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unaryBy

Apply a unary function to each element in an input ndarray according to a callback function and assign results to elements in an output ndarray.

Installation

npm install @stdlib/ndarray-base-unary-by

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var unaryBy = require( '@stdlib/ndarray-base-unary-by' );

unaryBy( arrays, fcn, clbk[, thisArg] )

Applies a unary function to each element retrieved from an input ndarray according to a callback function and assigns results to elements in an output ndarray.

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

function scale( x ) {
    return x * 10.0;
}

function accessor( v ) {
    return v * 2.0;
}

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
var ybuf = new Float64Array( 6 );

// Define the shape of the input and output arrays:
var shape = [ 3, 1, 2 ];

// Define the array strides:
var sx = [ 4, 4, 1 ];
var sy = [ 2, 2, 1 ];

// Define the index offsets:
var ox = 1;
var oy = 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'
};

// Apply the unary function:
unaryBy( [ x, y ], scale, accessor );

console.log( y.data );
// => <Float64Array>[ 40.0, 60.0, 120.0, 140.0, 200.0, 220.0 ]

The function accepts the following arguments:

• arrays: array-like object containing one input ndarray and one output ndarray.
• fcn: unary 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).

The invoked callback function is provided four arguments:

• value: input array element.
• idx: iteration index (zero-based).
• indices: input and output ndarray data buffer indices [ix, iy].
• arrays: input and output ndarrays [x, y].

To set the callback execution context, provide a thisArg.

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

function scale( x ) {
    return x * 10.0;
}

function accessor( v ) {
    this.count += 1;
    return v * 2.0;
}

// Create data buffers:
var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
var ybuf = new Float64Array( 6 );

// Define the shape of the input and output arrays:
var shape = [ 3, 1, 2 ];

// Define the array strides:
var sx = [ 4, 4, 1 ];
var sy = [ 2, 2, 1 ];

// Define the index offsets:
var ox = 1;
var oy = 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'
};

// Apply the unary function:
var context = {
    'count': 0
};
unaryBy( [ x, y ], scale, accessor, context );

var cnt = context.count;
// returns 6

Notes

• For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before applying a unary function in order to achieve better performance.

• If a provided callback function does not return any value (or equivalently, explicitly returns undefined), the value is ignored.

  var Float64Array = require( '@stdlib/array-float64' );
  
  function scale( x ) {
      return x * 10.0;
  }
  
  function accessor() {
      // No-op...
  }
  
  // Create data buffers:
  var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
  var ybuf = new Float64Array( 6 );
  
  // Define the shape of the input and output arrays:
  var shape = [ 3, 1, 2 ];
  
  // Define the array strides:
  var sx = [ 4, 4, 1 ];
  var sy = [ 2, 2, 1 ];
  
  // Define the index offsets:
  var ox = 1;
  var oy = 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'
  };
  
  // Apply the unary function:
  unaryBy( [ x, y ], scale, accessor );
  
  console.log( y.data );
  // => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]

Examples

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarray = require( '@stdlib/array-filled' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var abs = require( '@stdlib/math-base-special-abs' );
var sqrt = require( '@stdlib/math-base-special-sqrt' );
var naryFunction = require( '@stdlib/utils-nary-function' );
var shape2strides = require( '@stdlib/ndarray-base-shape2strides' );
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var unaryBy = require( '@stdlib/ndarray-base-unary-by' );

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

unaryBy( [ x, y ], sqrt, naryFunction( abs, 1 ) );
console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
console.log( ndarray2array( y.data, y.shape, y.strides, y.offset, y.order ) );

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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.

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License

See LICENSE.

Copyright

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