zbdsqr.f

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      SUBROUTINE ZBDSQR( UPLO, N, NCVT, NRU, NCC, D, E, VT, LDVT, U,
     $                   LDU, C, LDC, RWORK, INFO )
*
*  -- LAPACK routine (instrumented to count operations, version 3.0) --
*     Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
*     Courant Institute, Argonne National Lab, and Rice University
*     October 31, 1999
*
*     .. Scalar Arguments ..
      CHARACTER          UPLO
      INTEGER            INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU
*     ..
*     .. Array Arguments ..
      DOUBLE PRECISION   D( * ), E( * ), RWORK( * )
      COMPLEX*16         C( LDC, * ), U( LDU, * ), VT( LDVT, * )
*     ..
*     Common block to return operation count and iteration count
*     ITCNT is initialized to 0, OPS is only incremented
*     .. Common blocks ..
      COMMON             / LATIME / OPS, ITCNT
*     ..
*     .. Scalars in Common ..
      DOUBLE PRECISION   ITCNT, OPS
*     ..
*
*  Purpose
*  =======
*
*  ZBDSQR computes the singular value decomposition (SVD) of a real
*  N-by-N (upper or lower) bidiagonal matrix B:  B = Q * S * P' (P'
*  denotes the transpose of P), where S is a diagonal matrix with
*  non-negative diagonal elements (the singular values of B), and Q
*  and P are orthogonal matrices.
*
*  The routine computes S, and optionally computes U * Q, P' * VT,
*  or Q' * C, for given complex input matrices U, VT, and C.
*
*  See "Computing  Small Singular Values of Bidiagonal Matrices With
*  Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan,
*  LAPACK Working Note #3 (or SIAM J. Sci. Statist. Comput. vol. 11,
*  no. 5, pp. 873-912, Sept 1990) and
*  "Accurate singular values and differential qd algorithms," by
*  B. Parlett and V. Fernando, Technical Report CPAM-554, Mathematics
*  Department, University of California at Berkeley, July 1992
*  for a detailed description of the algorithm.
*
*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  B is upper bidiagonal;
*          = 'L':  B is lower bidiagonal.
*
*  N       (input) INTEGER
*          The order of the matrix B.  N >= 0.
*
*  NCVT    (input) INTEGER
*          The number of columns of the matrix VT. NCVT >= 0.
*
*  NRU     (input) INTEGER
*          The number of rows of the matrix U. NRU >= 0.
*
*  NCC     (input) INTEGER
*          The number of columns of the matrix C. NCC >= 0.
*
*  D       (input/output) DOUBLE PRECISION array, dimension (N)
*          On entry, the n diagonal elements of the bidiagonal matrix B.
*          On exit, if INFO=0, the singular values of B in decreasing
*          order.
*
*  E       (input/output) DOUBLE PRECISION array, dimension (N)
*          On entry, the elements of E contain the
*          offdiagonal elements of of the bidiagonal matrix whose SVD
*          is desired. On normal exit (INFO = 0), E is destroyed.
*          If the algorithm does not converge (INFO > 0), D and E
*          will contain the diagonal and superdiagonal elements of a
*          bidiagonal matrix orthogonally equivalent to the one given
*          as input. E(N) is used for workspace.
*
*  VT      (input/output) COMPLEX*16 array, dimension (LDVT, NCVT)
*          On entry, an N-by-NCVT matrix VT.
*          On exit, VT is overwritten by P' * VT.
*          VT is not referenced if NCVT = 0.
*
*  LDVT    (input) INTEGER
*          The leading dimension of the array VT.
*          LDVT >= max(1,N) if NCVT > 0; LDVT >= 1 if NCVT = 0.
*
*  U       (input/output) COMPLEX*16 array, dimension (LDU, N)
*          On entry, an NRU-by-N matrix U.
*          On exit, U is overwritten by U * Q.
*          U is not referenced if NRU = 0.
*
*  LDU     (input) INTEGER
*          The leading dimension of the array U.  LDU >= max(1,NRU).
*
*  C       (input/output) COMPLEX*16 array, dimension (LDC, NCC)
*          On entry, an N-by-NCC matrix C.
*          On exit, C is overwritten by Q' * C.
*          C is not referenced if NCC = 0.
*
*  LDC     (input) INTEGER
*          The leading dimension of the array C.
*          LDC >= max(1,N) if NCC > 0; LDC >=1 if NCC = 0.
*
*  RWORK   (workspace) DOUBLE PRECISION array, dimension (4*N)
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  If INFO = -i, the i-th argument had an illegal value
*          > 0:  the algorithm did not converge; D and E contain the
*                elements of a bidiagonal matrix which is orthogonally
*                similar to the input matrix B;  if INFO = i, i
*                elements of E have not converged to zero.
*
*  Internal Parameters
*  ===================
*
*  TOLMUL  DOUBLE PRECISION, default = max(10,min(100,EPS**(-1/8)))
*          TOLMUL controls the convergence criterion of the QR loop.
*          If it is positive, TOLMUL*EPS is the desired relative
*             precision in the computed singular values.
*          If it is negative, abs(TOLMUL*EPS*sigma_max) is the
*             desired absolute accuracy in the computed singular
*             values (corresponds to relative accuracy
*             abs(TOLMUL*EPS) in the largest singular value.
*          abs(TOLMUL) should be between 1 and 1/EPS, and preferably
*             between 10 (for fast convergence) and .1/EPS
*             (for there to be some accuracy in the results).
*          Default is to lose at either one eighth or 2 of the
*             available decimal digits in each computed singular value
*             (whichever is smaller).
*
*  MAXITR  INTEGER, default = 6
*          MAXITR controls the maximum number of passes of the
*          algorithm through its inner loop. The algorithms stops
*          (and so fails to converge) if the number of passes
*          through the inner loop exceeds MAXITR*N**2.
*
*  =====================================================================
*
*     .. Parameters ..
      DOUBLE PRECISION   ZERO
      PARAMETER          ( ZERO = 0.0D0 )
      DOUBLE PRECISION   ONE
      PARAMETER          ( ONE = 1.0D0 )
      DOUBLE PRECISION   NEGONE
      PARAMETER          ( NEGONE = -1.0D0 )
      DOUBLE PRECISION   HNDRTH
      PARAMETER          ( HNDRTH = 0.01D0 )
      DOUBLE PRECISION   TEN
      PARAMETER          ( TEN = 10.0D0 )
      DOUBLE PRECISION   HNDRD
      PARAMETER          ( HNDRD = 100.0D0 )
      DOUBLE PRECISION   MEIGTH
      PARAMETER          ( MEIGTH = -0.125D0 )
      INTEGER            MAXITR
      PARAMETER          ( MAXITR = 6 )
*     ..
*     .. Local Scalars ..
      LOGICAL            LOWER, ROTATE
      INTEGER            I, IDIR, ISUB, ITER, J, LL, LLL, M, MAXIT, NM1,
     $                   NM12, NM13, OLDLL, OLDM
      DOUBLE PRECISION   ABSE, ABSS, COSL, COSR, CS, EPS, F, G, H, MU,
     $                   OLDCS, OLDSN, R, SHIFT, SIGMN, SIGMX, SINL,
     $                   SINR, SLL, SMAX, SMIN, SMINL, SMINLO, SMINOA,
     $                   SN, THRESH, TOL, TOLMUL, UNFL
*     ..
*     .. External Functions ..
      LOGICAL            LSAME
      DOUBLE PRECISION   DLAMCH
      EXTERNAL           LSAME, DLAMCH
*     ..
*     .. External Subroutines ..
      EXTERNAL           DLARTG, DLAS2, DLASQ1, DLASV2, XERBLA, ZDROT,
     $                   ZDSCAL, ZLASR, ZSWAP
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          ABS, DBLE, MAX, MIN, SIGN, SQRT
*     ..
*     .. Executable Statements ..
*
*     Test the input parameters.
*
      INFO = 0
      LOWER = LSAME( UPLO, 'L' )
      IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LOWER ) THEN
         INFO = -1
      ELSE IF( N.LT.0 ) THEN
         INFO = -2
      ELSE IF( NCVT.LT.0 ) THEN
         INFO = -3
      ELSE IF( NRU.LT.0 ) THEN
         INFO = -4
      ELSE IF( NCC.LT.0 ) THEN
         INFO = -5
      ELSE IF( ( NCVT.EQ.0 .AND. LDVT.LT.1 ) .OR.
     $         ( NCVT.GT.0 .AND. LDVT.LT.MAX( 1, N ) ) ) THEN
         INFO = -9
      ELSE IF( LDU.LT.MAX( 1, NRU ) ) THEN
         INFO = -11
      ELSE IF( ( NCC.EQ.0 .AND. LDC.LT.1 ) .OR.
     $         ( NCC.GT.0 .AND. LDC.LT.MAX( 1, N ) ) ) THEN
         INFO = -13
      END IF
      IF( INFO.NE.0 ) THEN
         CALL XERBLA( 'ZBDSQR', -INFO )
         RETURN
      END IF
      IF( N.EQ.0 )
     $   RETURN
      IF( N.EQ.1 )
     $   GO TO 160
*
*     ROTATE is true if any singular vectors desired, false otherwise
*
      ROTATE = ( NCVT.GT.0 ) .OR. ( NRU.GT.0 ) .OR. ( NCC.GT.0 )
*
*     If no singular vectors desired, use qd algorithm
*
      IF( .NOT.ROTATE ) THEN
         CALL DLASQ1( N, D, E, RWORK, INFO )
         RETURN
      END IF
*
      NM1 = N - 1
      NM12 = NM1 + NM1
      NM13 = NM12 + NM1
      IDIR = 0
*
*     Get machine constants
*
      EPS = DLAMCH( 'Epsilon' )
      UNFL = DLAMCH( 'Safe minimum' )
*
*     If matrix lower bidiagonal, rotate to be upper bidiagonal
*     by applying Givens rotations on the left
*
      IF( LOWER ) THEN
         OPS = OPS + DBLE( N-1 )*( 8+12*( NRU+NCC ) )
         DO 10 I = 1, N - 1
            CALL DLARTG( D( I ), E( I ), CS, SN, R )
            D( I ) = R
            E( I ) = SN*D( I+1 )
            D( I+1 ) = CS*D( I+1 )
            RWORK( I ) = CS
            RWORK( NM1+I ) = SN
   10    CONTINUE
*
*        Update singular vectors if desired
*
         IF( NRU.GT.0 )
     $      CALL ZLASR( 'R', 'V', 'F', NRU, N, RWORK( 1 ), RWORK( N ),
     $                  U, LDU )
         IF( NCC.GT.0 )
     $      CALL ZLASR( 'L', 'V', 'F', N, NCC, RWORK( 1 ), RWORK( N ),
     $                  C, LDC )
      END IF
*
*     Compute singular values to relative accuracy TOL
*     (By setting TOL to be negative, algorithm will compute
*     singular values to absolute accuracy ABS(TOL)*norm(input matrix))
*
      OPS = OPS + 4
      TOLMUL = MAX( TEN, MIN( HNDRD, EPS**MEIGTH ) )
      TOL = TOLMUL*EPS
*
*     Compute approximate maximum, minimum singular values
*
      SMAX = ZERO
      DO 20 I = 1, N
         SMAX = MAX( SMAX, ABS( D( I ) ) )
   20 CONTINUE
      DO 30 I = 1, N - 1
         SMAX = MAX( SMAX, ABS( E( I ) ) )
   30 CONTINUE
      SMINL = ZERO
      IF( TOL.GE.ZERO ) THEN
*
*        Relative accuracy desired
*
         SMINOA = ABS( D( 1 ) )
         IF( SMINOA.EQ.ZERO )
     $      GO TO 50
         MU = SMINOA
         OPS = OPS + 3*N - 1
         DO 40 I = 2, N
            MU = ABS( D( I ) )*( MU / ( MU+ABS( E( I-1 ) ) ) )
            SMINOA = MIN( SMINOA, MU )
            IF( SMINOA.EQ.ZERO )
     $         GO TO 50
   40    CONTINUE
   50    CONTINUE
         SMINOA = SMINOA / SQRT( DBLE( N ) )
         THRESH = MAX( TOL*SMINOA, MAXITR*N*N*UNFL )
      ELSE
*
*        Absolute accuracy desired
*
         THRESH = MAX( ABS( TOL )*SMAX, MAXITR*N*N*UNFL )
      END IF
*
*     Prepare for main iteration loop for the singular values
*     (MAXIT is the maximum number of passes through the inner
*     loop permitted before nonconvergence signalled.)
*
      MAXIT = MAXITR*N*N
      ITER = 0
      OLDLL = -1
      OLDM = -1
*
*     M points to last element of unconverged part of matrix
*
      M = N
*
*     Begin main iteration loop
*
   60 CONTINUE
*
*     Check for convergence or exceeding iteration count
*
      IF( M.LE.1 )
     $   GO TO 160
      IF( ITER.GT.MAXIT )
     $   GO TO 200
*
*     Find diagonal block of matrix to work on
*
      IF( TOL.LT.ZERO .AND. ABS( D( M ) ).LE.THRESH )
     $   D( M ) = ZERO
      SMAX = ABS( D( M ) )
      SMIN = SMAX
      DO 70 LLL = 1, M - 1
         LL = M - LLL
         ABSS = ABS( D( LL ) )
         ABSE = ABS( E( LL ) )
         IF( TOL.LT.ZERO .AND. ABSS.LE.THRESH )
     $      D( LL ) = ZERO
         IF( ABSE.LE.THRESH )
     $      GO TO 80
         SMIN = MIN( SMIN, ABSS )
         SMAX = MAX( SMAX, ABSS, ABSE )
   70 CONTINUE
      LL = 0
      GO TO 90
   80 CONTINUE
      E( LL ) = ZERO
*
*     Matrix splits since E(LL) = 0
*
      IF( LL.EQ.M-1 ) THEN
*
*        Convergence of bottom singular value, return to top of loop
*
         M = M - 1
         GO TO 60
      END IF
   90 CONTINUE
      LL = LL + 1
*
*     E(LL) through E(M-1) are nonzero, E(LL-1) is zero
*
      IF( LL.EQ.M-1 ) THEN
*
*        2 by 2 block, handle separately
*
         OPS = OPS + 37 + 12*( NCVT+NRU+NCC )
         CALL DLASV2( D( M-1 ), E( M-1 ), D( M ), SIGMN, SIGMX, SINR,
     $                COSR, SINL, COSL )
         D( M-1 ) = SIGMX
         E( M-1 ) = ZERO
         D( M ) = SIGMN
*
*        Compute singular vectors, if desired
*
         IF( NCVT.GT.0 )
     $      CALL ZDROT( NCVT, VT( M-1, 1 ), LDVT, VT( M, 1 ), LDVT,
     $                  COSR, SINR )