dlasd1.f

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*> \brief \b DLASD1 computes the SVD of an upper bidiagonal matrix B of the specified size. Used by sbdsdc.
*
*  =========== DOCUMENTATION ===========
*
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*
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*
*  Definition:
*  ===========
*
*       SUBROUTINE DLASD1( NL, NR, SQRE, D, ALPHA, BETA, U, LDU, VT, LDVT,
*                          IDXQ, IWORK, WORK, INFO )
* 
*       .. Scalar Arguments ..
*       INTEGER            INFO, LDU, LDVT, NL, NR, SQRE
*       DOUBLE PRECISION   ALPHA, BETA
*       ..
*       .. Array Arguments ..
*       INTEGER            IDXQ( * ), IWORK( * )
*       DOUBLE PRECISION   D( * ), U( LDU, * ), VT( LDVT, * ), WORK( * )
*       ..
*  
*
*> \par Purpose:
*  =============
*>
*> \verbatim
*>
*> DLASD1 computes the SVD of an upper bidiagonal N-by-M matrix B,
*> where N = NL + NR + 1 and M = N + SQRE. DLASD1 is called from DLASD0.
*>
*> A related subroutine DLASD7 handles the case in which the singular
*> values (and the singular vectors in factored form) are desired.
*>
*> DLASD1 computes the SVD as follows:
*>
*>               ( D1(in)    0    0       0 )
*>   B = U(in) * (   Z1**T   a   Z2**T    b ) * VT(in)
*>               (   0       0   D2(in)   0 )
*>
*>     = U(out) * ( D(out) 0) * VT(out)
*>
*> where Z**T = (Z1**T a Z2**T b) = u**T VT**T, and u is a vector of dimension M
*> with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros
*> elsewhere; and the entry b is empty if SQRE = 0.
*>
*> The left singular vectors of the original matrix are stored in U, and
*> the transpose of the right singular vectors are stored in VT, and the
*> singular values are in D.  The algorithm consists of three stages:
*>
*>    The first stage consists of deflating the size of the problem
*>    when there are multiple singular values or when there are zeros in
*>    the Z vector.  For each such occurrence the dimension of the
*>    secular equation problem is reduced by one.  This stage is
*>    performed by the routine DLASD2.
*>
*>    The second stage consists of calculating the updated
*>    singular values. This is done by finding the square roots of the
*>    roots of the secular equation via the routine DLASD4 (as called
*>    by DLASD3). This routine also calculates the singular vectors of
*>    the current problem.
*>
*>    The final stage consists of computing the updated singular vectors
*>    directly using the updated singular values.  The singular vectors
*>    for the current problem are multiplied with the singular vectors
*>    from the overall problem.
*> \endverbatim
*
*  Arguments:
*  ==========
*
*> \param[in] NL
*> \verbatim
*>          NL is INTEGER
*>         The row dimension of the upper block.  NL >= 1.
*> \endverbatim
*>
*> \param[in] NR
*> \verbatim
*>          NR is INTEGER
*>         The row dimension of the lower block.  NR >= 1.
*> \endverbatim
*>
*> \param[in] SQRE
*> \verbatim
*>          SQRE is INTEGER
*>         = 0: the lower block is an NR-by-NR square matrix.
*>         = 1: the lower block is an NR-by-(NR+1) rectangular matrix.
*>
*>         The bidiagonal matrix has row dimension N = NL + NR + 1,
*>         and column dimension M = N + SQRE.
*> \endverbatim
*>
*> \param[in,out] D
*> \verbatim
*>          D is DOUBLE PRECISION array,
*>                        dimension (N = NL+NR+1).
*>         On entry D(1:NL,1:NL) contains the singular values of the
*>         upper block; and D(NL+2:N) contains the singular values of
*>         the lower block. On exit D(1:N) contains the singular values
*>         of the modified matrix.
*> \endverbatim
*>
*> \param[in,out] ALPHA
*> \verbatim
*>          ALPHA is DOUBLE PRECISION
*>         Contains the diagonal element associated with the added row.
*> \endverbatim
*>
*> \param[in,out] BETA
*> \verbatim
*>          BETA is DOUBLE PRECISION
*>         Contains the off-diagonal element associated with the added
*>         row.
*> \endverbatim
*>
*> \param[in,out] U
*> \verbatim
*>          U is DOUBLE PRECISION array, dimension(LDU,N)
*>         On entry U(1:NL, 1:NL) contains the left singular vectors of
*>         the upper block; U(NL+2:N, NL+2:N) contains the left singular
*>         vectors of the lower block. On exit U contains the left
*>         singular vectors of the bidiagonal matrix.
*> \endverbatim
*>
*> \param[in] LDU
*> \verbatim
*>          LDU is INTEGER
*>         The leading dimension of the array U.  LDU >= max( 1, N ).
*> \endverbatim
*>
*> \param[in,out] VT
*> \verbatim
*>          VT is DOUBLE PRECISION array, dimension(LDVT,M)
*>         where M = N + SQRE.
*>         On entry VT(1:NL+1, 1:NL+1)**T contains the right singular
*>         vectors of the upper block; VT(NL+2:M, NL+2:M)**T contains
*>         the right singular vectors of the lower block. On exit
*>         VT**T contains the right singular vectors of the
*>         bidiagonal matrix.
*> \endverbatim
*>
*> \param[in] LDVT
*> \verbatim
*>          LDVT is INTEGER
*>         The leading dimension of the array VT.  LDVT >= max( 1, M ).
*> \endverbatim
*>
*> \param[in,out] IDXQ
*> \verbatim
*>          IDXQ is INTEGER array, dimension(N)
*>         This contains the permutation which will reintegrate the
*>         subproblem just solved back into sorted order, i.e.
*>         D( IDXQ( I = 1, N ) ) will be in ascending order.
*> \endverbatim
*>
*> \param[out] IWORK
*> \verbatim
*>          IWORK is INTEGER array, dimension( 4 * N )
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*>          WORK is DOUBLE PRECISION array, dimension( 3*M**2 + 2*M )
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*>          INFO is INTEGER
*>          = 0:  successful exit.
*>          < 0:  if INFO = -i, the i-th argument had an illegal value.
*>          > 0:  if INFO = 1, a singular value did not converge
*> \endverbatim
*
*  Authors:
*  ========
*
*> \author Univ. of Tennessee 
*> \author Univ. of California Berkeley 
*> \author Univ. of Colorado Denver 
*> \author NAG Ltd. 
*
*> \date June 2016
*
*> \ingroup auxOTHERauxiliary
*
*> \par Contributors:
*  ==================
*>
*>     Ming Gu and Huan Ren, Computer Science Division, University of
*>     California at Berkeley, USA
*>
*  =====================================================================
      SUBROUTINE dlasd1( NL, NR, SQRE, D, ALPHA, BETA, U, LDU, VT, LDVT,
     $                   idxq, iwork, work, info )
*
*  -- LAPACK auxiliary routine (version 3.6.1) --
*  -- LAPACK is a software package provided by Univ. of Tennessee,    --
*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*     June 2016
*
*     .. Scalar Arguments ..
      INTEGER            INFO, LDU, LDVT, NL, NR, SQRE
      DOUBLE PRECISION   ALPHA, BETA
*     ..
*     .. Array Arguments ..
      INTEGER            IDXQ( * ), IWORK( * )
      DOUBLE PRECISION   D( * ), U( ldu, * ), VT( ldvt, * ), WORK( * )
*     ..
*
*  =====================================================================
*
*     .. Parameters ..
*
      DOUBLE PRECISION   ONE, ZERO
      parameter                ( one = 1.0d+0, zero = 0.0d+0 )
*     ..
*     .. Local Scalars ..
      INTEGER            COLTYP, I, IDX, IDXC, IDXP, IQ, ISIGMA, IU2,
     $                   ivt2, iz, k, ldq, ldu2, ldvt2, m, n, n1, n2
      DOUBLE PRECISION   ORGNRM
*     ..
*     .. External Subroutines ..
      EXTERNAL           dlamrg, dlascl, dlasd2, dlasd3, xerbla
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          abs, max
*     ..
*     .. Executable Statements ..
*
*     Test the input parameters.
*
      info = 0
*
      IF( nl.LT.1 ) THEN
         info = -1
      ELSE IF( nr.LT.1 ) THEN
         info = -2
      ELSE IF( ( sqre.LT.0 ) .OR. ( sqre.GT.1 ) ) THEN
         info = -3
      END IF
      IF( info.NE.0 ) THEN
         CALL xerbla( 'DLASD1', -info )
         RETURN
      END IF
*
      n = nl + nr + 1
      m = n + sqre
*
*     The following values are for bookkeeping purposes only.  They are
*     integer pointers which indicate the portion of the workspace
*     used by a particular array in DLASD2 and DLASD3.
*
      ldu2 = n
      ldvt2 = m
*
      iz = 1
      isigma = iz + m
      iu2 = isigma + n
      ivt2 = iu2 + ldu2*n
      iq = ivt2 + ldvt2*m
*
      idx = 1
      idxc = idx + n
      coltyp = idxc + n
      idxp = coltyp + n
*
*     Scale.
*
      orgnrm = max( abs( alpha ), abs( beta ) )
      d( nl+1 ) = zero
      DO 10 i = 1, n
         IF( abs( d( i ) ).GT.orgnrm ) THEN
            orgnrm = abs( d( i ) )
         END IF
   10 CONTINUE
      CALL dlascl( 'G', 0, 0, orgnrm, one, n, 1, d, n, info )
      alpha = alpha / orgnrm
      beta = beta / orgnrm
*
*     Deflate singular values.
*
      CALL dlasd2( nl, nr, sqre, k, d, work( iz ), alpha, beta, u, ldu,
     $             vt, ldvt, work( isigma ), work( iu2 ), ldu2,
     $             work( ivt2 ), ldvt2, iwork( idxp ), iwork( idx ),
     $             iwork( idxc ), idxq, iwork( coltyp ), info )
*
*     Solve Secular Equation and update singular vectors.
*
      ldq = k
      CALL dlasd3( nl, nr, sqre, k, d, work( iq ), ldq, work( isigma ),
     $             u, ldu, work( iu2 ), ldu2, vt, ldvt, work( ivt2 ),
     $             ldvt2, iwork( idxc ), iwork( coltyp ), work( iz ),
     $             info )
*
*     Report the convergence failure.
*
      IF( info.NE.0 ) THEN
         RETURN
      END IF
*
*     Unscale.
*
      CALL dlascl( 'G', 0, 0, one, orgnrm, n, 1, d, n, info )
*
*     Prepare the IDXQ sorting permutation.
*
      n1 = k
      n2 = n - k
      CALL dlamrg( n1, n2, d, 1, -1, idxq )
*
      RETURN
*
*     End of DLASD1
*
      END