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find

Return the first element in an ndarray which passes a test implemented by a predicate function.

Installation

npm install @stdlib/ndarray-base-find

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

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

find( arrays, predicate[, thisArg] )

Returns the first element in an ndarray which passes a test implemented by a predicate function.

var Float64Array = require( '@stdlib/array-float64' );

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

// Create a data buffer:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

// Define the shape of the input array:
var shape = [ 3, 1, 2 ];

// Define the array strides:
var sx = [ 4, 4, 1 ];

// Define the index offset:
var ox = 0;

// Create the input ndarray-like object:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': shape,
    'strides': sx,
    'offset': ox,
    'order': 'row-major'
};

// Create an ndarray-like object containing a sentinel value:
var sentinelValue = {
    'dtype': 'float64',
    'data': new Float64Array( [ NaN ] ),
    'shape': [],
    'strides': [ 0 ],
    'offset': 0,
    'order': 'row-major'
};

// Perform reduction:
var out = find( [ x, sentinelValue ], isEven );
// returns 2.0

The function accepts the following arguments:

• arrays: array-like object containing an input ndarray and a zero-dimensional ndarray containing a sentinel value. The sentinel value is returned when no element in an input ndarray passes a test implemented by the predicate function.
• predicate: predicate function.
• thisArg: predicate function execution context (optional).

Each provided ndarray should be an object with the following properties:

• dtype: data type.
• data: data buffer.
• shape: dimensions.
• strides: stride lengths.
• offset: index offset.
• order: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).

The predicate function is provided the following arguments:

• value: current array element.
• indices: current array element indices.
• arr: the input ndarray.

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

var Float64Array = require( '@stdlib/array-float64' );

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

// Create a data buffer:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );

// Define the shape of the input array:
var shape = [ 3, 1, 2 ];

// Define the array strides:
var sx = [ 4, 4, 1 ];

// Define the index offset:
var ox = 0;

// Create the input ndarray-like object:
var x = {
    'dtype': 'float64',
    'data': xbuf,
    'shape': shape,
    'strides': sx,
    'offset': ox,
    'order': 'row-major'
};

// Create an ndarray-like object containing a sentinel value:
var sentinelValue = {
    'dtype': 'float64',
    'data': new Float64Array( [ NaN ] ),
    'shape': [],
    'strides': [ 0 ],
    'offset': 0,
    'order': 'row-major'
};

var ctx = {
    'count': 0
};

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

var count = ctx.count;
// returns 2

Notes

• For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing the operation in order to achieve better performance.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var Float64Array = require( '@stdlib/array-float64' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var find = require( '@stdlib/ndarray-base-find' );

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

var x = {
    'dtype': 'float64',
    'data': discreteUniform( 10, 0.0, 10.0, {
        'dtype': 'float64'
    }),
    'shape': [ 5, 2 ],
    'strides': [ 2, 1 ],
    'offset': 0,
    'order': 'row-major'
};
console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );

var sv = {
    'dtype': 'float64',
    'data': new Float64Array( [ NaN ] ),
    'shape': [],
    'strides': [ 0 ],
    'offset': 0,
    'order': x.order
};
console.log( 'Sentinel Value: %d', sv.data[ 0 ] );

var out = find( [ x, sv ], isEven );
console.log( out );

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Notice

This package is part of 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, see the main project repository.

Community

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.