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122 changes: 122 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/ssome/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.

-->

# ssome

> Test whether a one-dimensional single-precision floating-point ndarray contains at least `k` truthy elements.

<section class="intro">

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var ssome = require( '@stdlib/blas/ext/base/ndarray/ssome' );
```

#### ssome( arrays )

Tests whether a one-dimensional single-precision floating-point ndarray contains at least `k` truthy elements.

```javascript
var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );

var x = new Float32Vector( [ 0.0, 0.0, 1.0, 2.0 ] );

var k = scalar2ndarray( 2, {
'dtype': 'generic'
});

var v = ssome( [ x, k ] );
// returns true
```

The function has the following parameters:

- **arrays**: array-like object containing the following ndarrays:

- a one-dimensional input ndarray.
- a zero-dimensional ndarray specifying the minimum number of truthy elements.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

- If provided an empty one-dimensional ndarray, the function returns `false`.
- The function explicitly treats `NaN` values as falsy.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var bernoulli = require( '@stdlib/random/bernoulli' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var ssome = require( '@stdlib/blas/ext/base/ndarray/ssome' );

var x = bernoulli( [ 10 ], 0.3, {
'dtype': 'float32'
});
console.log( ndarray2array( x ) );

var k = scalar2ndarray( 3, {
'dtype': 'generic'
});

var v = ssome( [ x, k ] );
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 zeros = require( '@stdlib/ndarray/zeros' );
var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
var floor = require( '@stdlib/math/base/special/floor' );
var pow = require( '@stdlib/math/base/special/pow' );
var format = require( '@stdlib/string/format' );
var pkg = require( './../package.json' ).name;
var ssome = 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 x = zeros( [ len ], options );
var k = scalar2ndarray( floor( len / 2 ), {
'dtype': 'generic'
});
return benchmark;

/**
* Benchmark function.
*
* @private
* @param {Benchmark} b - benchmark instance
*/
function benchmark( b ) {
var out;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
out = ssome( [ x, k ] );
if ( typeof out !== 'boolean' ) {
b.fail( 'should return a boolean' );
}
}
b.toc();
if ( typeof out !== 'boolean' ) {
b.fail( 'should return a boolean' );
}
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();
33 changes: 33 additions & 0 deletions lib/node_modules/@stdlib/blas/ext/base/ndarray/ssome/docs/repl.txt
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{{alias}}( arrays )
Tests whether a one-dimensional single-precision floating-point ndarray
contains at least `k` truthy elements.

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

The function explicitly treats `NaN` values as falsy.

Parameters
----------
arrays: ArrayLikeObject<ndarray>
Array-like object containing the following ndarrays:

- a one-dimensional input ndarray.
- a zero-dimensional ndarray specifying the minimum number of truthy
elements.

Returns
-------
bool: boolean
Boolean indicating whether the input ndarray contains at least `k`
truthy elements.

Examples
--------
> var x = new {{alias:@stdlib/ndarray/vector/float32}}( [ 0.0, 0.0, 1.0, 2.0 ] );
> var k = {{alias:@stdlib/ndarray/from-scalar}}( 2, { 'dtype': 'generic' } );
> {{alias}}( [ x, k ] )
true

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, typedndarray } from '@stdlib/types/ndarray';

/**
* Tests whether a one-dimensional single-precision floating-point ndarray contains at least `k` truthy elements.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a zero-dimensional ndarray specifying the minimum number of truthy elements.
*
* - The function explicitly treats `NaN` values as falsy.
*
* @param arrays - array-like object containing ndarrays
* @returns boolean indicating whether the input ndarray contains at least `k` truthy elements
*
* @example
* var Float32Vector = require( '@stdlib/ndarray/vector/float32' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var x = new Float32Vector( [ 0.0, 0.0, 1.0, 2.0 ] );
*
* var k = scalar2ndarray( 2, {
* 'dtype': 'generic'
* });
*
* var v = ssome( [ x, k ] );
* // returns true
*/
declare function ssome( arrays: [ float32ndarray, typedndarray<number> ] ): boolean;


// EXPORTS //

export = ssome;
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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.
*/

/* eslint-disable space-in-parens */

import zeros = require( '@stdlib/ndarray/zeros' );
import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
import ssome = require( './index' );


// TESTS //

// The function returns a boolean...
{
const x = zeros( [ 10 ], {
'dtype': 'float32'
});
const k = scalar2ndarray( 2, {
'dtype': 'generic'
});

ssome( [ x, k ] ); // $ExpectType boolean
}

// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
{
ssome( '10' ); // $ExpectError
ssome( 10 ); // $ExpectError
ssome( true ); // $ExpectError
ssome( false ); // $ExpectError
ssome( null ); // $ExpectError
ssome( undefined ); // $ExpectError
ssome( [] ); // $ExpectError
ssome( {} ); // $ExpectError
ssome( ( x: number ): number => x ); // $ExpectError
}

// The compiler throws an error if the function is provided an unsupported number of arguments...
{
const x = zeros( [ 10 ], {
'dtype': 'float32'
});
const k = scalar2ndarray( 2, {
'dtype': 'generic'
});

ssome(); // $ExpectError
ssome( [ x, k ], {} ); // $ExpectError
}
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