sggsvp - compute orthogonal matrices U, V and Q such that N-K-L K L U'*A*Q = K ( 0 A12 A13 ) if M-K-L >= 0
SUBROUTINE SGGSVP( JOBU, JOBV, JOBQ, M, P, N, A, LDA, B, LDB, TOLA, * TOLB, K, L, U, LDU, V, LDV, Q, LDQ, IWORK, TAU, WORK, INFO) CHARACTER * 1 JOBU, JOBV, JOBQ INTEGER M, P, N, LDA, LDB, K, L, LDU, LDV, LDQ, INFO INTEGER IWORK(*) REAL TOLA, TOLB REAL A(LDA,*), B(LDB,*), U(LDU,*), V(LDV,*), Q(LDQ,*), TAU(*), WORK(*)
SUBROUTINE SGGSVP_64( JOBU, JOBV, JOBQ, M, P, N, A, LDA, B, LDB, * TOLA, TOLB, K, L, U, LDU, V, LDV, Q, LDQ, IWORK, TAU, WORK, INFO) CHARACTER * 1 JOBU, JOBV, JOBQ INTEGER*8 M, P, N, LDA, LDB, K, L, LDU, LDV, LDQ, INFO INTEGER*8 IWORK(*) REAL TOLA, TOLB REAL A(LDA,*), B(LDB,*), U(LDU,*), V(LDV,*), Q(LDQ,*), TAU(*), WORK(*)
SUBROUTINE GGSVP( JOBU, JOBV, JOBQ, [M], [P], [N], A, [LDA], B, [LDB], * TOLA, TOLB, K, L, U, [LDU], V, [LDV], Q, [LDQ], [IWORK], [TAU], * [WORK], [INFO]) CHARACTER(LEN=1) :: JOBU, JOBV, JOBQ INTEGER :: M, P, N, LDA, LDB, K, L, LDU, LDV, LDQ, INFO INTEGER, DIMENSION(:) :: IWORK REAL :: TOLA, TOLB REAL, DIMENSION(:) :: TAU, WORK REAL, DIMENSION(:,:) :: A, B, U, V, Q
SUBROUTINE GGSVP_64( JOBU, JOBV, JOBQ, [M], [P], [N], A, [LDA], B, * [LDB], TOLA, TOLB, K, L, U, [LDU], V, [LDV], Q, [LDQ], [IWORK], * [TAU], [WORK], [INFO]) CHARACTER(LEN=1) :: JOBU, JOBV, JOBQ INTEGER(8) :: M, P, N, LDA, LDB, K, L, LDU, LDV, LDQ, INFO INTEGER(8), DIMENSION(:) :: IWORK REAL :: TOLA, TOLB REAL, DIMENSION(:) :: TAU, WORK REAL, DIMENSION(:,:) :: A, B, U, V, Q
#include <sunperf.h>
void sggsvp(char jobu, char jobv, char jobq, int m, int p, int n, float *a, int lda, float *b, int ldb, float tola, float tolb, int *k, int *l, float *u, int ldu, float *v, int ldv, float *q, int ldq, int *info);
void sggsvp_64(char jobu, char jobv, char jobq, long m, long p, long n, float *a, long lda, float *b, long ldb, float tola, float tolb, long *k, long *l, float *u, long ldu, float *v, long ldv, float *q, long ldq, long *info);
sggsvp computes orthogonal matrices U, V and Q such that L ( 0 0 A23 )
M-K-L ( 0 0 0 )
N-K-L K L
= K ( 0 A12 A13 ) if M-K-L < 0;
M-K ( 0 0 A23 )
N-K-L K L
V'*B*Q = L ( 0 0 B13 )
P-L ( 0 0 0 )
where the K-by-K matrix A12 and L-by-L matrix B13 are nonsingular upper triangular; A23 is L-by-L upper triangular if M-K-L >= 0, otherwise A23 is (M-K)-by-L upper trapezoidal. K+L = the effective numerical rank of the (M+P)-by-N matrix (A',B')'. Z' denotes the transpose of Z.
This decomposition is the preprocessing step for computing the Generalized Singular Value Decomposition (GSVD), see subroutine SGGSVD.
= 'U': Orthogonal matrix U is computed;
= 'N': U is not computed.
= 'V': Orthogonal matrix V is computed;
= 'N': V is not computed.
= 'Q': Orthogonal matrix Q is computed;
= 'N': Q is not computed.
max(1,M)
if
JOBU = 'U'; LDU > = 1 otherwise.
max(1,P)
if
JOBV = 'V'; LDV > = 1 otherwise.
max(1,N)
if
JOBQ = 'Q'; LDQ > = 1 otherwise.
dimension(N)
dimension(N)
dimension(MAX(3*N,M,P))
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
The subroutine uses LAPACK subroutine SGEQPF for the QR factorization with column pivoting to detect the effective numerical rank of the a matrix. It may be replaced by a better rank determination strategy.