naginterfaces.library.lapackeig.zgelss¶
- naginterfaces.library.lapackeig.zgelss(a, b, rcond)[source]¶
zgelss
computes the minimum norm solution to a complex linear least squares problemFor full information please refer to the NAG Library document for f08kn
https://support.nag.com/numeric/nl/nagdoc_30.2/flhtml/f08/f08knf.html
- Parameters
- acomplex, array-like, shape
The matrix .
- bcomplex, array-like, shape
The right-hand side matrix .
- rcondfloat
Used to determine the effective rank of . Singular values are treated as zero. If , machine precision is used instead.
- Returns
- acomplex, ndarray, shape
The first rows of are overwritten with its right singular vectors, stored row-wise.
- bcomplex, ndarray, shape
is overwritten by the solution matrix . If and , the residual sum of squares for the solution in the th column is given by the sum of squares of the modulus of elements in that column.
- sfloat, ndarray, shape
The singular values of in decreasing order.
- rankint
The effective rank of , i.e., the number of singular values which are greater than .
- Raises
- NagValueError
- (errno )
On entry, error in parameter .
Constraint: .
- (errno )
On entry, error in parameter .
Constraint: .
- (errno )
On entry, error in parameter .
Constraint: .
- (errno )
The algorithm for computing the SVD failed to converge; off-diagonal elements of an intermediate bidiagonal form did not converge to zero.
- Notes
zgelss
uses the singular value decomposition (SVD) of , where is an matrix which may be rank-deficient.Several right-hand side vectors and solution vectors can be handled in a single call; they are stored as the columns of the right-hand side matrix and the solution matrix .
The effective rank of is determined by treating as zero those singular values which are less than times the largest singular value.
- References
Anderson, E, Bai, Z, Bischof, C, Blackford, S, Demmel, J, Dongarra, J J, Du Croz, J J, Greenbaum, A, Hammarling, S, McKenney, A and Sorensen, D, 1999, LAPACK Users’ Guide, (3rd Edition), SIAM, Philadelphia, https://www.netlib.org/lapack/lug
Golub, G H and Van Loan, C F, 1996, Matrix Computations, (3rd Edition), Johns Hopkins University Press, Baltimore