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.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

Test whether an ndarray contains a specified value.

npm install @stdlib/ndarray-base-includes

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.

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

Tests whether an ndarray contains a specified value.

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'
};

// Create the search element ndarray-like object:
var searchElement = {
    'dtype': 'float64',
    'data': new Float64Array( [ 6.0 ] ),
    'shape': [],
    'strides': [ 0 ],
    'offset': 0,
    'order': 'row-major'
};

// Perform reduction:
var out = includes( [ x, searchElement ] );
// returns true

The function accepts the following arguments:

• arrays: array-like object containing an input ndarray and a zero-dimensional search element ndarray.

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).

• 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.

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

var x = {
    'dtype': 'generic',
    'data': discreteUniform( 10, 0, 10, {
        '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 v = {
    'dtype': x.dtype,
    'data': [ 1 ],
    'shape': [],
    'strides': [ 0 ],
    'offset': 0,
    'order': x.order
};
console.log( 'Search element: %d', v.data[ 0 ] );

var out = includes( [ x, v ] );
console.log( out );

Character codes for data types:

• x: bool (boolean).
• z: complex128 (double-precision floating-point complex number).
• c: complex64 (single-precision floating-point complex number).
• f: float32 (single-precision floating-point number).
• d: float64 (double-precision floating-point number).
• k: int16 (signed 16-bit integer).
• i: int32 (signed 32-bit integer).
• s: int8 (signed 8-bit integer).
• t: uint16 (unsigned 16-bit integer).
• u: uint32 (unsigned 32-bit integer).
• b: uint8 (unsigned 8-bit integer).

Function name suffix naming convention:

stdlib_ndarray_includes_<input_data_type><search_element_data_type>_<output_data_type>[_as_<input_cast_data_type><search_element_cast_data_type>_<output_data_type>]

For example,

void stdlib_ndarray_includes_dd_x(...) {...}

is a function which accepts one double-precision floating-point input ndarray, a double-precision floating-point search element ndarray, and one boolean output ndarray.

TODO: document casting convention

#include "stdlib/ndarray/base/includes.h"

// TODO

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.

See LICENSE.

Copyright © 2016-2026. The Stdlib Authors.