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Perform one of the matrix-vector operations
y = α*A*x + β*yory = α*A^T*x + β*yory = α*A^H*x + β*y.
npm install @stdlib/blas-base-cgemvAlternatively,
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umdbranch (see README).
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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.
var cgemv = require( '@stdlib/blas-base-cgemv' );Performs one of the matrix-vector operations y = α*A*x + β*y or y = α*A^T*x + β*y or y = α*A^H*x + β*y where α and β are scalars, x and y are vectors, and A is an M by N matrix.
var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var A = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 7.0, 8.0, 8.0 ] );
var x = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] );
var y = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0 ] );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
cgemv( 'column-major', 'no-transpose', 4, 2, alpha, A, 4, x, 1, beta, y, 1 );
// y => <Complex64Array>[ -10.0, 11.0, -12.0, 14.0, -14.0, 17.0, -16.0, 20.0 ]The function has the following parameters:
- order: storage layout.
- trans: specifies whether
Ashould be transposed, conjugate-transposed, or not transposed. - M: number of rows in the matrix
A. - N: number of columns in the matrix
A. - α: scalar constant.
- A: input matrix stored in linear memory as a
Complex64Array. - LDA: stride of the first dimension of
A(a.k.a., leading dimension of the matrixA). - x: input
Complex64Array. - sx: stride length for
x. - β: scalar constant.
- y: output
Complex64Array. - sy: stride length for
y.
The stride parameters determine how elements are accessed. For example, to iterate over every other element in x and y,
var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var A = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 7.0, 8.0, 8.0 ] );
var x = new Complex64Array( [ 1.0, 1.0, 0.0, 0.0, 2.0, 2.0, 0.0, 0.0 ] );
var y = new Complex64Array( [ 1.0, 1.0, 0.0, 0.0, 2.0, 2.0, 0.0, 0.0, 3.0, 3.0, 0.0, 0.0, 4.0, 4.0 ] );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
cgemv( 'column-major', 'no-transpose', 4, 2, alpha, A, 4, x, 2, beta, y, 2 );
// y => <Complex64Array>[ -10.0, 11.0, 0.0, 0.0, -12.0, 14.0, 0.0, 0.0, -14.0, 17.0, 0.0, 0.0, -16.0, 20.0 ]Note that indexing is relative to the first index. To introduce an offset, use typed array views.
var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
// Initial arrays...
var x0 = new Complex64Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0 ] );
var y0 = new Complex64Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0 ] );
var A = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 7.0, 8.0, 8.0 ] );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
// Create offset views...
var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd complex element
var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd complex element
cgemv( 'column-major', 'no-transpose', 4, 2, alpha, A, 4, x1, 1, beta, y1, 1 );
// y1 => <Complex64Array>[ -10.0, 11.0, -12.0, 14.0, -14.0, 17.0, -16.0, 20.0 ]Performs one of the matrix-vector operations y = α*A*x + β*y or y = α*A^T*x + β*y or y = α*A^H*x + β*y using alternative indexing semantics and where α and β are scalars, x and y are vectors, and A is an M by N matrix.
var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var A = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 7.0, 8.0, 8.0 ] );
var x = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] );
var y = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0 ] );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
cgemv.ndarray( 'no-transpose', 4, 2, alpha, A, 1, 4, 0, x, 1, 0, beta, y, 1, 0 );
// y => <Complex64Array>[ -10.0, 11.0, -12.0, 14.0, -14.0, 17.0, -16.0, 20.0 ]The function has the following additional parameters:
- sa1: stride of the first dimension of
A. - sa2: stride of the second dimension of
A. - oa: starting index for
A. - ox: starting index for
x. - oy: 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,
var Complex64Array = require( '@stdlib/array-complex64' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var A = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0, 6.0, 6.0, 7.0, 7.0, 8.0, 8.0 ] );
var x = new Complex64Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0 ] );
var y = new Complex64Array( [ 4.0, 4.0, 0.0, 0.0, 3.0, 3.0, 0.0, 0.0, 2.0, 2.0, 0.0, 0.0, 1.0, 1.0 ] );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
cgemv.ndarray( 'no-transpose', 4, 2, alpha, A, 1, 4, 0, x, 1, 1, beta, y, -2, 6 );
// y => <Complex64Array>[ -16.0, 20.0, 0.0, 0.0, -14.0, 17.0, 0.0, 0.0, -12.0, 14.0, 0.0, 0.0, -10.0, 11.0 ]var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var Complex64 = require( '@stdlib/complex-float32-ctor' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var logEach = require( '@stdlib/console-log-each' );
var cgemv = require( '@stdlib/blas-base-cgemv' );
function rand() {
return new Complex64( discreteUniform( 0, 255 ), discreteUniform( -128, 127 ) );
}
var M = 3;
var N = 3;
var A = filledarrayBy( M*N, 'complex64', rand );
var x = filledarrayBy( N, 'complex64', rand );
var y = filledarrayBy( M, 'complex64', rand );
var alpha = new Complex64( 0.5, 0.5 );
var beta = new Complex64( 0.5, -0.5 );
cgemv( 'column-major', 'no-transpose', M, N, alpha, A, 4, x, 1, beta, y, 1 );
// Print the results:
logEach( '%s', x );
cgemv.ndarray( 'no-transpose', M, N, alpha, A, 1, 4, 0, x, 1, 0, beta, y, 1, 0 );
// Print the results:
logEach( '%s', x );TODOTODO.
TODOTODO
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