npm package: @stdlib/ndarray-some
Description: Test whether at least `n` elements along one or more ndarray dimensions are truthy.
Author: The Stdlib Authors
Latest version: 0.1.1

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<details>
  <summary>
    About stdlib...
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  <p>We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.</p>
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</details>

# some

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Test whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/ndarray-some
```

</section>

<section class="usage">

## Usage

```javascript
var some = require( '@stdlib/ndarray-some' );
```

#### some( x, n\[, options] )

Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.

```javascript
var array = require( '@stdlib/ndarray-array' );

// Create an input ndarray:
var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>

// Perform reduction:
var out = some( x, 3 );
// returns <ndarray>[ true ]
```

The function accepts the following arguments:

-   **x**: input [`ndarray`][@stdlib/ndarray/ctor].
-   **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
-   **options**: function options (_optional_).

The function accepts the following options:

-   **dims**: list of dimensions over which to perform a reduction.
-   **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [`ndarray`][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.

By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.

```javascript
var array = require( '@stdlib/ndarray-array' );

// Create an input ndarray:
var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>

var opts = {
    'dims': [ 0, 1 ]
};

// Perform reduction:
var out = some( x, 2, opts );
// returns <ndarray>[ true, true ]
```

By default, the function returns an [`ndarray`][@stdlib/ndarray/ctor] having a shape matching only the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor] (i.e., the reduced dimensions are dropped). To include the reduced dimensions as singleton dimensions in the output [`ndarray`][@stdlib/ndarray/ctor], set the `keepdims` option to `true`.

```javascript
var array = require( '@stdlib/ndarray-array' );

// Create an input ndarray:
var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>

var opts = {
    'dims': [ 0, 1 ],
    'keepdims': true
};

// Perform reduction:
var out = some( x, 2, opts );
// returns <ndarray>[ [ [ true, true ] ] ]
```

#### some.assign( x, n, out\[, options] )

Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy and assigns the results to an output [`ndarray`][@stdlib/ndarray/ctor].

```javascript
var array = require( '@stdlib/ndarray-array' );
var empty = require( '@stdlib/ndarray-empty' );

// Create an input ndarray:
var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>

// Create an output ndarray:
var y = empty( [], {
    'dtype': 'bool'
});

// Perform reduction:
var out = some.assign( x, 3, y );
// returns <ndarray>[ true ]

var bool = ( out === y );
// returns true
```

The function accepts the following arguments:

-   **x**: input [`ndarray`][@stdlib/ndarray/ctor].
-   **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
-   **out**: output [`ndarray`][@stdlib/ndarray/ctor]. The output [`ndarray`][@stdlib/ndarray/ctor] must have a shape matching the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor].
-   **options**: function options (_optional_).

The function accepts the following `options`:

-   **dims**: list of dimensions over which to perform a reduction.

By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.

```javascript
var array = require( '@stdlib/ndarray-array' );
var empty = require( '@stdlib/ndarray-empty' );

// Create an input ndarray:
var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
// returns <ndarray>

// Create an output ndarray:
var y = empty( [ 2 ], {
    'dtype': 'bool'
});

var opts = {
    'dims': [ 0, 1 ]
};

// Perform reduction:
var out = some.assign( x, 2, y, opts );
// returns <ndarray>[ true, true ]

var bool = ( out === y );
// returns true
```

</section>

<!-- /.usage -->

<section class="notes">

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var fillBy = require( '@stdlib/ndarray-fill-by' );
var zeros = require( '@stdlib/ndarray-zeros' );
var some = require( '@stdlib/ndarray-some' );

var x = zeros( [ 2, 4, 5 ], {
    'dtype': 'float64'
});
x = fillBy( x, discreteUniform( 0, 10 ) );
console.log( ndarray2array( x ) );

var n = scalar2ndarray( 4, {
    'dtype': 'int8'
});
var y = some( x, n );
console.log( y.get() );
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</section>

<!-- /.related -->

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<section class="main-repo" >

* * *

## Notice

This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

#### Community

[![Chat][chat-image]][chat-url]

---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

</section>

<!-- /.stdlib -->

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[umd]: https://github.com/umdjs/umd
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[deno-readme]: https://github.com/stdlib-js/ndarray-some/blob/deno/README.md
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/ndarray-some/main/LICENSE

[@stdlib/ndarray/ctor]: https://www.npmjs.com/package/@stdlib/ndarray-ctor

[@stdlib/ndarray/dtypes]: https://www.npmjs.com/package/@stdlib/ndarray-dtypes

[@stdlib/ndarray/base/broadcast-shapes]: https://www.npmjs.com/package/@stdlib/ndarray-base-broadcast-shapes

</section>

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