Apply a binary callback to elements in input ndarrays and assign results to elements in an output ndarray.
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> Apply a binary callback to elements in input ndarrays and assign results to elements in an output ndarray.
``bash`
npm install @stdlib/ndarray-base-binary
`javascript`
var binary = require( '@stdlib/ndarray-base-binary' );
#### binary( arrays, fcn )
Applies a binary callback to elements in input ndarrays and assigns results to elements in an output ndarray.
`javascript
var Float64Array = require( '@stdlib/array-float64' );
var add = require( '@stdlib/number-float64-base-add' );
// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var ybuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
var zbuf = new Float64Array( 6 );
// Define the shape of the input and output arrays:
var shape = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 2, 2, 1 ];
var sy = [ 2, 2, 1 ];
var sz = [ 2, 2, 1 ];
// Define the index offsets:
var ox = 0;
var oy = 0;
var oz = 0;
// Create the input and output ndarray-like objects:
var x = {
'dtype': 'float64',
'data': xbuf,
'shape': shape,
'strides': sx,
'offset': ox,
'order': 'row-major'
};
var y = {
'dtype': 'float64',
'data': ybuf,
'shape': shape,
'strides': sy,
'offset': oy,
'order': 'row-major'
};
var z = {
'dtype': 'float64',
'data': zbuf,
'shape': shape,
'strides': sz,
'offset': oz,
'order': 'row-major'
};
// Apply the binary function:
binary( [ x, y, z ], add );
console.log( z.data );
// =>
`
The function accepts the following arguments:
- arrays: array-like object containing two input ndarrays and one output ndarray.
- fcn: binary function to apply.
- 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 applying a binary function in order to achieve better performance.
`javascript
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarray = require( '@stdlib/array-filled' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var add = require( '@stdlib/number-float64-base-add' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var binary = require( '@stdlib/ndarray-base-binary' );
var N = 10;
var x = {
'dtype': 'generic',
'data': filledarrayBy( N, 'generic', discreteUniform( -100, 100 ) ),
'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 y = {
'dtype': 'generic',
'data': filledarrayBy( N, 'generic', discreteUniform( -100, 100 ) ),
'shape': x.shape.slice(),
'strides': shape2strides( x.shape, 'column-major' ),
'offset': 0,
'order': 'column-major'
};
console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );
var z = {
'dtype': 'generic',
'data': filledarray( 0, N, 'generic' ),
'shape': x.shape.slice(),
'strides': shape2strides( x.shape, 'column-major' ),
'offset': 0,
'order': 'column-major'
};
binary( [ x, y, z ], add );
console.log( ndarray2array( z.data, z.shape, z.strides, z.offset, z.order ) );
`
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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