expandDimensions

Expand the shape of an array by inserting a new dimension of size one at a specified axis.

Installation

npm install @stdlib/ndarray-base-expand-dimensions

Usage

var expandDimensions = require( '@stdlib/ndarray-base-expand-dimensions' );

expandDimensions( x, axis )

Expands the shape of an array x by inserting a new dimension of size one at a specified axis.

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

// Create a 2x2 ndarray:
var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );
// returns <ndarray>

// Prepend a singleton dimension:
var y = expandDimensions( x, 0 );
// returns <ndarray>

var sh = y.shape;
// returns [ 1, 2, 2 ]

// Append a singleton dimension:
y = expandDimensions( x, 2 );
// returns <ndarray>

sh = y.shape;
// returns [ 2, 2, 1 ]

// Insert a singleton dimension:
y = expandDimensions( x, 1 );
// returns <ndarray>

sh = y.shape;
// returns [ 2, 1, 2 ]

Notes

• A provided axis must reside on the interval [-N-1, N], where N is the rank (i.e., number of dimensions) of the provided input array. If provided a negative axis, the axis position at which to insert a singleton dimension is computed as N + axis + 1. Hence, if provided -1, the resolved axis position is N (i.e., a singleton dimension is appended to the input array).

Examples

var array = require( '@stdlib/ndarray-array' );
var numel = require( '@stdlib/ndarray-base-numel' );
var ind2sub = require( '@stdlib/ndarray-ind2sub' );
var expandDimensions = require( '@stdlib/ndarray-base-expand-dimensions' );

// Create a 2-dimensional array:
var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );
// returns <ndarray>

// Insert a singleton dimension:
var y = expandDimensions( x, 1 );
// returns <ndarray>

// Retrieve the shape:
var sh = y.shape;
// returns [ 2, 1, 2 ]

// Retrieve the number of elements:
var N = numel( sh );

// Loop through the array elements...
var i;
for ( i = 0; i < N; i++ ) {
    console.log( 'Y[%s] = %d', ind2sub( sh, i ).join( ', ' ), y.iget( i ) );
}

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 © 2016-2024. The Stdlib Authors.