isComplex64ndarrayLike

Test if a value is an ndarray-like object containing single-precision complex floating-point numbers.

Installation

npm install @stdlib/assert-is-complex64ndarray-like

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 isComplex64ndarrayLike = require( '@stdlib/assert-is-complex64ndarray-like' );

isComplex64ndarrayLike( value )

Tests if a value is an ndarray-like object whose underlying data type is complex64.

var Complex64Array = require( '@stdlib/array-complex64' );
var ndarray = require( '@stdlib/ndarray-ctor' );

var arr = ndarray( 'complex64', new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] ), [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );

var bool = isComplex64ndarrayLike( arr );
// returns true

Examples

var ndarray = require( '@stdlib/ndarray-ctor' );
var Complex64Array = require( '@stdlib/array-complex64' );
var isComplex64ndarrayLike = require( '@stdlib/assert-is-complex64ndarray-like' );

var buffer = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );
var arr = ndarray( 'complex64', buffer, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );

var out = isComplex64ndarrayLike( arr );
// returns true

out = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] );
// returns false

out = isComplex64ndarrayLike( {} );
// returns false

out = isComplex64ndarrayLike( null );
// returns false

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.