any

Test whether at least one element in an ndarray is truthy.

Installation

npm install @stdlib/ndarray-base-any

Usage

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

any( arrays )

Tests whether at least one element in an ndarray is truthy.

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

// 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'
};

// Test elements:
var out = any( [ x ] );
// returns true

The function accepts the following arguments:

• arrays: array-like object containing an input ndarray.

The 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).

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

Examples

var bernoulli = require( '@stdlib/random-array-bernoulli' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var any = require( '@stdlib/ndarray-base-any' );

var x = {
    'dtype': 'generic',
    'data': bernoulli( 10, 0.1, {
        'dtype': 'generic'
    }),
    '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 out = any( [ x ] );
console.log( out );

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

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.