@stdlib/ndarray-base-unary-by

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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

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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