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tgsja(3) Library Functions Manual tgsja(3)

NAME

tgsja - tgsja: generalized SVD of trapezoidal matrices, step in ggsvd3

SYNOPSIS

Functions


subroutine CTGSJA (jobu, jobv, jobq, m, p, n, k, l, a, lda, b, ldb, tola, tolb, alpha, beta, u, ldu, v, ldv, q, ldq, work, ncycle, info)
CTGSJA subroutine DTGSJA (jobu, jobv, jobq, m, p, n, k, l, a, lda, b, ldb, tola, tolb, alpha, beta, u, ldu, v, ldv, q, ldq, work, ncycle, info)
DTGSJA subroutine STGSJA (jobu, jobv, jobq, m, p, n, k, l, a, lda, b, ldb, tola, tolb, alpha, beta, u, ldu, v, ldv, q, ldq, work, ncycle, info)
STGSJA subroutine ZTGSJA (jobu, jobv, jobq, m, p, n, k, l, a, lda, b, ldb, tola, tolb, alpha, beta, u, ldu, v, ldv, q, ldq, work, ncycle, info)
ZTGSJA

Detailed Description

Function Documentation

subroutine CTGSJA (character jobu, character jobv, character jobq, integer m, integer p, integer n, integer k, integer l, complex, dimension( lda, * ) a, integer lda, complex, dimension( ldb, * ) b, integer ldb, real tola, real tolb, real, dimension( * ) alpha, real, dimension( * ) beta, complex, dimension( ldu, * ) u, integer ldu, complex, dimension( ldv, * ) v, integer ldv, complex, dimension( ldq, * ) q, integer ldq, complex, dimension( * ) work, integer ncycle, integer info)

CTGSJA

Purpose:

!>
!> CTGSJA computes the generalized singular value decomposition (GSVD)
!> of two complex upper triangular (or trapezoidal) matrices A and B.
!>
!> On entry, it is assumed that matrices A and B have the following
!> forms, which may be obtained by the preprocessing subroutine CGGSVP
!> from a general M-by-N matrix A and P-by-N matrix B:
!>
!>              N-K-L  K    L
!>    A =    K ( 0    A12  A13 ) if M-K-L >= 0;
!>           L ( 0     0   A23 )
!>       M-K-L ( 0     0    0  )
!>
!>            N-K-L  K    L
!>    A =  K ( 0    A12  A13 ) if M-K-L < 0;
!>       M-K ( 0     0   A23 )
!>
!>            N-K-L  K    L
!>    B =  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.
!>
!> On exit,
!>
!>        U**H *A*Q = D1*( 0 R ),    V**H *B*Q = D2*( 0 R ),
!>
!> where U, V and Q are unitary matrices.
!> R is a nonsingular upper triangular matrix, and D1
!> and D2 are ``diagonal'' matrices, which are of the following
!> structures:
!>
!> If M-K-L >= 0,
!>
!>                     K  L
!>        D1 =     K ( I  0 )
!>                 L ( 0  C )
!>             M-K-L ( 0  0 )
!>
!>                    K  L
!>        D2 = L   ( 0  S )
!>             P-L ( 0  0 )
!>
!>                N-K-L  K    L
!>   ( 0 R ) = K (  0   R11  R12 ) K
!>             L (  0    0   R22 ) L
!>
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
!>   S = diag( BETA(K+1),  ... , BETA(K+L) ),
!>   C**2 + S**2 = I.
!>
!>   R is stored in A(1:K+L,N-K-L+1:N) on exit.
!>
!> If M-K-L < 0,
!>
!>                K M-K K+L-M
!>     D1 =   K ( I  0    0   )
!>          M-K ( 0  C    0   )
!>
!>                  K M-K K+L-M
!>     D2 =   M-K ( 0  S    0   )
!>          K+L-M ( 0  0    I   )
!>            P-L ( 0  0    0   )
!>
!>                N-K-L  K   M-K  K+L-M
!> ( 0 R ) =    K ( 0    R11  R12  R13  )
!>           M-K ( 0     0   R22  R23  )
!>         K+L-M ( 0     0    0   R33  )
!>
!> where
!> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
!> S = diag( BETA(K+1),  ... , BETA(M) ),
!> C**2 + S**2 = I.
!>
!> R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
!>     (  0  R22 R23 )
!> in B(M-K+1:L,N+M-K-L+1:N) on exit.
!>
!> The computation of the unitary transformation matrices U, V or Q
!> is optional.  These matrices may either be formed explicitly, or they
!> may be postmultiplied into input matrices U1, V1, or Q1.
!>

Parameters

JOBU 

!>          JOBU is CHARACTER*1
!>          = 'U':  U must contain a unitary matrix U1 on entry, and
!>                  the product U1*U is returned;
!>          = 'I':  U is initialized to the unit matrix, and the
!>                  unitary matrix U is returned;
!>          = 'N':  U is not computed.
!>

JOBV

!>          JOBV is CHARACTER*1
!>          = 'V':  V must contain a unitary matrix V1 on entry, and
!>                  the product V1*V is returned;
!>          = 'I':  V is initialized to the unit matrix, and the
!>                  unitary matrix V is returned;
!>          = 'N':  V is not computed.
!>

JOBQ

!>          JOBQ is CHARACTER*1
!>          = 'Q':  Q must contain a unitary matrix Q1 on entry, and
!>                  the product Q1*Q is returned;
!>          = 'I':  Q is initialized to the unit matrix, and the
!>                  unitary matrix Q is returned;
!>          = 'N':  Q is not computed.
!>

M

!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!>

P

!>          P is INTEGER
!>          The number of rows of the matrix B.  P >= 0.
!>

N

!>          N is INTEGER
!>          The number of columns of the matrices A and B.  N >= 0.
!>

K

!>          K is INTEGER
!>

L

!>          L is INTEGER
!>
!>          K and L specify the subblocks in the input matrices A and B:
!>          A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,,N-L+1:N)
!>          of A and B, whose GSVD is going to be computed by CTGSJA.
!>          See Further Details.
!>

A

!>          A is COMPLEX array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
!>          matrix R or part of R.  See Purpose for details.
!>

LDA

!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!>

B

!>          B is COMPLEX array, dimension (LDB,N)
!>          On entry, the P-by-N matrix B.
!>          On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
!>          a part of R.  See Purpose for details.
!>

LDB

!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,P).
!>

TOLA

!>          TOLA is REAL
!>

TOLB

!>          TOLB is REAL
!>
!>          TOLA and TOLB are the convergence criteria for the Jacobi-
!>          Kogbetliantz iteration procedure. Generally, they are the
!>          same as used in the preprocessing step, say
!>              TOLA = MAX(M,N)*norm(A)*MACHEPS,
!>              TOLB = MAX(P,N)*norm(B)*MACHEPS.
!>

ALPHA

!>          ALPHA is REAL array, dimension (N)
!>

BETA

!>          BETA is REAL array, dimension (N)
!>
!>          On exit, ALPHA and BETA contain the generalized singular
!>          value pairs of A and B;
!>            ALPHA(1:K) = 1,
!>            BETA(1:K)  = 0,
!>          and if M-K-L >= 0,
!>            ALPHA(K+1:K+L) = diag(C),
!>            BETA(K+1:K+L)  = diag(S),
!>          or if M-K-L < 0,
!>            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
!>            BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
!>          Furthermore, if K+L < N,
!>            ALPHA(K+L+1:N) = 0
!>            BETA(K+L+1:N)  = 0.
!>

U

!>          U is COMPLEX array, dimension (LDU,M)
!>          On entry, if JOBU = 'U', U must contain a matrix U1 (usually
!>          the unitary matrix returned by CGGSVP).
!>          On exit,
!>          if JOBU = 'I', U contains the unitary matrix U;
!>          if JOBU = 'U', U contains the product U1*U.
!>          If JOBU = 'N', U is not referenced.
!>

LDU

!>          LDU is INTEGER
!>          The leading dimension of the array U. LDU >= max(1,M) if
!>          JOBU = 'U'; LDU >= 1 otherwise.
!>

V

!>          V is COMPLEX array, dimension (LDV,P)
!>          On entry, if JOBV = 'V', V must contain a matrix V1 (usually
!>          the unitary matrix returned by CGGSVP).
!>          On exit,
!>          if JOBV = 'I', V contains the unitary matrix V;
!>          if JOBV = 'V', V contains the product V1*V.
!>          If JOBV = 'N', V is not referenced.
!>

LDV

!>          LDV is INTEGER
!>          The leading dimension of the array V. LDV >= max(1,P) if
!>          JOBV = 'V'; LDV >= 1 otherwise.
!>

Q

!>          Q is COMPLEX array, dimension (LDQ,N)
!>          On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
!>          the unitary matrix returned by CGGSVP).
!>          On exit,
!>          if JOBQ = 'I', Q contains the unitary matrix Q;
!>          if JOBQ = 'Q', Q contains the product Q1*Q.
!>          If JOBQ = 'N', Q is not referenced.
!>

LDQ

!>          LDQ is INTEGER
!>          The leading dimension of the array Q. LDQ >= max(1,N) if
!>          JOBQ = 'Q'; LDQ >= 1 otherwise.
!>

WORK

!>          WORK is COMPLEX array, dimension (2*N)
!>

NCYCLE

!>          NCYCLE is INTEGER
!>          The number of cycles required for convergence.
!>

INFO

!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value.
!>          = 1:  the procedure does not converge after MAXIT cycles.
!>

Internal Parameters:

!>  MAXIT   INTEGER
!>          MAXIT specifies the total loops that the iterative procedure
!>          may take. If after MAXIT cycles, the routine fails to
!>          converge, we return INFO = 1.
!>

Author

Univ. of Tennessee

Univ. of California Berkeley

Univ. of Colorado Denver

NAG Ltd.

Further Details:

!>
!>  CTGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
!>  min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
!>  matrix B13 to the form:
!>
!>           U1**H *A13*Q1 = C1*R1; V1**H *B13*Q1 = S1*R1,
!>
!>  where U1, V1 and Q1 are unitary matrix.
!>  C1 and S1 are diagonal matrices satisfying
!>
!>                C1**2 + S1**2 = I,
!>
!>  and R1 is an L-by-L nonsingular upper triangular matrix.
!>

Definition at line 376 of file ctgsja.f.

subroutine DTGSJA (character jobu, character jobv, character jobq, integer m, integer p, integer n, integer k, integer l, double precision, dimension( lda, * ) a, integer lda, double precision, dimension( ldb, * ) b, integer ldb, double precision tola, double precision tolb, double precision, dimension( * ) alpha, double precision, dimension( * ) beta, double precision, dimension( ldu, * ) u, integer ldu, double precision, dimension( ldv, * ) v, integer ldv, double precision, dimension( ldq, * ) q, integer ldq, double precision, dimension( * ) work, integer ncycle, integer info)

DTGSJA

Purpose:

!>
!> DTGSJA computes the generalized singular value decomposition (GSVD)
!> of two real upper triangular (or trapezoidal) matrices A and B.
!>
!> On entry, it is assumed that matrices A and B have the following
!> forms, which may be obtained by the preprocessing subroutine DGGSVP
!> from a general M-by-N matrix A and P-by-N matrix B:
!>
!>              N-K-L  K    L
!>    A =    K ( 0    A12  A13 ) if M-K-L >= 0;
!>           L ( 0     0   A23 )
!>       M-K-L ( 0     0    0  )
!>
!>            N-K-L  K    L
!>    A =  K ( 0    A12  A13 ) if M-K-L < 0;
!>       M-K ( 0     0   A23 )
!>
!>            N-K-L  K    L
!>    B =  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.
!>
!> On exit,
!>
!>        U**T *A*Q = D1*( 0 R ),    V**T *B*Q = D2*( 0 R ),
!>
!> where U, V and Q are orthogonal matrices.
!> R is a nonsingular upper triangular matrix, and D1 and D2 are
!> ``diagonal'' matrices, which are of the following structures:
!>
!> If M-K-L >= 0,
!>
!>                     K  L
!>        D1 =     K ( I  0 )
!>                 L ( 0  C )
!>             M-K-L ( 0  0 )
!>
!>                   K  L
!>        D2 = L   ( 0  S )
!>             P-L ( 0  0 )
!>
!>                N-K-L  K    L
!>   ( 0 R ) = K (  0   R11  R12 ) K
!>             L (  0    0   R22 ) L
!>
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
!>   S = diag( BETA(K+1),  ... , BETA(K+L) ),
!>   C**2 + S**2 = I.
!>
!>   R is stored in A(1:K+L,N-K-L+1:N) on exit.
!>
!> If M-K-L < 0,
!>
!>                K M-K K+L-M
!>     D1 =   K ( I  0    0   )
!>          M-K ( 0  C    0   )
!>
!>                  K M-K K+L-M
!>     D2 =   M-K ( 0  S    0   )
!>          K+L-M ( 0  0    I   )
!>            P-L ( 0  0    0   )
!>
!>                N-K-L  K   M-K  K+L-M
!> ( 0 R ) =    K ( 0    R11  R12  R13  )
!>           M-K ( 0     0   R22  R23  )
!>         K+L-M ( 0     0    0   R33  )
!>
!> where
!> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
!> S = diag( BETA(K+1),  ... , BETA(M) ),
!> C**2 + S**2 = I.
!>
!> R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
!>     (  0  R22 R23 )
!> in B(M-K+1:L,N+M-K-L+1:N) on exit.
!>
!> The computation of the orthogonal transformation matrices U, V or Q
!> is optional.  These matrices may either be formed explicitly, or they
!> may be postmultiplied into input matrices U1, V1, or Q1.
!>

Parameters

JOBU 

!>          JOBU is CHARACTER*1
!>          = 'U':  U must contain an orthogonal matrix U1 on entry, and
!>                  the product U1*U is returned;
!>          = 'I':  U is initialized to the unit matrix, and the
!>                  orthogonal matrix U is returned;
!>          = 'N':  U is not computed.
!>

JOBV

!>          JOBV is CHARACTER*1
!>          = 'V':  V must contain an orthogonal matrix V1 on entry, and
!>                  the product V1*V is returned;
!>          = 'I':  V is initialized to the unit matrix, and the
!>                  orthogonal matrix V is returned;
!>          = 'N':  V is not computed.
!>

JOBQ

!>          JOBQ is CHARACTER*1
!>          = 'Q':  Q must contain an orthogonal matrix Q1 on entry, and
!>                  the product Q1*Q is returned;
!>          = 'I':  Q is initialized to the unit matrix, and the
!>                  orthogonal matrix Q is returned;
!>          = 'N':  Q is not computed.
!>

M

!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!>

P

!>          P is INTEGER
!>          The number of rows of the matrix B.  P >= 0.
!>

N

!>          N is INTEGER
!>          The number of columns of the matrices A and B.  N >= 0.
!>

K

!>          K is INTEGER
!>

L

!>          L is INTEGER
!>
!>          K and L specify the subblocks in the input matrices A and B:
!>          A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,N-L+1:N)
!>          of A and B, whose GSVD is going to be computed by DTGSJA.
!>          See Further Details.
!>

A

!>          A is DOUBLE PRECISION array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
!>          matrix R or part of R.  See Purpose for details.
!>

LDA

!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!>

B

!>          B is DOUBLE PRECISION array, dimension (LDB,N)
!>          On entry, the P-by-N matrix B.
!>          On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
!>          a part of R.  See Purpose for details.
!>

LDB

!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,P).
!>

TOLA

!>          TOLA is DOUBLE PRECISION
!>

TOLB

!>          TOLB is DOUBLE PRECISION
!>
!>          TOLA and TOLB are the convergence criteria for the Jacobi-
!>          Kogbetliantz iteration procedure. Generally, they are the
!>          same as used in the preprocessing step, say
!>              TOLA = max(M,N)*norm(A)*MAZHEPS,
!>              TOLB = max(P,N)*norm(B)*MAZHEPS.
!>

ALPHA

!>          ALPHA is DOUBLE PRECISION array, dimension (N)
!>

BETA

!>          BETA is DOUBLE PRECISION array, dimension (N)
!>
!>          On exit, ALPHA and BETA contain the generalized singular
!>          value pairs of A and B;
!>            ALPHA(1:K) = 1,
!>            BETA(1:K)  = 0,
!>          and if M-K-L >= 0,
!>            ALPHA(K+1:K+L) = diag(C),
!>            BETA(K+1:K+L)  = diag(S),
!>          or if M-K-L < 0,
!>            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
!>            BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
!>          Furthermore, if K+L < N,
!>            ALPHA(K+L+1:N) = 0 and
!>            BETA(K+L+1:N)  = 0.
!>

U

!>          U is DOUBLE PRECISION array, dimension (LDU,M)
!>          On entry, if JOBU = 'U', U must contain a matrix U1 (usually
!>          the orthogonal matrix returned by DGGSVP).
!>          On exit,
!>          if JOBU = 'I', U contains the orthogonal matrix U;
!>          if JOBU = 'U', U contains the product U1*U.
!>          If JOBU = 'N', U is not referenced.
!>

LDU

!>          LDU is INTEGER
!>          The leading dimension of the array U. LDU >= max(1,M) if
!>          JOBU = 'U'; LDU >= 1 otherwise.
!>

V

!>          V is DOUBLE PRECISION array, dimension (LDV,P)
!>          On entry, if JOBV = 'V', V must contain a matrix V1 (usually
!>          the orthogonal matrix returned by DGGSVP).
!>          On exit,
!>          if JOBV = 'I', V contains the orthogonal matrix V;
!>          if JOBV = 'V', V contains the product V1*V.
!>          If JOBV = 'N', V is not referenced.
!>

LDV

!>          LDV is INTEGER
!>          The leading dimension of the array V. LDV >= max(1,P) if
!>          JOBV = 'V'; LDV >= 1 otherwise.
!>

Q

!>          Q is DOUBLE PRECISION array, dimension (LDQ,N)
!>          On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
!>          the orthogonal matrix returned by DGGSVP).
!>          On exit,
!>          if JOBQ = 'I', Q contains the orthogonal matrix Q;
!>          if JOBQ = 'Q', Q contains the product Q1*Q.
!>          If JOBQ = 'N', Q is not referenced.
!>

LDQ

!>          LDQ is INTEGER
!>          The leading dimension of the array Q. LDQ >= max(1,N) if
!>          JOBQ = 'Q'; LDQ >= 1 otherwise.
!>

WORK

!>          WORK is DOUBLE PRECISION array, dimension (2*N)
!>

NCYCLE

!>          NCYCLE is INTEGER
!>          The number of cycles required for convergence.
!>

INFO

!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value.
!>          = 1:  the procedure does not converge after MAXIT cycles.
!> 

!>  Internal Parameters
!>  ===================
!>
!>  MAXIT   INTEGER
!>          MAXIT specifies the total loops that the iterative procedure
!>          may take. If after MAXIT cycles, the routine fails to
!>          converge, we return INFO = 1.
!> .fi


 
Author
Univ. of Tennessee 
Univ. of California Berkeley 
Univ. of Colorado Denver 
NAG Ltd. 
Further Details:




!>
!>  DTGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
!>  min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
!>  matrix B13 to the form:
!>
!>           U1**T *A13*Q1 = C1*R1; V1**T *B13*Q1 = S1*R1,
!>
!>  where U1, V1 and Q1 are orthogonal matrix, and Z**T is the transpose
!>  of Z.  C1 and S1 are diagonal matrices satisfying
!>
!>                C1**2 + S1**2 = I,
!>
!>  and R1 is an L-by-L nonsingular upper triangular matrix.
!> 




Definition at line 375 of file dtgsja.f.






subroutine STGSJA (character jobu, character jobv, character jobq, integer m, integer p, integer n, integer k, integer l, real, dimension( lda, * ) a, integer lda, real, dimension( ldb, * ) b, integer ldb, real tola, real tolb, real, dimension( * ) alpha, real, dimension( * ) beta, real, dimension( ldu, * ) u, integer ldu, real, dimension( ldv, * ) v, integer ldv, real, dimension( ldq, * ) q, integer ldq, real, dimension( * ) work, integer ncycle, integer info)


STGSJA


Purpose:








!>
!> STGSJA computes the generalized singular value decomposition (GSVD)
!> of two real upper triangular (or trapezoidal) matrices A and B.
!>
!> On entry, it is assumed that matrices A and B have the following
!> forms, which may be obtained by the preprocessing subroutine SGGSVP
!> from a general M-by-N matrix A and P-by-N matrix B:
!>
!>              N-K-L  K    L
!>    A =    K ( 0    A12  A13 ) if M-K-L >= 0;
!>           L ( 0     0   A23 )
!>       M-K-L ( 0     0    0  )
!>
!>            N-K-L  K    L
!>    A =  K ( 0    A12  A13 ) if M-K-L < 0;
!>       M-K ( 0     0   A23 )
!>
!>            N-K-L  K    L
!>    B =  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.
!>
!> On exit,
!>
!>        U**T *A*Q = D1*( 0 R ),    V**T *B*Q = D2*( 0 R ),
!>
!> where U, V and Q are orthogonal matrices.
!> R is a nonsingular upper triangular matrix, and D1 and D2 are
!> ``diagonal'' matrices, which are of the following structures:
!>
!> If M-K-L >= 0,
!>
!>                     K  L
!>        D1 =     K ( I  0 )
!>                 L ( 0  C )
!>             M-K-L ( 0  0 )
!>
!>                   K  L
!>        D2 = L   ( 0  S )
!>             P-L ( 0  0 )
!>
!>                N-K-L  K    L
!>   ( 0 R ) = K (  0   R11  R12 ) K
!>             L (  0    0   R22 ) L
!>
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
!>   S = diag( BETA(K+1),  ... , BETA(K+L) ),
!>   C**2 + S**2 = I.
!>
!>   R is stored in A(1:K+L,N-K-L+1:N) on exit.
!>
!> If M-K-L < 0,
!>
!>                K M-K K+L-M
!>     D1 =   K ( I  0    0   )
!>          M-K ( 0  C    0   )
!>
!>                  K M-K K+L-M
!>     D2 =   M-K ( 0  S    0   )
!>          K+L-M ( 0  0    I   )
!>            P-L ( 0  0    0   )
!>
!>                N-K-L  K   M-K  K+L-M
!> ( 0 R ) =    K ( 0    R11  R12  R13  )
!>           M-K ( 0     0   R22  R23  )
!>         K+L-M ( 0     0    0   R33  )
!>
!> where
!> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
!> S = diag( BETA(K+1),  ... , BETA(M) ),
!> C**2 + S**2 = I.
!>
!> R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
!>     (  0  R22 R23 )
!> in B(M-K+1:L,N+M-K-L+1:N) on exit.
!>
!> The computation of the orthogonal transformation matrices U, V or Q
!> is optional.  These matrices may either be formed explicitly, or they
!> may be postmultiplied into input matrices U1, V1, or Q1.
!> 




Parameters


JOBU



!>          JOBU is CHARACTER*1
!>          = 'U':  U must contain an orthogonal matrix U1 on entry, and
!>                  the product U1*U is returned;
!>          = 'I':  U is initialized to the unit matrix, and the
!>                  orthogonal matrix U is returned;
!>          = 'N':  U is not computed.
!> 


JOBV




!>          JOBV is CHARACTER*1
!>          = 'V':  V must contain an orthogonal matrix V1 on entry, and
!>                  the product V1*V is returned;
!>          = 'I':  V is initialized to the unit matrix, and the
!>                  orthogonal matrix V is returned;
!>          = 'N':  V is not computed.
!> 


JOBQ




!>          JOBQ is CHARACTER*1
!>          = 'Q':  Q must contain an orthogonal matrix Q1 on entry, and
!>                  the product Q1*Q is returned;
!>          = 'I':  Q is initialized to the unit matrix, and the
!>                  orthogonal matrix Q is returned;
!>          = 'N':  Q is not computed.
!> 


M




!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!> 


P




!>          P is INTEGER
!>          The number of rows of the matrix B.  P >= 0.
!> 


N




!>          N is INTEGER
!>          The number of columns of the matrices A and B.  N >= 0.
!> 


K




!>          K is INTEGER
!> 


L




!>          L is INTEGER
!>
!>          K and L specify the subblocks in the input matrices A and B:
!>          A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,N-L+1:N)
!>          of A and B, whose GSVD is going to be computed by STGSJA.
!>          See Further Details.
!> 


A




!>          A is REAL array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
!>          matrix R or part of R.  See Purpose for details.
!> 


LDA




!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!> 


B




!>          B is REAL array, dimension (LDB,N)
!>          On entry, the P-by-N matrix B.
!>          On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
!>          a part of R.  See Purpose for details.
!> 


LDB




!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,P).
!> 


TOLA




!>          TOLA is REAL
!> 


TOLB




!>          TOLB is REAL
!>
!>          TOLA and TOLB are the convergence criteria for the Jacobi-
!>          Kogbetliantz iteration procedure. Generally, they are the
!>          same as used in the preprocessing step, say
!>              TOLA = max(M,N)*norm(A)*MACHEPS,
!>              TOLB = max(P,N)*norm(B)*MACHEPS.
!> 


ALPHA




!>          ALPHA is REAL array, dimension (N)
!> 


BETA




!>          BETA is REAL array, dimension (N)
!>
!>          On exit, ALPHA and BETA contain the generalized singular
!>          value pairs of A and B;
!>            ALPHA(1:K) = 1,
!>            BETA(1:K)  = 0,
!>          and if M-K-L >= 0,
!>            ALPHA(K+1:K+L) = diag(C),
!>            BETA(K+1:K+L)  = diag(S),
!>          or if M-K-L < 0,
!>            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
!>            BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
!>          Furthermore, if K+L < N,
!>            ALPHA(K+L+1:N) = 0 and
!>            BETA(K+L+1:N)  = 0.
!> 


U




!>          U is REAL array, dimension (LDU,M)
!>          On entry, if JOBU = 'U', U must contain a matrix U1 (usually
!>          the orthogonal matrix returned by SGGSVP).
!>          On exit,
!>          if JOBU = 'I', U contains the orthogonal matrix U;
!>          if JOBU = 'U', U contains the product U1*U.
!>          If JOBU = 'N', U is not referenced.
!> 


LDU




!>          LDU is INTEGER
!>          The leading dimension of the array U. LDU >= max(1,M) if
!>          JOBU = 'U'; LDU >= 1 otherwise.
!> 


V




!>          V is REAL array, dimension (LDV,P)
!>          On entry, if JOBV = 'V', V must contain a matrix V1 (usually
!>          the orthogonal matrix returned by SGGSVP).
!>          On exit,
!>          if JOBV = 'I', V contains the orthogonal matrix V;
!>          if JOBV = 'V', V contains the product V1*V.
!>          If JOBV = 'N', V is not referenced.
!> 


LDV




!>          LDV is INTEGER
!>          The leading dimension of the array V. LDV >= max(1,P) if
!>          JOBV = 'V'; LDV >= 1 otherwise.
!> 


Q




!>          Q is REAL array, dimension (LDQ,N)
!>          On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
!>          the orthogonal matrix returned by SGGSVP).
!>          On exit,
!>          if JOBQ = 'I', Q contains the orthogonal matrix Q;
!>          if JOBQ = 'Q', Q contains the product Q1*Q.
!>          If JOBQ = 'N', Q is not referenced.
!> 


LDQ




!>          LDQ is INTEGER
!>          The leading dimension of the array Q. LDQ >= max(1,N) if
!>          JOBQ = 'Q'; LDQ >= 1 otherwise.
!> 


WORK




!>          WORK is REAL array, dimension (2*N)
!> 


NCYCLE




!>          NCYCLE is INTEGER
!>          The number of cycles required for convergence.
!> 


INFO




!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value.
!>          = 1:  the procedure does not converge after MAXIT cycles.
!> 






!>  Internal Parameters
!>  ===================
!>
!>  MAXIT   INTEGER
!>          MAXIT specifies the total loops that the iterative procedure
!>          may take. If after MAXIT cycles, the routine fails to
!>          converge, we return INFO = 1.
!> .fi




 


Author




Univ. of Tennessee 


Univ. of California Berkeley 


Univ. of Colorado Denver 


NAG Ltd. 




Further Details:








!>
!>  STGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
!>  min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
!>  matrix B13 to the form:
!>
!>           U1**T *A13*Q1 = C1*R1; V1**T *B13*Q1 = S1*R1,
!>
!>  where U1, V1 and Q1 are orthogonal matrix, and Z**T is the transpose
!>  of Z.  C1 and S1 are diagonal matrices satisfying
!>
!>                C1**2 + S1**2 = I,
!>
!>  and R1 is an L-by-L nonsingular upper triangular matrix.
!> 




Definition at line 375 of file stgsja.f.






subroutine ZTGSJA (character jobu, character jobv, character jobq, integer m, integer p, integer n, integer k, integer l, complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension( ldb, * ) b, integer ldb, double precision tola, double precision tolb, double precision, dimension( * ) alpha, double precision, dimension( * ) beta, complex*16, dimension( ldu, * ) u, integer ldu, complex*16, dimension( ldv, * ) v, integer ldv, complex*16, dimension( ldq, * ) q, integer ldq, complex*16, dimension( * ) work, integer ncycle, integer info)


ZTGSJA


Purpose:








!>
!> ZTGSJA computes the generalized singular value decomposition (GSVD)
!> of two complex upper triangular (or trapezoidal) matrices A and B.
!>
!> On entry, it is assumed that matrices A and B have the following
!> forms, which may be obtained by the preprocessing subroutine ZGGSVP
!> from a general M-by-N matrix A and P-by-N matrix B:
!>
!>              N-K-L  K    L
!>    A =    K ( 0    A12  A13 ) if M-K-L >= 0;
!>           L ( 0     0   A23 )
!>       M-K-L ( 0     0    0  )
!>
!>            N-K-L  K    L
!>    A =  K ( 0    A12  A13 ) if M-K-L < 0;
!>       M-K ( 0     0   A23 )
!>
!>            N-K-L  K    L
!>    B =  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.
!>
!> On exit,
!>
!>        U**H *A*Q = D1*( 0 R ),    V**H *B*Q = D2*( 0 R ),
!>
!> where U, V and Q are unitary matrices.
!> R is a nonsingular upper triangular matrix, and D1
!> and D2 are ``diagonal'' matrices, which are of the following
!> structures:
!>
!> If M-K-L >= 0,
!>
!>                     K  L
!>        D1 =     K ( I  0 )
!>                 L ( 0  C )
!>             M-K-L ( 0  0 )
!>
!>                    K  L
!>        D2 = L   ( 0  S )
!>             P-L ( 0  0 )
!>
!>                N-K-L  K    L
!>   ( 0 R ) = K (  0   R11  R12 ) K
!>             L (  0    0   R22 ) L
!>
!> where
!>
!>   C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
!>   S = diag( BETA(K+1),  ... , BETA(K+L) ),
!>   C**2 + S**2 = I.
!>
!>   R is stored in A(1:K+L,N-K-L+1:N) on exit.
!>
!> If M-K-L < 0,
!>
!>                K M-K K+L-M
!>     D1 =   K ( I  0    0   )
!>          M-K ( 0  C    0   )
!>
!>                  K M-K K+L-M
!>     D2 =   M-K ( 0  S    0   )
!>          K+L-M ( 0  0    I   )
!>            P-L ( 0  0    0   )
!>
!>                N-K-L  K   M-K  K+L-M
!> ( 0 R ) =    K ( 0    R11  R12  R13  )
!>           M-K ( 0     0   R22  R23  )
!>         K+L-M ( 0     0    0   R33  )
!>
!> where
!> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
!> S = diag( BETA(K+1),  ... , BETA(M) ),
!> C**2 + S**2 = I.
!>
!> R = ( R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N) and R33 is stored
!>     (  0  R22 R23 )
!> in B(M-K+1:L,N+M-K-L+1:N) on exit.
!>
!> The computation of the unitary transformation matrices U, V or Q
!> is optional.  These matrices may either be formed explicitly, or they
!> may be postmultiplied into input matrices U1, V1, or Q1.
!> 




Parameters


JOBU



!>          JOBU is CHARACTER*1
!>          = 'U':  U must contain a unitary matrix U1 on entry, and
!>                  the product U1*U is returned;
!>          = 'I':  U is initialized to the unit matrix, and the
!>                  unitary matrix U is returned;
!>          = 'N':  U is not computed.
!> 


JOBV




!>          JOBV is CHARACTER*1
!>          = 'V':  V must contain a unitary matrix V1 on entry, and
!>                  the product V1*V is returned;
!>          = 'I':  V is initialized to the unit matrix, and the
!>                  unitary matrix V is returned;
!>          = 'N':  V is not computed.
!> 


JOBQ




!>          JOBQ is CHARACTER*1
!>          = 'Q':  Q must contain a unitary matrix Q1 on entry, and
!>                  the product Q1*Q is returned;
!>          = 'I':  Q is initialized to the unit matrix, and the
!>                  unitary matrix Q is returned;
!>          = 'N':  Q is not computed.
!> 


M




!>          M is INTEGER
!>          The number of rows of the matrix A.  M >= 0.
!> 


P




!>          P is INTEGER
!>          The number of rows of the matrix B.  P >= 0.
!> 


N




!>          N is INTEGER
!>          The number of columns of the matrices A and B.  N >= 0.
!> 


K




!>          K is INTEGER
!> 


L




!>          L is INTEGER
!>
!>          K and L specify the subblocks in the input matrices A and B:
!>          A23 = A(K+1:MIN(K+L,M),N-L+1:N) and B13 = B(1:L,,N-L+1:N)
!>          of A and B, whose GSVD is going to be computed by ZTGSJA.
!>          See Further Details.
!> 


A




!>          A is COMPLEX*16 array, dimension (LDA,N)
!>          On entry, the M-by-N matrix A.
!>          On exit, A(N-K+1:N,1:MIN(K+L,M) ) contains the triangular
!>          matrix R or part of R.  See Purpose for details.
!> 


LDA




!>          LDA is INTEGER
!>          The leading dimension of the array A. LDA >= max(1,M).
!> 


B




!>          B is COMPLEX*16 array, dimension (LDB,N)
!>          On entry, the P-by-N matrix B.
!>          On exit, if necessary, B(M-K+1:L,N+M-K-L+1:N) contains
!>          a part of R.  See Purpose for details.
!> 


LDB




!>          LDB is INTEGER
!>          The leading dimension of the array B. LDB >= max(1,P).
!> 


TOLA




!>          TOLA is DOUBLE PRECISION
!> 


TOLB




!>          TOLB is DOUBLE PRECISION
!>
!>          TOLA and TOLB are the convergence criteria for the Jacobi-
!>          Kogbetliantz iteration procedure. Generally, they are the
!>          same as used in the preprocessing step, say
!>              TOLA = MAX(M,N)*norm(A)*MAZHEPS,
!>              TOLB = MAX(P,N)*norm(B)*MAZHEPS.
!> 


ALPHA




!>          ALPHA is DOUBLE PRECISION array, dimension (N)
!> 


BETA




!>          BETA is DOUBLE PRECISION array, dimension (N)
!>
!>          On exit, ALPHA and BETA contain the generalized singular
!>          value pairs of A and B;
!>            ALPHA(1:K) = 1,
!>            BETA(1:K)  = 0,
!>          and if M-K-L >= 0,
!>            ALPHA(K+1:K+L) = diag(C),
!>            BETA(K+1:K+L)  = diag(S),
!>          or if M-K-L < 0,
!>            ALPHA(K+1:M)= C, ALPHA(M+1:K+L)= 0
!>            BETA(K+1:M) = S, BETA(M+1:K+L) = 1.
!>          Furthermore, if K+L < N,
!>            ALPHA(K+L+1:N) = 0 and
!>            BETA(K+L+1:N)  = 0.
!> 


U




!>          U is COMPLEX*16 array, dimension (LDU,M)
!>          On entry, if JOBU = 'U', U must contain a matrix U1 (usually
!>          the unitary matrix returned by ZGGSVP).
!>          On exit,
!>          if JOBU = 'I', U contains the unitary matrix U;
!>          if JOBU = 'U', U contains the product U1*U.
!>          If JOBU = 'N', U is not referenced.
!> 


LDU




!>          LDU is INTEGER
!>          The leading dimension of the array U. LDU >= max(1,M) if
!>          JOBU = 'U'; LDU >= 1 otherwise.
!> 


V




!>          V is COMPLEX*16 array, dimension (LDV,P)
!>          On entry, if JOBV = 'V', V must contain a matrix V1 (usually
!>          the unitary matrix returned by ZGGSVP).
!>          On exit,
!>          if JOBV = 'I', V contains the unitary matrix V;
!>          if JOBV = 'V', V contains the product V1*V.
!>          If JOBV = 'N', V is not referenced.
!> 


LDV




!>          LDV is INTEGER
!>          The leading dimension of the array V. LDV >= max(1,P) if
!>          JOBV = 'V'; LDV >= 1 otherwise.
!> 


Q




!>          Q is COMPLEX*16 array, dimension (LDQ,N)
!>          On entry, if JOBQ = 'Q', Q must contain a matrix Q1 (usually
!>          the unitary matrix returned by ZGGSVP).
!>          On exit,
!>          if JOBQ = 'I', Q contains the unitary matrix Q;
!>          if JOBQ = 'Q', Q contains the product Q1*Q.
!>          If JOBQ = 'N', Q is not referenced.
!> 


LDQ




!>          LDQ is INTEGER
!>          The leading dimension of the array Q. LDQ >= max(1,N) if
!>          JOBQ = 'Q'; LDQ >= 1 otherwise.
!> 


WORK




!>          WORK is COMPLEX*16 array, dimension (2*N)
!> 


NCYCLE




!>          NCYCLE is INTEGER
!>          The number of cycles required for convergence.
!> 


INFO




!>          INFO is INTEGER
!>          = 0:  successful exit
!>          < 0:  if INFO = -i, the i-th argument had an illegal value.
!>          = 1:  the procedure does not converge after MAXIT cycles.
!> 




Internal Parameters:








!>  MAXIT   INTEGER
!>          MAXIT specifies the total loops that the iterative procedure
!>          may take. If after MAXIT cycles, the routine fails to
!>          converge, we return INFO = 1.
!> 




Author


Univ. of Tennessee

Univ. of California Berkeley


Univ. of Colorado Denver


NAG Ltd.




Further Details:








!>
!>  ZTGSJA essentially uses a variant of Kogbetliantz algorithm to reduce
!>  min(L,M-K)-by-L triangular (or trapezoidal) matrix A23 and L-by-L
!>  matrix B13 to the form:
!>
!>           U1**H *A13*Q1 = C1*R1; V1**H *B13*Q1 = S1*R1,
!>
!>  where U1, V1 and Q1 are unitary matrix.
!>  C1 and S1 are diagonal matrices satisfying
!>
!>                C1**2 + S1**2 = I,
!>
!>  and R1 is an L-by-L nonsingular upper triangular matrix.
!> 




Definition at line 376 of file ztgsja.f.








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