npm package: @stdlib/ndarray-find
Description: Return a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.
Author: The Stdlib Authors
Latest version: 0.1.1

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  <summary>
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# find

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

> Return a new [ndarray][@stdlib/ndarray/ctor] containing the first elements which pass a test implemented by a predicate function along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.

<section class="intro">

</section>

<!-- /.intro -->

<section class="installation">

## Installation

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

</section>

<section class="usage">

## Usage

<!-- eslint-disable no-redeclare -->

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

<!-- eslint-enable no-redeclare -->

#### find( x\[, options], predicate\[, thisArg] )

Returns a new [ndarray][@stdlib/ndarray/ctor] containing the first elements which pass a test implemented by a predicate function along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.

<!-- eslint-disable no-invalid-this, max-len -->

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

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

// Perform reduction:
var out = find( x, isEven );
// returns <ndarray>[ 2.0 ]
```

The function accepts the following arguments:

-   **x**: input [ndarray][@stdlib/ndarray/ctor].
-   **options**: function options _(optional)_.
-   **predicate**: predicate function.
-   **thisArg**: predicate function execution context _(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`.
-   **sentinel**: value to return when no element passes the test. May be either a scalar value or a zero-dimensional [ndarray][@stdlib/ndarray/ctor].

By default, the function performs 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' );

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

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

// Perform reduction:
var out = find( x, opts, isEven );
// returns <ndarray>[ [ NaN, 2.0 ], [ NaN, 6.0 ] ]
```

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' );

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

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

// Perform reduction:
var out = find( x, opts, isEven );
// returns <ndarray>[ [ [ NaN, 2.0 ] ], [ [ NaN, 6.0 ] ] ]
```

To specify a custom sentinel value to return when no element passes the test, set the `sentinel` option.

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

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 3.0 ], [ 5.0, 7.0 ] ], [ [ 9.0, 11.0 ], [ 13.0, 15.0 ] ] ] );
// returns <ndarray>

var opts = {
    'sentinel': -999
};

// Perform reduction:
var out = find( x, opts, isEven );
// returns <ndarray>[ -999 ]
```

To set the `predicate` function execution context, provide a `thisArg`.

<!-- eslint-disable no-invalid-this -->

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

function isEven( value ) {
    this.count += 1;
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

var ctx = {
    'count': 0
};

// Perform reduction:
var out = find( x, isEven, ctx );
// returns <ndarray>[ 2.0 ]

var count = ctx.count;
// returns 2
```

#### find.assign( x, out\[, options], predicate\[, thisArg] )

Finds the first elements which pass a test implemented by a predicate function along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor].

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

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

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

// Perform reduction:
var out = find.assign( x, y, isEven );
// returns <ndarray>[ 2.0 ]

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

The function accepts the following arguments:

-   **x**: input [ndarray][@stdlib/ndarray/ctor].
-   **out**: output [ndarray][@stdlib/ndarray/ctor].
-   **options**: function options _(optional)_.
-   **predicate**: predicate function.
-   **thisArg**: predicate function execution context _(optional)_.

The function accepts the following options:

-   **dims**: list of dimensions over which to perform a reduction.
-   **sentinel**: value to return when no element passes the test. May be either a scalar value or a zero-dimensional [ndarray][@stdlib/ndarray/ctor].

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

function isEven( value ) {
    return value % 2.0 === 0.0;
}

// Create an input ndarray:
var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
// returns <ndarray>

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

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

// Perform reduction:
var out = find.assign( x, y, opts, isEven );
// returns <ndarray>[ [ NaN, 2.0 ], [ NaN, 6.0 ] ]

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

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   By default, when no `sentinel` is provided, the function returns a default sentinel value based on the input [ndarray][@stdlib/ndarray/ctor] [data-type][@stdlib/ndarray/dtypes]:

    -   real-valued floating-point data types: `NaN`.
    -   complex-valued floating-point data types: `NaN + NaNj`.
    -   integer data types: maximum value.
    -   boolean data types: `false`.

-   The `predicate` function is provided the following arguments:

    -   **value**: current array element.
    -   **indices**: current array element indices.
    -   **arr**: the input [ndarray][@stdlib/ndarray/ctor].

</section>

<!-- /.notes -->

<section class="examples">

## Examples

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

```javascript
var uniform = require( '@stdlib/random-uniform' );
var isPositive = require( '@stdlib/assert-is-positive-number' ).isPrimitive;
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var find = require( '@stdlib/ndarray-find' );

var x = uniform( [ 2, 4, 5 ], -10.0, 10.0, {
    'dtype': 'float64'
});
console.log( ndarray2array( x ) );

var y = find( x, isPositive );
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 -->


<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-url]: https://github.com/stdlib-js/ndarray-find/tree/deno
[deno-readme]: https://github.com/stdlib-js/ndarray-find/blob/deno/README.md
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[umd-readme]: https://github.com/stdlib-js/ndarray-find/blob/umd/README.md
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/ndarray-find/main/LICENSE

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

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

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</section>

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