@stdlib/blas-base-gaxpy
v0.2.2
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Multiply x by a constant and add the result to y.
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gaxpy
Multiply
x
by a constantalpha
and add the result toy
.
Installation
npm install @stdlib/blas-base-gaxpy
Usage
var gaxpy = require( '@stdlib/blas-base-gaxpy' );
gaxpy( N, alpha, x, strideX, y, strideY )
Multiplies x
by a constant alpha
and adds the result to y
.
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];
var alpha = 5.0;
gaxpy( x.length, alpha, x, 1, y, 1 );
// y => [ 6.0, 11.0, 16.0, 21.0, 26.0 ]
The function has the following parameters:
- N: number of indexed elements.
- alpha:
numeric
constant. - x: input
Array
ortyped array
. - strideX: index increment for
x
. - y: input
Array
ortyped array
. - strideY: index increment for
y
.
The N
and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other value in x
by alpha
and add the result to the first N
elements of y
in reverse order,
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];
gaxpy( 3, 5.0, x, 2, y, -1 );
// y => [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
// Initial arrays...
var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
// 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
gaxpy( 3, 5.0, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )
Multiplies x
by a constant alpha
and adds the result to y
using alternative indexing semantics.
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];
var alpha = 5.0;
gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 );
// y => [ 6.0, 11.0, 16.0, 21.0, 26.0 ]
The function has the following additional parameters:
- offsetX: starting index for
x
. - offsetY: starting index for
y
.
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 multiply every other value in x
by a constant alpha
starting from the second value and add to the last N
elements in y
where x[i] -> y[n]
, x[i+2] -> y[n-1]
,...,
var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];
var y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];
gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 );
// y => [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
Notes
- If
N <= 0
oralpha == 0
, both functions returny
unchanged. gaxpy()
corresponds to the BLAS level 1 functiondaxpy
with the exception that this implementation works with any array type, not just Float64Arrays. Depending on the environment, the typed versions (daxpy
,saxpy
, etc.) are likely to be significantly more performant.
Examples
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var gaxpy = require( '@stdlib/blas-base-gaxpy' );
var opts = {
'dtype': 'generic'
};
var x = discreteUniform( 10, 0, 100, opts );
console.log( x );
var y = discreteUniform( x.length, 0, 10, opts );
console.log( y );
gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, -1, y.length-1 );
console.log( y );
See Also
@stdlib/blas-base/daxpy
: multiply a vector x by a constant and add the result to y.@stdlib/blas-base/saxpy
: multiply a vector x by a constant and add the result to y.
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 © 2016-2024. The Stdlib Authors.