dtrsv
Solve one of the systems of equations
A*x = borA^T*x = b.
Usage
var dtrsv = require( '@stdlib/blas/base/dtrsv' );
dtrsv( order, uplo, trans, diag, N, A, LDA, x, sx )
Solves one of the systems of equations A*x = b or A^T*x = b where b and x are N element vectors and A is an N by N unit, or non-unit, upper or lower triangular matrix.
var Float64Array = require( '@stdlib/array/float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
dtrsv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x, 1 );
// x => <Float64Array>[ 0.0, -4.0, 3.0 ]
The function has the following parameters:
- order: storage layout.
- uplo: specifies whether
Ais an upper or lower triangular matrix. - trans: specifies whether
Ashould be transposed, conjugate-transposed, or not transposed. - diag: specifies whether
Ahas a unit diagonal. - N: number of elements along each dimension of
A. - A: input matrix stored in linear memory as a
Float64Array. - lda: stride of the first dimension of
A(a.k.a., leading dimension of the matrixA). - x: input vector
Float64Array. - sx:
xstride 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 Float64Array = require( '@stdlib/array/float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float64Array( [ 3.0, 2.0, 1.0 ] );
dtrsv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x, -1 );
// x => <Float64Array>[ 3.0, -4.0, 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' );
// Initial arrays...
var x0 = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
dtrsv( 'row-major', 'upper', 'no-transpose', 'unit', 3, A, 3, x1, 1 );
// x0 => <Float64Array>[ 1.0, 0.0, -1.0, 1.0 ]
dtrsv.ndarray( uplo, trans, diag, N, A, sa1, sa2, oa, x, sx, ox )
Solves one of the systems of equations A*x = b or A^T*x = b, using alternative indexing semantics and where b and x are N element vectors and A is an N by N unit, or non-unit, upper or lower triangular matrix.
var Float64Array = require( '@stdlib/array/float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
dtrsv.ndarray( 'upper', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, 1, 0 );
// x => <Float64Array>[ 0.0, -4.0, 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 Float64Array = require( '@stdlib/array/float64' );
var A = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 1.0, 2.0, 0.0, 0.0, 1.0 ] );
var x = new Float64Array( [ 3.0, 2.0, 1.0 ] );
dtrsv.ndarray( 'upper', 'no-transpose', 'unit', 3, A, 3, 1, 0, x, -1, 2 );
// x => <Float64Array>[ 3.0, -4.0, 0.0 ]
Notes
Examples
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var dtrsv = require( '@stdlib/blas/base/dtrsv' );
var opts = {
'dtype': 'float64'
};
var N = 5;
var A = discreteUniform( N*N, -10.0, 10.0, opts );
var x = discreteUniform( N, -10.0, 10.0, opts );
dtrsv( 'column-major', 'upper', 'no-transpose', 'unit', N, A, N, x, 1 );
console.log( x );
dtrsv.ndarray( 'upper', 'no-transpose', 'unit', N, A, 1, N, 0, x, 1, 0 );
console.log( x );
C APIs
Usage
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Examples
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