@stdlib/math-strided-ops-add-by

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addBy

Element-wise addition of two strided arrays via a callback function.

Installation

npm install @stdlib/math-strided-ops-add-by

Usage

var addBy = require( '@stdlib/math-strided-ops-add-by' );

addBy( N, x, strideX, y, strideY, z, strideZ, clbk[, thisArg] )

Performs element-wise addition of two strided arrays via a callback function and assigns each result to an element in an output strided array.

function accessor( values ) {
    return values;
}

var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 11.0, 12.0, 13.0, 14.0, 15.0 ];
var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];

addBy( x.length, x, 1, y, 1, z, 1, accessor );
// z => [ 12.0, 14.0, 16.0, 18.0, 20.0 ]

The function accepts the following arguments:

• N: number of indexed elements.
• x: input Array, typed array, or an array-like object (excluding strings and functions).
• strideX: index increment for x.
• y: input Array, typed array, or an array-like object (excluding strings and functions).
• strideY: index increment for y.
• z: output Array, typed array, or an array-like object (excluding strings and functions).
• strideZ: index increment for z.
• clbk: callback function.
• thisArg: execution context (optional).

The invoked callback function is provided four arguments:

• values: input array element values [vx, vy].
• idx: iteration index (zero-based).
• indices: input and output array strided indices [ix, iy, iz] (computed according to offset + idx*stride).
• arrays: input and output arrays/collections [x, y, z].

To set the callback execution context, provide a thisArg.

function accessor( values ) {
    this.count += 1;
    return values;
}

var context = {
    'count': 0
};

var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 11.0, 12.0, 13.0, 14.0, 15.0 ];
var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];

addBy( x.length, x, 1, y, 1, z, 1, accessor, context );
// z => [ 12.0, 14.0, 16.0, 18.0, 20.0 ]

var cnt = context.count;
// returns 5

The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to index every other value in x and to index the first N elements of y in reverse order,

function accessor( values ) {
    return values;
}

var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var y = [ 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ];
var z = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

addBy( 3, x, 2, y, -1, z, 1, accessor );
// z => [ 14.0, 15.0, 16.0, 0.0, 0.0, 0.0 ]

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

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

function accessor( values ) {
    return values;
}

// Initial arrays...
var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] );
var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );

// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*3 ); // start at 4th element

addBy( 3, x1, -2, y1, 1, z1, 1, accessor );
// z0 => <Float64Array>[ 0.0, 0.0, 0.0, 20.0, 19.0, 18.0 ]

addBy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, z, strideZ, offsetZ, clbk[, thisArg] )

Performs element-wise addition of two strided arrays via a callback function and assigns each result to an element in an output strided array using alternative indexing semantics.

function accessor( values ) {
    return values;
}

var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 11.0, 12.0, 13.0, 14.0, 15.0 ];
var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];

addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, accessor );
// z => [ 12.0, 14.0, 16.0, 18.0, 20.0 ]

The function accepts the following additional arguments:

• offsetX: starting index for x.
• offsetY: starting index for y.
• offsetZ: starting index for z.

While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to index every other value in x starting from the second value and to index the last N elements in y,

function accessor( values ) {
    return values;
}

var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var y = [ 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ];
var z = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

addBy.ndarray( 3, x, 2, 1, y, -1, y.length-1, z, 1, 2, accessor );
// z => [ 0.0, 0.0, 0.0, 20.0, 19.0, 18.0 ]

Notes

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

  function accessor() {
      // No-op...
  }
  
  var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
  var y = [ 11.0, 12.0, 13.0, 14.0, 15.0 ];
  var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
  
  addBy( x.length, x, 1, y, 1, z, 1, accessor );
  // z => [ 0.0, 0.0, 0.0, 0.0, 0.0 ]

Examples

var uniform = require( '@stdlib/random-base-uniform' ).factory;
var filledarray = require( '@stdlib/array-filled' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var addBy = require( '@stdlib/math-strided-ops-add-by' );

function accessor( values, i ) {
    if ( (i%3) === 0 ) {
        // Simulate a "missing" value...
        return;
    }
    return values;
}

var x = filledarrayBy( 10, 'generic', uniform( -10.0, 10.0 ) );
console.log( x );

var y = filledarrayBy( x.length, 'generic', uniform( -10.0, 10.0 ) );
console.log( y );

var z = filledarray( null, x.length, 'generic' );
console.log( z );

addBy.ndarray( x.length, x, 1, 0, y, -1, y.length-1, z, 1, 0, accessor );
console.log( z );

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See Also

• @stdlib/math-strided/ops/add: element-wise addition of two strided arrays.
• @stdlib/math-strided/ops/mul-by: element-wise multiplication of two strided arrays via a callback function.
• @stdlib/math-strided/ops/sub-by: element-wise subtraction of two strided arrays via a callback function.

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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.

Community

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License

See LICENSE.

Copyright

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