../lib' );


// FUNCTIONS //

/**
* Returns a random number.
*
* @private
* @returns {number} random number or `NaN`
*/
function rand() {
if ( bernoulli( 0.2 ) < 1 ) {
return NaN;
}
return uniform( -10.0, 10.0 );
}

/**
* Returns a random mask value.
*
* @private
* @returns {number} 0 or 1
*/
function randMask() {
if ( bernoulli( 0.1 ) < 1 ) {
return 1;
}
return 0;
}

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var mask;
var mbuf;
var xbuf;
var x;

xbuf = filledarrayBy( len, 'float64', rand );
x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );

mbuf = filledarrayBy( len, 'uint8', randMask );
mask = new ndarray( 'uint8', mbuf, [ len ], [ 1 ], 0, 'row-major' );

return benchmark;

function benchmark( b ) {
var v;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = dnanmskmax( [ x, mask ] );
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();
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{{alias}}( arrays )
Computes the maximum value of a double-precision floating-
point ndarray according to a mask, ignoring `NaN` values.

If provided an empty ndarray, the function returns `NaN`.

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing a one-dimensional input ndarray and a
one-dimensional mask ndarray.

Returns
-------
out: number
Maximum value.

Examples
--------
> var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, NaN, 2.0 ] );
> var dt = 'float64';
> var sh = [ xbuf.length ];
> var sx = [ 1 ];
> var ox = 0;
> var ord = 'row-major';
> var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
> var mbuf = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0 ] );
> var mask = new {{alias:@stdlib/ndarray/ctor}}( 'uint8', mbuf, sh, sx, ox, ord );
> {{alias}}( [ x, mask ] )
2.0

See Also
--------

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/*
* @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

/// <reference types="@stdlib/types"/>

import { float64ndarray, uint8ndarray } from '@stdlib/types/ndarray';

/**
* Computes the maximum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.
*
* @param arrays - array-like object containing an input ndarray and a mask ndarray
* @returns maximum value
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var Uint8Array = require( '@stdlib/array/uint8' );
* var ndarray = require( '@stdlib/ndarray/base/ctor' );
*
* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
*
* var mbuf = new Uint8Array( [ 0, 0, 0, 0 ] );
* var mask = new ndarray( 'uint8', mbuf, [ 4 ], [ 1 ], 0, 'row-major' );
*
* var v = dnanmskmax( [ x, mask ] );
* // returns 2.0
*/
declare function dnanmskmax( arrays: [ float64ndarray, uint8ndarray ] ): number;


// EXPORTS //

export = dnanmskmax;
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