strmv
Perform one of the matrix-vector operations
x = A*x
orx = A^T*x
.
Usage
var strmv = require( '@stdlib/blas/base/strmv' );
strmv( order, uplo, trans, diag, N, A, LDA, x, sx )
Performs one of the matrix-vector operations x = A*x
or x = A^T*x
, where x
is an N
element vector and A
is an N
by N
unit, or non-unit, upper or lower triangular matrix.
var Float32Array = require( '@stdlib/array/float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
strmv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x, 1 );
// x => <Float32Array>[ 14.0, 8.0, 3.0 ]
The function has the following parameters:
- order: storage layout.
- uplo: specifies whether
A
is an upper or lower triangular matrix. - trans: specifies whether
A
should be transposed, conjugate-transposed, or not transposed. - diag: specifies whether
A
has a unit diagonal. - N: number of elements along each dimension of
A
. - A: input matrix stored in linear memory as a
Float32Array
. - lda: stride of the first dimension of
A
(a.k.a., leading dimension of the matrixA
). - x: input vector
Float32Array
. - sx:
x
stride length.
The stride parameters determine how elements in the input arrays are accessed at runtime. For example, to iterate over the elements of x
in reverse order,
var Float32Array = require( '@stdlib/array/float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
strmv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x, -1 );
// x => <Float32Array>[ 1.0, 4.0, 10.0 ]
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float32Array = require( '@stdlib/array/float32' );
// Initial arrays...
var x0 = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
strmv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x1, 1 );
// x0 => <Float32Array>[ 1.0, 6.0, 3.0, 1.0 ]
strmv.ndarray( uplo, trans, diag, N, A, sa1, sa2, oa, x, sx, ox )
Performs one of the matrix-vector operations x = A*x
or x = A^T*x
, using alternative indexing semantics and where x
is an N
element vector and A
is an N
by N
unit, or non-unit, upper or lower triangular matrix.
var Float32Array = require( '@stdlib/array/float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
strmv.ndarray( 'upper', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, 1, 0 );
// x => <Float32Array>[ 14.0, 8.0, 3.0 ]
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
.
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 Float32Array = require( '@stdlib/array/float32' );
var A = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
strmv.ndarray( 'upper', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, -1, 2 );
// x => <Float32Array>[ 1.0, 4.0, 10.0 ]
Notes
Examples
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var strmv = require( '@stdlib/blas/base/strmv' );
var opts = {
'dtype': 'float32'
};
var N = 5;
var A = discreteUniform( N*N, -10.0, 10.0, opts );
var x = discreteUniform( N, -10.0, 10.0, opts );
strmv( 'column-major', 'upper', 'no-transpose', 'unit', N, A, N, x, 1 );
console.log( x );
strmv.ndarray( 'upper', 'no-transpose', 'unit', N, A, 1, N, 0, x, 1, 0 );
console.log( x );
C APIs
Usage
TODO
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Examples
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