Ternary

Apply a ternary callback to elements in input ndarrays and assign results to elements in an output ndarray.

Installation

npm install @stdlib/ndarray-base-ternary

Usage

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

ternary( arrays, fcn )

Applies a ternary callback to elements in input ndarrays and assigns results to elements in an output ndarray.

var Float64Array = require( '@stdlib/array-float64' );
var add3 = require( '@stdlib/number-float64-base-add3' );

// 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( [ 0.5, 0.5, 0.5, 0.5, 0.5, 0.5 ] );
var wbuf = 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 ];
var sw = [ 2, 2, 1 ];

// Define the index offsets:
var ox = 0;
var oy = 0;
var oz = 0;
var ow = 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'
};
var w = {
    'dtype': 'float64',
    'data': wbuf,
    'shape': shape,
    'strides': sw,
    'offset': ow,
    'order': 'row-major'
};

// Apply the ternary function:
ternary( [ x, y, z, w ], add3 );

console.log( w.data );
// => <Float64Array>[ 2.5, 3.5, 4.5, 5.5, 6.5, 7.5 ]

The function accepts the following arguments:

• arrays: array-like object containing three input ndarrays and one output ndarray.
• fcn: ternary function to apply.

Notes

• 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 ternary function in order to achieve better performance.

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarray = require( '@stdlib/array-filled' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var add3 = require( '@stdlib/number-float64-base-add3' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var ternary = require( '@stdlib/ndarray-base-ternary' );

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': filledarrayBy( N, 'generic', discreteUniform( -100, 100 ) ),
    'shape': x.shape.slice(),
    'strides': shape2strides( x.shape, 'row-major' ),
    'offset': 0,
    'order': 'row-major'
};
console.log( ndarray2array( z.data, z.shape, z.strides, z.offset, z.order ) );

var w = {
    'dtype': 'generic',
    'data': filledarray( 0, N, 'generic' ),
    'shape': x.shape.slice(),
    'strides': shape2strides( x.shape, 'column-major' ),
    'offset': 0,
    'order': 'column-major'
};

ternary( [ x, y, z, w ], add3 );
console.log( ndarray2array( w.data, w.shape, w.strides, w.offset, w.order ) );

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 © 2016-2026. The Stdlib Authors.