LAPACK  3.6.1
LAPACK: Linear Algebra PACKage
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

Download CTGSJA + dependencies [TGZ] [ZIP] [TXT]

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
[in]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.
[in]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.
[in]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.
[in]M
          M is INTEGER
          The number of rows of the matrix A.  M >= 0.
[in]P
          P is INTEGER
          The number of rows of the matrix B.  P >= 0.
[in]N
          N is INTEGER
          The number of columns of the matrices A and B.  N >= 0.
[in]K
          K is INTEGER
[in]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.
[in,out]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.
[in]LDA
          LDA is INTEGER
          The leading dimension of the array A. LDA >= max(1,M).
[in,out]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.
[in]LDB
          LDB is INTEGER
          The leading dimension of the array B. LDB >= max(1,P).
[in]TOLA
          TOLA is REAL
[in]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.
[out]ALPHA
          ALPHA is REAL array, dimension (N)
[out]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.
[in,out]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.
[in]LDU
          LDU is INTEGER
          The leading dimension of the array U. LDU >= max(1,M) if
          JOBU = 'U'; LDU >= 1 otherwise.
[in,out]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.
[in]LDV
          LDV is INTEGER
          The leading dimension of the array V. LDV >= max(1,P) if
          JOBV = 'V'; LDV >= 1 otherwise.
[in,out]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.
[in]LDQ
          LDQ is INTEGER
          The leading dimension of the array Q. LDQ >= max(1,N) if
          JOBQ = 'Q'; LDQ >= 1 otherwise.
[out]WORK
          WORK is COMPLEX array, dimension (2*N)
[out]NCYCLE
          NCYCLE is INTEGER
          The number of cycles required for convergence.
[out]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.
Date
November 2011
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 381 of file ctgsja.f.

381 *
382 * -- LAPACK computational routine (version 3.4.0) --
383 * -- LAPACK is a software package provided by Univ. of Tennessee, --
384 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
385 * November 2011
386 *
387 * .. Scalar Arguments ..
388  CHARACTER jobq, jobu, jobv
389  INTEGER info, k, l, lda, ldb, ldq, ldu, ldv, m, n,
390  $ ncycle, p
391  REAL tola, tolb
392 * ..
393 * .. Array Arguments ..
394  REAL alpha( * ), beta( * )
395  COMPLEX a( lda, * ), b( ldb, * ), q( ldq, * ),
396  $ u( ldu, * ), v( ldv, * ), work( * )
397 * ..
398 *
399 * =====================================================================
400 *
401 * .. Parameters ..
402  INTEGER maxit
403  parameter ( maxit = 40 )
404  REAL zero, one
405  parameter ( zero = 0.0e+0, one = 1.0e+0 )
406  COMPLEX czero, cone
407  parameter ( czero = ( 0.0e+0, 0.0e+0 ),
408  $ cone = ( 1.0e+0, 0.0e+0 ) )
409 * ..
410 * .. Local Scalars ..
411 *
412  LOGICAL initq, initu, initv, upper, wantq, wantu, wantv
413  INTEGER i, j, kcycle
414  REAL a1, a3, b1, b3, csq, csu, csv, error, gamma,
415  $ rwk, ssmin
416  COMPLEX a2, b2, snq, snu, snv
417 * ..
418 * .. External Functions ..
419  LOGICAL lsame
420  EXTERNAL lsame
421 * ..
422 * .. External Subroutines ..
423  EXTERNAL ccopy, clags2, clapll, claset, crot, csscal,
424  $ slartg, xerbla
425 * ..
426 * .. Intrinsic Functions ..
427  INTRINSIC abs, conjg, max, min, real
428 * ..
429 * .. Executable Statements ..
430 *
431 * Decode and test the input parameters
432 *
433  initu = lsame( jobu, 'I' )
434  wantu = initu .OR. lsame( jobu, 'U' )
435 *
436  initv = lsame( jobv, 'I' )
437  wantv = initv .OR. lsame( jobv, 'V' )
438 *
439  initq = lsame( jobq, 'I' )
440  wantq = initq .OR. lsame( jobq, 'Q' )
441 *
442  info = 0
443  IF( .NOT.( initu .OR. wantu .OR. lsame( jobu, 'N' ) ) ) THEN
444  info = -1
445  ELSE IF( .NOT.( initv .OR. wantv .OR. lsame( jobv, 'N' ) ) ) THEN
446  info = -2
447  ELSE IF( .NOT.( initq .OR. wantq .OR. lsame( jobq, 'N' ) ) ) THEN
448  info = -3
449  ELSE IF( m.LT.0 ) THEN
450  info = -4
451  ELSE IF( p.LT.0 ) THEN
452  info = -5
453  ELSE IF( n.LT.0 ) THEN
454  info = -6
455  ELSE IF( lda.LT.max( 1, m ) ) THEN
456  info = -10
457  ELSE IF( ldb.LT.max( 1, p ) ) THEN
458  info = -12
459  ELSE IF( ldu.LT.1 .OR. ( wantu .AND. ldu.LT.m ) ) THEN
460  info = -18
461  ELSE IF( ldv.LT.1 .OR. ( wantv .AND. ldv.LT.p ) ) THEN
462  info = -20
463  ELSE IF( ldq.LT.1 .OR. ( wantq .AND. ldq.LT.n ) ) THEN
464  info = -22
465  END IF
466  IF( info.NE.0 ) THEN
467  CALL xerbla( 'CTGSJA', -info )
468  RETURN
469  END IF
470 *
471 * Initialize U, V and Q, if necessary
472 *
473  IF( initu )
474  $ CALL claset( 'Full', m, m, czero, cone, u, ldu )
475  IF( initv )
476  $ CALL claset( 'Full', p, p, czero, cone, v, ldv )
477  IF( initq )
478  $ CALL claset( 'Full', n, n, czero, cone, q, ldq )
479 *
480 * Loop until convergence
481 *
482  upper = .false.
483  DO 40 kcycle = 1, maxit
484 *
485  upper = .NOT.upper
486 *
487  DO 20 i = 1, l - 1
488  DO 10 j = i + 1, l
489 *
490  a1 = zero
491  a2 = czero
492  a3 = zero
493  IF( k+i.LE.m )
494  $ a1 = REAL( A( K+I, N-L+I ) )
495  IF( k+j.LE.m )
496  $ a3 = REAL( A( K+J, N-L+J ) )
497 *
498  b1 = REAL( B( I, N-L+I ) )
499  b3 = REAL( B( J, N-L+J ) )
500 *
501  IF( upper ) THEN
502  IF( k+i.LE.m )
503  $ a2 = a( k+i, n-l+j )
504  b2 = b( i, n-l+j )
505  ELSE
506  IF( k+j.LE.m )
507  $ a2 = a( k+j, n-l+i )
508  b2 = b( j, n-l+i )
509  END IF
510 *
511  CALL clags2( upper, a1, a2, a3, b1, b2, b3, csu, snu,
512  $ csv, snv, csq, snq )
513 *
514 * Update (K+I)-th and (K+J)-th rows of matrix A: U**H *A
515 *
516  IF( k+j.LE.m )
517  $ CALL crot( l, a( k+j, n-l+1 ), lda, a( k+i, n-l+1 ),
518  $ lda, csu, conjg( snu ) )
519 *
520 * Update I-th and J-th rows of matrix B: V**H *B
521 *
522  CALL crot( l, b( j, n-l+1 ), ldb, b( i, n-l+1 ), ldb,
523  $ csv, conjg( snv ) )
524 *
525 * Update (N-L+I)-th and (N-L+J)-th columns of matrices
526 * A and B: A*Q and B*Q
527 *
528  CALL crot( min( k+l, m ), a( 1, n-l+j ), 1,
529  $ a( 1, n-l+i ), 1, csq, snq )
530 *
531  CALL crot( l, b( 1, n-l+j ), 1, b( 1, n-l+i ), 1, csq,
532  $ snq )
533 *
534  IF( upper ) THEN
535  IF( k+i.LE.m )
536  $ a( k+i, n-l+j ) = czero
537  b( i, n-l+j ) = czero
538  ELSE
539  IF( k+j.LE.m )
540  $ a( k+j, n-l+i ) = czero
541  b( j, n-l+i ) = czero
542  END IF
543 *
544 * Ensure that the diagonal elements of A and B are real.
545 *
546  IF( k+i.LE.m )
547  $ a( k+i, n-l+i ) = REAL( A( K+I, N-L+I ) )
548  IF( k+j.LE.m )
549  $ a( k+j, n-l+j ) = REAL( A( K+J, N-L+J ) )
550  b( i, n-l+i ) = REAL( B( I, N-L+I ) )
551  b( j, n-l+j ) = REAL( B( J, N-L+J ) )
552 *
553 * Update unitary matrices U, V, Q, if desired.
554 *
555  IF( wantu .AND. k+j.LE.m )
556  $ CALL crot( m, u( 1, k+j ), 1, u( 1, k+i ), 1, csu,
557  $ snu )
558 *
559  IF( wantv )
560  $ CALL crot( p, v( 1, j ), 1, v( 1, i ), 1, csv, snv )
561 *
562  IF( wantq )
563  $ CALL crot( n, q( 1, n-l+j ), 1, q( 1, n-l+i ), 1, csq,
564  $ snq )
565 *
566  10 CONTINUE
567  20 CONTINUE
568 *
569  IF( .NOT.upper ) THEN
570 *
571 * The matrices A13 and B13 were lower triangular at the start
572 * of the cycle, and are now upper triangular.
573 *
574 * Convergence test: test the parallelism of the corresponding
575 * rows of A and B.
576 *
577  error = zero
578  DO 30 i = 1, min( l, m-k )
579  CALL ccopy( l-i+1, a( k+i, n-l+i ), lda, work, 1 )
580  CALL ccopy( l-i+1, b( i, n-l+i ), ldb, work( l+1 ), 1 )
581  CALL clapll( l-i+1, work, 1, work( l+1 ), 1, ssmin )
582  error = max( error, ssmin )
583  30 CONTINUE
584 *
585  IF( abs( error ).LE.min( tola, tolb ) )
586  $ GO TO 50
587  END IF
588 *
589 * End of cycle loop
590 *
591  40 CONTINUE
592 *
593 * The algorithm has not converged after MAXIT cycles.
594 *
595  info = 1
596  GO TO 100
597 *
598  50 CONTINUE
599 *
600 * If ERROR <= MIN(TOLA,TOLB), then the algorithm has converged.
601 * Compute the generalized singular value pairs (ALPHA, BETA), and
602 * set the triangular matrix R to array A.
603 *
604  DO 60 i = 1, k
605  alpha( i ) = one
606  beta( i ) = zero
607  60 CONTINUE
608 *
609  DO 70 i = 1, min( l, m-k )
610 *
611  a1 = REAL( A( K+I, N-L+I ) )
612  b1 = REAL( B( I, N-L+I ) )
613 *
614  IF( a1.NE.zero ) THEN
615  gamma = b1 / a1
616 *
617  IF( gamma.LT.zero ) THEN
618  CALL csscal( l-i+1, -one, b( i, n-l+i ), ldb )
619  IF( wantv )
620  $ CALL csscal( p, -one, v( 1, i ), 1 )
621  END IF
622 *
623  CALL slartg( abs( gamma ), one, beta( k+i ), alpha( k+i ),
624  $ rwk )
625 *
626  IF( alpha( k+i ).GE.beta( k+i ) ) THEN
627  CALL csscal( l-i+1, one / alpha( k+i ), a( k+i, n-l+i ),
628  $ lda )
629  ELSE
630  CALL csscal( l-i+1, one / beta( k+i ), b( i, n-l+i ),
631  $ ldb )
632  CALL ccopy( l-i+1, b( i, n-l+i ), ldb, a( k+i, n-l+i ),
633  $ lda )
634  END IF
635 *
636  ELSE
637  alpha( k+i ) = zero
638  beta( k+i ) = one
639  CALL ccopy( l-i+1, b( i, n-l+i ), ldb, a( k+i, n-l+i ),
640  $ lda )
641  END IF
642  70 CONTINUE
643 *
644 * Post-assignment
645 *
646  DO 80 i = m + 1, k + l
647  alpha( i ) = zero
648  beta( i ) = one
649  80 CONTINUE
650 *
651  IF( k+l.LT.n ) THEN
652  DO 90 i = k + l + 1, n
653  alpha( i ) = zero
654  beta( i ) = zero
655  90 CONTINUE
656  END IF
657 *
658  100 CONTINUE
659  ncycle = kcycle
660 *
661  RETURN
662 *
663 * End of CTGSJA
664 *
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:62
subroutine slartg(F, G, CS, SN, R)
SLARTG generates a plane rotation with real cosine and real sine.
Definition: slartg.f:99
subroutine claset(UPLO, M, N, ALPHA, BETA, A, LDA)
CLASET initializes the off-diagonal elements and the diagonal elements of a matrix to given values...
Definition: claset.f:108
subroutine clapll(N, X, INCX, Y, INCY, SSMIN)
CLAPLL measures the linear dependence of two vectors.
Definition: clapll.f:102
subroutine ccopy(N, CX, INCX, CY, INCY)
CCOPY
Definition: ccopy.f:52
subroutine clags2(UPPER, A1, A2, A3, B1, B2, B3, CSU, SNU, CSV, SNV, CSQ, SNQ)
CLAGS2
Definition: clags2.f:160
logical function lsame(CA, CB)
LSAME
Definition: lsame.f:55
subroutine csscal(N, SA, CX, INCX)
CSSCAL
Definition: csscal.f:54
subroutine crot(N, CX, INCX, CY, INCY, C, S)
CROT applies a plane rotation with real cosine and complex sine to a pair of complex vectors...
Definition: crot.f:105

Here is the call graph for this function:

Here is the caller graph for this function: