Apply a binary callback to elements in input ndarrays and assign results to elements in an output ndarray.
var binary = require( '@stdlib/ndarray/base/binary' );Applies a binary callback to elements in input ndarrays and assigns results to elements in an output ndarray.
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 );
// => <Float64Array>[ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]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.
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 ) );