@stdlib/ndarray-base-broadcast-scalar

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broadcastScalar

Broadcast a scalar value to an ndarray having a specified shape.

Installation

npm install @stdlib/ndarray-base-broadcast-scalar

Usage

var broadcastScalar = require( '@stdlib/ndarray-base-broadcast-scalar' );

broadcastScalar( value, dtype, shape, order )

Broadcast a scalar value to an ndarray having a specified shape and data type.

var x = broadcastScalar( 1.0, 'float64', [ 2, 2 ], 'row-major' );
// returns <ndarray>

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

var dt = x.dtype;
// returns 'float64'

var v = x.get( 0, 0 );
// returns 1.0

Notes

• If value is a number and dtype is a complex data type, the function returns an ndarray containing a complex number whose real component equals the provided scalar value and whose imaginary component is zero.
• The returned ndarray is a view on an ndarray data buffer containing a single element. The view is not contiguous. As more than one element of a returned view may refer to the same memory location, writing to the view may affect multiple elements. If you need to write to the returned ndarray, copy the ndarray before performing operations which may mutate elements.
• The returned ndarray is a "base" ndarray, and, thus, the returned ndarray does not perform bounds checking or afford any of the guarantees of the non-base ndarray constructor. The primary intent of this function is to broadcast a scalar value as an ndarray within internal implementations and to do so with minimal overhead.

Examples

var dtypes = require( '@stdlib/ndarray-dtypes' );
var broadcastScalar = require( '@stdlib/ndarray-base-broadcast-scalar' );

// Get a list of data types:
var dt = dtypes();

// Generate two-dimensional arrays...
var x;
var i;
for ( i = 0; i < dt.length; i++ ) {
    x = broadcastScalar( i, dt[ i ], [ 2, 2 ], 'row-major' );
    console.log( x.get( 0, 1 ) );
}

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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

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