|
- *> \brief <b> DGESVDQ computes the singular value decomposition (SVD) with a QR-Preconditioned QR SVD Method for GE matrices</b>
- *
- * =========== DOCUMENTATION ===========
- *
- * Online html documentation available at
- * http://www.netlib.org/lapack/explore-html/
- *
- *> \htmlonly
- *> Download DGESVDQ + dependencies
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dgesvdq.f">
- *> [TGZ]</a>
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dgesvdq.f">
- *> [ZIP]</a>
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dgesvdq.f">
- *> [TXT]</a>
- *> \endhtmlonly
- *
- * Definition:
- * ===========
- *
- * SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
- * S, U, LDU, V, LDV, NUMRANK, IWORK, LIWORK,
- * WORK, LWORK, RWORK, LRWORK, INFO )
- *
- * .. Scalar Arguments ..
- * IMPLICIT NONE
- * CHARACTER JOBA, JOBP, JOBR, JOBU, JOBV
- * INTEGER M, N, LDA, LDU, LDV, NUMRANK, LIWORK, LWORK, LRWORK,
- * INFO
- * ..
- * .. Array Arguments ..
- * DOUBLE PRECISION A( LDA, * ), U( LDU, * ), V( LDV, * ), WORK( * )
- * DOUBLE PRECISION S( * ), RWORK( * )
- * INTEGER IWORK( * )
- * ..
- *
- *
- *> \par Purpose:
- * =============
- *>
- *> \verbatim
- *>
- *> DGESVDQ computes the singular value decomposition (SVD) of a real
- *> M-by-N matrix A, where M >= N. The SVD of A is written as
- *> [++] [xx] [x0] [xx]
- *> A = U * SIGMA * V^*, [++] = [xx] * [ox] * [xx]
- *> [++] [xx]
- *> where SIGMA is an N-by-N diagonal matrix, U is an M-by-N orthonormal
- *> matrix, and V is an N-by-N orthogonal matrix. The diagonal elements
- *> of SIGMA are the singular values of A. The columns of U and V are the
- *> left and the right singular vectors of A, respectively.
- *> \endverbatim
- *
- * Arguments:
- * ==========
- *
- *> \param[in] JOBA
- *> \verbatim
- *> JOBA is CHARACTER*1
- *> Specifies the level of accuracy in the computed SVD
- *> = 'A' The requested accuracy corresponds to having the backward
- *> error bounded by || delta A ||_F <= f(m,n) * EPS * || A ||_F,
- *> where EPS = DLAMCH('Epsilon'). This authorises DGESVDQ to
- *> truncate the computed triangular factor in a rank revealing
- *> QR factorization whenever the truncated part is below the
- *> threshold of the order of EPS * ||A||_F. This is aggressive
- *> truncation level.
- *> = 'M' Similarly as with 'A', but the truncation is more gentle: it
- *> is allowed only when there is a drop on the diagonal of the
- *> triangular factor in the QR factorization. This is medium
- *> truncation level.
- *> = 'H' High accuracy requested. No numerical rank determination based
- *> on the rank revealing QR factorization is attempted.
- *> = 'E' Same as 'H', and in addition the condition number of column
- *> scaled A is estimated and returned in RWORK(1).
- *> N^(-1/4)*RWORK(1) <= ||pinv(A_scaled)||_2 <= N^(1/4)*RWORK(1)
- *> \endverbatim
- *>
- *> \param[in] JOBP
- *> \verbatim
- *> JOBP is CHARACTER*1
- *> = 'P' The rows of A are ordered in decreasing order with respect to
- *> ||A(i,:)||_\infty. This enhances numerical accuracy at the cost
- *> of extra data movement. Recommended for numerical robustness.
- *> = 'N' No row pivoting.
- *> \endverbatim
- *>
- *> \param[in] JOBR
- *> \verbatim
- *> JOBR is CHARACTER*1
- *> = 'T' After the initial pivoted QR factorization, DGESVD is applied to
- *> the transposed R**T of the computed triangular factor R. This involves
- *> some extra data movement (matrix transpositions). Useful for
- *> experiments, research and development.
- *> = 'N' The triangular factor R is given as input to DGESVD. This may be
- *> preferred as it involves less data movement.
- *> \endverbatim
- *>
- *> \param[in] JOBU
- *> \verbatim
- *> JOBU is CHARACTER*1
- *> = 'A' All M left singular vectors are computed and returned in the
- *> matrix U. See the description of U.
- *> = 'S' or 'U' N = min(M,N) left singular vectors are computed and returned
- *> in the matrix U. See the description of U.
- *> = 'R' Numerical rank NUMRANK is determined and only NUMRANK left singular
- *> vectors are computed and returned in the matrix U.
- *> = 'F' The N left singular vectors are returned in factored form as the
- *> product of the Q factor from the initial QR factorization and the
- *> N left singular vectors of (R**T , 0)**T. If row pivoting is used,
- *> then the necessary information on the row pivoting is stored in
- *> IWORK(N+1:N+M-1).
- *> = 'N' The left singular vectors are not computed.
- *> \endverbatim
- *>
- *> \param[in] JOBV
- *> \verbatim
- *> JOBV is CHARACTER*1
- *> = 'A', 'V' All N right singular vectors are computed and returned in
- *> the matrix V.
- *> = 'R' Numerical rank NUMRANK is determined and only NUMRANK right singular
- *> vectors are computed and returned in the matrix V. This option is
- *> allowed only if JOBU = 'R' or JOBU = 'N'; otherwise it is illegal.
- *> = 'N' The right singular vectors are not computed.
- *> \endverbatim
- *>
- *> \param[in] M
- *> \verbatim
- *> M is INTEGER
- *> The number of rows of the input matrix A. M >= 0.
- *> \endverbatim
- *>
- *> \param[in] N
- *> \verbatim
- *> N is INTEGER
- *> The number of columns of the input matrix A. M >= N >= 0.
- *> \endverbatim
- *>
- *> \param[in,out] A
- *> \verbatim
- *> A is DOUBLE PRECISION array of dimensions LDA x N
- *> On entry, the input matrix A.
- *> On exit, if JOBU .NE. 'N' or JOBV .NE. 'N', the lower triangle of A contains
- *> the Householder vectors as stored by DGEQP3. If JOBU = 'F', these Householder
- *> vectors together with WORK(1:N) can be used to restore the Q factors from
- *> the initial pivoted QR factorization of A. See the description of U.
- *> \endverbatim
- *>
- *> \param[in] LDA
- *> \verbatim
- *> LDA is INTEGER.
- *> The leading dimension of the array A. LDA >= max(1,M).
- *> \endverbatim
- *>
- *> \param[out] S
- *> \verbatim
- *> S is DOUBLE PRECISION array of dimension N.
- *> The singular values of A, ordered so that S(i) >= S(i+1).
- *> \endverbatim
- *>
- *> \param[out] U
- *> \verbatim
- *> U is DOUBLE PRECISION array, dimension
- *> LDU x M if JOBU = 'A'; see the description of LDU. In this case,
- *> on exit, U contains the M left singular vectors.
- *> LDU x N if JOBU = 'S', 'U', 'R' ; see the description of LDU. In this
- *> case, U contains the leading N or the leading NUMRANK left singular vectors.
- *> LDU x N if JOBU = 'F' ; see the description of LDU. In this case U
- *> contains N x N orthogonal matrix that can be used to form the left
- *> singular vectors.
- *> If JOBU = 'N', U is not referenced.
- *> \endverbatim
- *>
- *> \param[in] LDU
- *> \verbatim
- *> LDU is INTEGER.
- *> The leading dimension of the array U.
- *> If JOBU = 'A', 'S', 'U', 'R', LDU >= max(1,M).
- *> If JOBU = 'F', LDU >= max(1,N).
- *> Otherwise, LDU >= 1.
- *> \endverbatim
- *>
- *> \param[out] V
- *> \verbatim
- *> V is DOUBLE PRECISION array, dimension
- *> LDV x N if JOBV = 'A', 'V', 'R' or if JOBA = 'E' .
- *> If JOBV = 'A', or 'V', V contains the N-by-N orthogonal matrix V**T;
- *> If JOBV = 'R', V contains the first NUMRANK rows of V**T (the right
- *> singular vectors, stored rowwise, of the NUMRANK largest singular values).
- *> If JOBV = 'N' and JOBA = 'E', V is used as a workspace.
- *> If JOBV = 'N', and JOBA.NE.'E', V is not referenced.
- *> \endverbatim
- *>
- *> \param[in] LDV
- *> \verbatim
- *> LDV is INTEGER
- *> The leading dimension of the array V.
- *> If JOBV = 'A', 'V', 'R', or JOBA = 'E', LDV >= max(1,N).
- *> Otherwise, LDV >= 1.
- *> \endverbatim
- *>
- *> \param[out] NUMRANK
- *> \verbatim
- *> NUMRANK is INTEGER
- *> NUMRANK is the numerical rank first determined after the rank
- *> revealing QR factorization, following the strategy specified by the
- *> value of JOBA. If JOBV = 'R' and JOBU = 'R', only NUMRANK
- *> leading singular values and vectors are then requested in the call
- *> of DGESVD. The final value of NUMRANK might be further reduced if
- *> some singular values are computed as zeros.
- *> \endverbatim
- *>
- *> \param[out] IWORK
- *> \verbatim
- *> IWORK is INTEGER array, dimension (max(1, LIWORK)).
- *> On exit, IWORK(1:N) contains column pivoting permutation of the
- *> rank revealing QR factorization.
- *> If JOBP = 'P', IWORK(N+1:N+M-1) contains the indices of the sequence
- *> of row swaps used in row pivoting. These can be used to restore the
- *> left singular vectors in the case JOBU = 'F'.
- *>
- *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
- *> LIWORK(1) returns the minimal LIWORK.
- *> \endverbatim
- *>
- *> \param[in] LIWORK
- *> \verbatim
- *> LIWORK is INTEGER
- *> The dimension of the array IWORK.
- *> LIWORK >= N + M - 1, if JOBP = 'P' and JOBA .NE. 'E';
- *> LIWORK >= N if JOBP = 'N' and JOBA .NE. 'E';
- *> LIWORK >= N + M - 1 + N, if JOBP = 'P' and JOBA = 'E';
- *> LIWORK >= N + N if JOBP = 'N' and JOBA = 'E'.
- *
- *> If LIWORK = -1, then a workspace query is assumed; the routine
- *> only calculates and returns the optimal and minimal sizes
- *> for the WORK, IWORK, and RWORK arrays, and no error
- *> message related to LWORK is issued by XERBLA.
- *> \endverbatim
- *>
- *> \param[out] WORK
- *> \verbatim
- *> WORK is DOUBLE PRECISION array, dimension (max(2, LWORK)), used as a workspace.
- *> On exit, if, on entry, LWORK.NE.-1, WORK(1:N) contains parameters
- *> needed to recover the Q factor from the QR factorization computed by
- *> DGEQP3.
- *>
- *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
- *> WORK(1) returns the optimal LWORK, and
- *> WORK(2) returns the minimal LWORK.
- *> \endverbatim
- *>
- *> \param[in,out] LWORK
- *> \verbatim
- *> LWORK is INTEGER
- *> The dimension of the array WORK. It is determined as follows:
- *> Let LWQP3 = 3*N+1, LWCON = 3*N, and let
- *> LWORQ = { MAX( N, 1 ), if JOBU = 'R', 'S', or 'U'
- *> { MAX( M, 1 ), if JOBU = 'A'
- *> LWSVD = MAX( 5*N, 1 )
- *> LWLQF = MAX( N/2, 1 ), LWSVD2 = MAX( 5*(N/2), 1 ), LWORLQ = MAX( N, 1 ),
- *> LWQRF = MAX( N/2, 1 ), LWORQ2 = MAX( N, 1 )
- *> Then the minimal value of LWORK is:
- *> = MAX( N + LWQP3, LWSVD ) if only the singular values are needed;
- *> = MAX( N + LWQP3, LWCON, LWSVD ) if only the singular values are needed,
- *> and a scaled condition estimate requested;
- *>
- *> = N + MAX( LWQP3, LWSVD, LWORQ ) if the singular values and the left
- *> singular vectors are requested;
- *> = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the singular values and the left
- *> singular vectors are requested, and also
- *> a scaled condition estimate requested;
- *>
- *> = N + MAX( LWQP3, LWSVD ) if the singular values and the right
- *> singular vectors are requested;
- *> = N + MAX( LWQP3, LWCON, LWSVD ) if the singular values and the right
- *> singular vectors are requested, and also
- *> a scaled condition etimate requested;
- *>
- *> = N + MAX( LWQP3, LWSVD, LWORQ ) if the full SVD is requested with JOBV = 'R';
- *> independent of JOBR;
- *> = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the full SVD is requested,
- *> JOBV = 'R' and, also a scaled condition
- *> estimate requested; independent of JOBR;
- *> = MAX( N + MAX( LWQP3, LWSVD, LWORQ ),
- *> N + MAX( LWQP3, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ) ) if the
- *> full SVD is requested with JOBV = 'A' or 'V', and
- *> JOBR ='N'
- *> = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ),
- *> N + MAX( LWQP3, LWCON, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ ) )
- *> if the full SVD is requested with JOBV = 'A' or 'V', and
- *> JOBR ='N', and also a scaled condition number estimate
- *> requested.
- *> = MAX( N + MAX( LWQP3, LWSVD, LWORQ ),
- *> N + MAX( LWQP3, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) ) if the
- *> full SVD is requested with JOBV = 'A', 'V', and JOBR ='T'
- *> = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ),
- *> N + MAX( LWQP3, LWCON, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) )
- *> if the full SVD is requested with JOBV = 'A' or 'V', and
- *> JOBR ='T', and also a scaled condition number estimate
- *> requested.
- *> Finally, LWORK must be at least two: LWORK = MAX( 2, LWORK ).
- *>
- *> If LWORK = -1, then a workspace query is assumed; the routine
- *> only calculates and returns the optimal and minimal sizes
- *> for the WORK, IWORK, and RWORK arrays, and no error
- *> message related to LWORK is issued by XERBLA.
- *> \endverbatim
- *>
- *> \param[out] RWORK
- *> \verbatim
- *> RWORK is DOUBLE PRECISION array, dimension (max(1, LRWORK)).
- *> On exit,
- *> 1. If JOBA = 'E', RWORK(1) contains an estimate of the condition
- *> number of column scaled A. If A = C * D where D is diagonal and C
- *> has unit columns in the Euclidean norm, then, assuming full column rank,
- *> N^(-1/4) * RWORK(1) <= ||pinv(C)||_2 <= N^(1/4) * RWORK(1).
- *> Otherwise, RWORK(1) = -1.
- *> 2. RWORK(2) contains the number of singular values computed as
- *> exact zeros in DGESVD applied to the upper triangular or trapeziodal
- *> R (from the initial QR factorization). In case of early exit (no call to
- *> DGESVD, such as in the case of zero matrix) RWORK(2) = -1.
- *>
- *> If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0,
- *> RWORK(1) returns the minimal LRWORK.
- *> \endverbatim
- *>
- *> \param[in] LRWORK
- *> \verbatim
- *> LRWORK is INTEGER.
- *> The dimension of the array RWORK.
- *> If JOBP ='P', then LRWORK >= MAX(2, M).
- *> Otherwise, LRWORK >= 2
- *
- *> If LRWORK = -1, then a workspace query is assumed; the routine
- *> only calculates and returns the optimal and minimal sizes
- *> for the WORK, IWORK, and RWORK arrays, and no error
- *> message related to LWORK is issued by XERBLA.
- *> \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 DBDSQR did not converge, INFO specifies how many superdiagonals
- *> of an intermediate bidiagonal form B (computed in DGESVD) did not
- *> converge to zero.
- *> \endverbatim
- *
- *> \par Further Details:
- * ========================
- *>
- *> \verbatim
- *>
- *> 1. The data movement (matrix transpose) is coded using simple nested
- *> DO-loops because BLAS and LAPACK do not provide corresponding subroutines.
- *> Those DO-loops are easily identified in this source code - by the CONTINUE
- *> statements labeled with 11**. In an optimized version of this code, the
- *> nested DO loops should be replaced with calls to an optimized subroutine.
- *> 2. This code scales A by 1/SQRT(M) if the largest ABS(A(i,j)) could cause
- *> column norm overflow. This is the minial precaution and it is left to the
- *> SVD routine (CGESVD) to do its own preemptive scaling if potential over-
- *> or underflows are detected. To avoid repeated scanning of the array A,
- *> an optimal implementation would do all necessary scaling before calling
- *> CGESVD and the scaling in CGESVD can be switched off.
- *> 3. Other comments related to code optimization are given in comments in the
- *> code, enlosed in [[double brackets]].
- *> \endverbatim
- *
- *> \par Bugs, examples and comments
- * ===========================
- *
- *> \verbatim
- *> Please report all bugs and send interesting examples and/or comments to
- *> drmac@math.hr. Thank you.
- *> \endverbatim
- *
- *> \par References
- * ===============
- *
- *> \verbatim
- *> [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for
- *> Computing the SVD with High Accuracy. ACM Trans. Math. Softw.
- *> 44(1): 11:1-11:30 (2017)
- *>
- *> SIGMA library, xGESVDQ section updated February 2016.
- *> Developed and coded by Zlatko Drmac, Department of Mathematics
- *> University of Zagreb, Croatia, drmac@math.hr
- *> \endverbatim
- *
- *
- *> \par Contributors:
- * ==================
- *>
- *> \verbatim
- *> Developed and coded by Zlatko Drmac, Department of Mathematics
- *> University of Zagreb, Croatia, drmac@math.hr
- *> \endverbatim
- *
- * Authors:
- * ========
- *
- *> \author Univ. of Tennessee
- *> \author Univ. of California Berkeley
- *> \author Univ. of Colorado Denver
- *> \author NAG Ltd.
- *
- *> \date November 2018
- *
- *> \ingroup doubleGEsing
- *
- * =====================================================================
- SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA,
- $ S, U, LDU, V, LDV, NUMRANK, IWORK, LIWORK,
- $ WORK, LWORK, RWORK, LRWORK, INFO )
- * .. Scalar Arguments ..
- IMPLICIT NONE
- CHARACTER JOBA, JOBP, JOBR, JOBU, JOBV
- INTEGER M, N, LDA, LDU, LDV, NUMRANK, LIWORK, LWORK, LRWORK,
- $ INFO
- * ..
- * .. Array Arguments ..
- DOUBLE PRECISION A( LDA, * ), U( LDU, * ), V( LDV, * ), WORK( * )
- DOUBLE PRECISION S( * ), RWORK( * )
- INTEGER IWORK( * )
- *
- * =====================================================================
- *
- * .. Parameters ..
- DOUBLE PRECISION ZERO, ONE
- PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
- * .. Local Scalars ..
- INTEGER IERR, IWOFF, NR, N1, OPTRATIO, p, q
- INTEGER LWCON, LWQP3, LWRK_DGELQF, LWRK_DGESVD, LWRK_DGESVD2,
- $ LWRK_DGEQP3, LWRK_DGEQRF, LWRK_DORMLQ, LWRK_DORMQR,
- $ LWRK_DORMQR2, LWLQF, LWQRF, LWSVD, LWSVD2, LWORQ,
- $ LWORQ2, LWORLQ, MINWRK, MINWRK2, OPTWRK, OPTWRK2,
- $ IMINWRK, RMINWRK
- LOGICAL ACCLA, ACCLM, ACCLH, ASCALED, CONDA, DNTWU, DNTWV,
- $ LQUERY, LSVC0, LSVEC, ROWPRM, RSVEC, RTRANS, WNTUA,
- $ WNTUF, WNTUR, WNTUS, WNTVA, WNTVR
- DOUBLE PRECISION BIG, EPSLN, RTMP, SCONDA, SFMIN
- * .. Local Arrays
- DOUBLE PRECISION RDUMMY(1)
- * ..
- * .. External Subroutines (BLAS, LAPACK)
- EXTERNAL DGELQF, DGEQP3, DGEQRF, DGESVD, DLACPY, DLAPMT,
- $ DLASCL, DLASET, DLASWP, DSCAL, DPOCON, DORMLQ,
- $ DORMQR, XERBLA
- * ..
- * .. External Functions (BLAS, LAPACK)
- LOGICAL LSAME
- INTEGER IDAMAX
- DOUBLE PRECISION DLANGE, DNRM2, DLAMCH
- EXTERNAL DLANGE, LSAME, IDAMAX, DNRM2, DLAMCH
- * ..
- * .. Intrinsic Functions ..
- *
- INTRINSIC ABS, MAX, MIN, DBLE, SQRT
- *
- * Test the input arguments
- *
- WNTUS = LSAME( JOBU, 'S' ) .OR. LSAME( JOBU, 'U' )
- WNTUR = LSAME( JOBU, 'R' )
- WNTUA = LSAME( JOBU, 'A' )
- WNTUF = LSAME( JOBU, 'F' )
- LSVC0 = WNTUS .OR. WNTUR .OR. WNTUA
- LSVEC = LSVC0 .OR. WNTUF
- DNTWU = LSAME( JOBU, 'N' )
- *
- WNTVR = LSAME( JOBV, 'R' )
- WNTVA = LSAME( JOBV, 'A' ) .OR. LSAME( JOBV, 'V' )
- RSVEC = WNTVR .OR. WNTVA
- DNTWV = LSAME( JOBV, 'N' )
- *
- ACCLA = LSAME( JOBA, 'A' )
- ACCLM = LSAME( JOBA, 'M' )
- CONDA = LSAME( JOBA, 'E' )
- ACCLH = LSAME( JOBA, 'H' ) .OR. CONDA
- *
- ROWPRM = LSAME( JOBP, 'P' )
- RTRANS = LSAME( JOBR, 'T' )
- *
- IF ( ROWPRM ) THEN
- IF ( CONDA ) THEN
- IMINWRK = MAX( 1, N + M - 1 + N )
- ELSE
- IMINWRK = MAX( 1, N + M - 1 )
- END IF
- RMINWRK = MAX( 2, M )
- ELSE
- IF ( CONDA ) THEN
- IMINWRK = MAX( 1, N + N )
- ELSE
- IMINWRK = MAX( 1, N )
- END IF
- RMINWRK = 2
- END IF
- LQUERY = (LIWORK .EQ. -1 .OR. LWORK .EQ. -1 .OR. LRWORK .EQ. -1)
- INFO = 0
- IF ( .NOT. ( ACCLA .OR. ACCLM .OR. ACCLH ) ) THEN
- INFO = -1
- ELSE IF ( .NOT.( ROWPRM .OR. LSAME( JOBP, 'N' ) ) ) THEN
- INFO = -2
- ELSE IF ( .NOT.( RTRANS .OR. LSAME( JOBR, 'N' ) ) ) THEN
- INFO = -3
- ELSE IF ( .NOT.( LSVEC .OR. DNTWU ) ) THEN
- INFO = -4
- ELSE IF ( WNTUR .AND. WNTVA ) THEN
- INFO = -5
- ELSE IF ( .NOT.( RSVEC .OR. DNTWV )) THEN
- INFO = -5
- ELSE IF ( M.LT.0 ) THEN
- INFO = -6
- ELSE IF ( ( N.LT.0 ) .OR. ( N.GT.M ) ) THEN
- INFO = -7
- ELSE IF ( LDA.LT.MAX( 1, M ) ) THEN
- INFO = -9
- ELSE IF ( LDU.LT.1 .OR. ( LSVC0 .AND. LDU.LT.M ) .OR.
- $ ( WNTUF .AND. LDU.LT.N ) ) THEN
- INFO = -12
- ELSE IF ( LDV.LT.1 .OR. ( RSVEC .AND. LDV.LT.N ) .OR.
- $ ( CONDA .AND. LDV.LT.N ) ) THEN
- INFO = -14
- ELSE IF ( LIWORK .LT. IMINWRK .AND. .NOT. LQUERY ) THEN
- INFO = -17
- END IF
- *
- *
- IF ( INFO .EQ. 0 ) THEN
- * .. compute the minimal and the optimal workspace lengths
- * [[The expressions for computing the minimal and the optimal
- * values of LWORK are written with a lot of redundancy and
- * can be simplified. However, this detailed form is easier for
- * maintenance and modifications of the code.]]
- *
- * .. minimal workspace length for DGEQP3 of an M x N matrix
- LWQP3 = 3 * N + 1
- * .. minimal workspace length for DORMQR to build left singular vectors
- IF ( WNTUS .OR. WNTUR ) THEN
- LWORQ = MAX( N , 1 )
- ELSE IF ( WNTUA ) THEN
- LWORQ = MAX( M , 1 )
- END IF
- * .. minimal workspace length for DPOCON of an N x N matrix
- LWCON = 3 * N
- * .. DGESVD of an N x N matrix
- LWSVD = MAX( 5 * N, 1 )
- IF ( LQUERY ) THEN
- CALL DGEQP3( M, N, A, LDA, IWORK, RDUMMY, RDUMMY, -1,
- $ IERR )
- LWRK_DGEQP3 = INT( RDUMMY(1) )
- IF ( WNTUS .OR. WNTUR ) THEN
- CALL DORMQR( 'L', 'N', M, N, N, A, LDA, RDUMMY, U,
- $ LDU, RDUMMY, -1, IERR )
- LWRK_DORMQR = INT( RDUMMY(1) )
- ELSE IF ( WNTUA ) THEN
- CALL DORMQR( 'L', 'N', M, M, N, A, LDA, RDUMMY, U,
- $ LDU, RDUMMY, -1, IERR )
- LWRK_DORMQR = INT( RDUMMY(1) )
- ELSE
- LWRK_DORMQR = 0
- END IF
- END IF
- MINWRK = 2
- OPTWRK = 2
- IF ( .NOT. (LSVEC .OR. RSVEC )) THEN
- * .. minimal and optimal sizes of the workspace if
- * only the singular values are requested
- IF ( CONDA ) THEN
- MINWRK = MAX( N+LWQP3, LWCON, LWSVD )
- ELSE
- MINWRK = MAX( N+LWQP3, LWSVD )
- END IF
- IF ( LQUERY ) THEN
- CALL DGESVD( 'N', 'N', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DGESVD = INT( RDUMMY(1) )
- IF ( CONDA ) THEN
- OPTWRK = MAX( N+LWRK_DGEQP3, N+LWCON, LWRK_DGESVD )
- ELSE
- OPTWRK = MAX( N+LWRK_DGEQP3, LWRK_DGESVD )
- END IF
- END IF
- ELSE IF ( LSVEC .AND. (.NOT.RSVEC) ) THEN
- * .. minimal and optimal sizes of the workspace if the
- * singular values and the left singular vectors are requested
- IF ( CONDA ) THEN
- MINWRK = N + MAX( LWQP3, LWCON, LWSVD, LWORQ )
- ELSE
- MINWRK = N + MAX( LWQP3, LWSVD, LWORQ )
- END IF
- IF ( LQUERY ) THEN
- IF ( RTRANS ) THEN
- CALL DGESVD( 'N', 'O', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- ELSE
- CALL DGESVD( 'O', 'N', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- END IF
- LWRK_DGESVD = INT( RDUMMY(1) )
- IF ( CONDA ) THEN
- OPTWRK = N + MAX( LWRK_DGEQP3, LWCON, LWRK_DGESVD,
- $ LWRK_DORMQR )
- ELSE
- OPTWRK = N + MAX( LWRK_DGEQP3, LWRK_DGESVD,
- $ LWRK_DORMQR )
- END IF
- END IF
- ELSE IF ( RSVEC .AND. (.NOT.LSVEC) ) THEN
- * .. minimal and optimal sizes of the workspace if the
- * singular values and the right singular vectors are requested
- IF ( CONDA ) THEN
- MINWRK = N + MAX( LWQP3, LWCON, LWSVD )
- ELSE
- MINWRK = N + MAX( LWQP3, LWSVD )
- END IF
- IF ( LQUERY ) THEN
- IF ( RTRANS ) THEN
- CALL DGESVD( 'O', 'N', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- ELSE
- CALL DGESVD( 'N', 'O', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- END IF
- LWRK_DGESVD = INT( RDUMMY(1) )
- IF ( CONDA ) THEN
- OPTWRK = N + MAX( LWRK_DGEQP3, LWCON, LWRK_DGESVD )
- ELSE
- OPTWRK = N + MAX( LWRK_DGEQP3, LWRK_DGESVD )
- END IF
- END IF
- ELSE
- * .. minimal and optimal sizes of the workspace if the
- * full SVD is requested
- IF ( RTRANS ) THEN
- MINWRK = MAX( LWQP3, LWSVD, LWORQ )
- IF ( CONDA ) MINWRK = MAX( MINWRK, LWCON )
- MINWRK = MINWRK + N
- IF ( WNTVA ) THEN
- * .. minimal workspace length for N x N/2 DGEQRF
- LWQRF = MAX( N/2, 1 )
- * .. minimal workspace lengt for N/2 x N/2 DGESVD
- LWSVD2 = MAX( 5 * (N/2), 1 )
- LWORQ2 = MAX( N, 1 )
- MINWRK2 = MAX( LWQP3, N/2+LWQRF, N/2+LWSVD2,
- $ N/2+LWORQ2, LWORQ )
- IF ( CONDA ) MINWRK2 = MAX( MINWRK2, LWCON )
- MINWRK2 = N + MINWRK2
- MINWRK = MAX( MINWRK, MINWRK2 )
- END IF
- ELSE
- MINWRK = MAX( LWQP3, LWSVD, LWORQ )
- IF ( CONDA ) MINWRK = MAX( MINWRK, LWCON )
- MINWRK = MINWRK + N
- IF ( WNTVA ) THEN
- * .. minimal workspace length for N/2 x N DGELQF
- LWLQF = MAX( N/2, 1 )
- LWSVD2 = MAX( 5 * (N/2), 1 )
- LWORLQ = MAX( N , 1 )
- MINWRK2 = MAX( LWQP3, N/2+LWLQF, N/2+LWSVD2,
- $ N/2+LWORLQ, LWORQ )
- IF ( CONDA ) MINWRK2 = MAX( MINWRK2, LWCON )
- MINWRK2 = N + MINWRK2
- MINWRK = MAX( MINWRK, MINWRK2 )
- END IF
- END IF
- IF ( LQUERY ) THEN
- IF ( RTRANS ) THEN
- CALL DGESVD( 'O', 'A', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DGESVD = INT( RDUMMY(1) )
- OPTWRK = MAX(LWRK_DGEQP3,LWRK_DGESVD,LWRK_DORMQR)
- IF ( CONDA ) OPTWRK = MAX( OPTWRK, LWCON )
- OPTWRK = N + OPTWRK
- IF ( WNTVA ) THEN
- CALL DGEQRF(N,N/2,U,LDU,RDUMMY,RDUMMY,-1,IERR)
- LWRK_DGEQRF = INT( RDUMMY(1) )
- CALL DGESVD( 'S', 'O', N/2,N/2, V,LDV, S, U,LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DGESVD2 = INT( RDUMMY(1) )
- CALL DORMQR( 'R', 'C', N, N, N/2, U, LDU, RDUMMY,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DORMQR2 = INT( RDUMMY(1) )
- OPTWRK2 = MAX( LWRK_DGEQP3, N/2+LWRK_DGEQRF,
- $ N/2+LWRK_DGESVD2, N/2+LWRK_DORMQR2 )
- IF ( CONDA ) OPTWRK2 = MAX( OPTWRK2, LWCON )
- OPTWRK2 = N + OPTWRK2
- OPTWRK = MAX( OPTWRK, OPTWRK2 )
- END IF
- ELSE
- CALL DGESVD( 'S', 'O', N, N, A, LDA, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DGESVD = INT( RDUMMY(1) )
- OPTWRK = MAX(LWRK_DGEQP3,LWRK_DGESVD,LWRK_DORMQR)
- IF ( CONDA ) OPTWRK = MAX( OPTWRK, LWCON )
- OPTWRK = N + OPTWRK
- IF ( WNTVA ) THEN
- CALL DGELQF(N/2,N,U,LDU,RDUMMY,RDUMMY,-1,IERR)
- LWRK_DGELQF = INT( RDUMMY(1) )
- CALL DGESVD( 'S','O', N/2,N/2, V, LDV, S, U, LDU,
- $ V, LDV, RDUMMY, -1, IERR )
- LWRK_DGESVD2 = INT( RDUMMY(1) )
- CALL DORMLQ( 'R', 'N', N, N, N/2, U, LDU, RDUMMY,
- $ V, LDV, RDUMMY,-1,IERR )
- LWRK_DORMLQ = INT( RDUMMY(1) )
- OPTWRK2 = MAX( LWRK_DGEQP3, N/2+LWRK_DGELQF,
- $ N/2+LWRK_DGESVD2, N/2+LWRK_DORMLQ )
- IF ( CONDA ) OPTWRK2 = MAX( OPTWRK2, LWCON )
- OPTWRK2 = N + OPTWRK2
- OPTWRK = MAX( OPTWRK, OPTWRK2 )
- END IF
- END IF
- END IF
- END IF
- *
- MINWRK = MAX( 2, MINWRK )
- OPTWRK = MAX( 2, OPTWRK )
- IF ( LWORK .LT. MINWRK .AND. (.NOT.LQUERY) ) INFO = -19
- *
- END IF
- *
- IF (INFO .EQ. 0 .AND. LRWORK .LT. RMINWRK .AND. .NOT. LQUERY) THEN
- INFO = -21
- END IF
- IF( INFO.NE.0 ) THEN
- CALL XERBLA( 'DGESVDQ', -INFO )
- RETURN
- ELSE IF ( LQUERY ) THEN
- *
- * Return optimal workspace
- *
- IWORK(1) = IMINWRK
- WORK(1) = OPTWRK
- WORK(2) = MINWRK
- RWORK(1) = RMINWRK
- RETURN
- END IF
- *
- * Quick return if the matrix is void.
- *
- IF( ( M.EQ.0 ) .OR. ( N.EQ.0 ) ) THEN
- * .. all output is void.
- RETURN
- END IF
- *
- BIG = DLAMCH('O')
- ASCALED = .FALSE.
- IWOFF = 1
- IF ( ROWPRM ) THEN
- IWOFF = M
- * .. reordering the rows in decreasing sequence in the
- * ell-infinity norm - this enhances numerical robustness in
- * the case of differently scaled rows.
- DO 1904 p = 1, M
- * RWORK(p) = ABS( A(p,ICAMAX(N,A(p,1),LDA)) )
- * [[DLANGE will return NaN if an entry of the p-th row is Nan]]
- RWORK(p) = DLANGE( 'M', 1, N, A(p,1), LDA, RDUMMY )
- * .. check for NaN's and Inf's
- IF ( ( RWORK(p) .NE. RWORK(p) ) .OR.
- $ ( (RWORK(p)*ZERO) .NE. ZERO ) ) THEN
- INFO = -8
- CALL XERBLA( 'DGESVDQ', -INFO )
- RETURN
- END IF
- 1904 CONTINUE
- DO 1952 p = 1, M - 1
- q = IDAMAX( M-p+1, RWORK(p), 1 ) + p - 1
- IWORK(N+p) = q
- IF ( p .NE. q ) THEN
- RTMP = RWORK(p)
- RWORK(p) = RWORK(q)
- RWORK(q) = RTMP
- END IF
- 1952 CONTINUE
- *
- IF ( RWORK(1) .EQ. ZERO ) THEN
- * Quick return: A is the M x N zero matrix.
- NUMRANK = 0
- CALL DLASET( 'G', N, 1, ZERO, ZERO, S, N )
- IF ( WNTUS ) CALL DLASET('G', M, N, ZERO, ONE, U, LDU)
- IF ( WNTUA ) CALL DLASET('G', M, M, ZERO, ONE, U, LDU)
- IF ( WNTVA ) CALL DLASET('G', N, N, ZERO, ONE, V, LDV)
- IF ( WNTUF ) THEN
- CALL DLASET( 'G', N, 1, ZERO, ZERO, WORK, N )
- CALL DLASET( 'G', M, N, ZERO, ONE, U, LDU )
- END IF
- DO 5001 p = 1, N
- IWORK(p) = p
- 5001 CONTINUE
- IF ( ROWPRM ) THEN
- DO 5002 p = N + 1, N + M - 1
- IWORK(p) = p - N
- 5002 CONTINUE
- END IF
- IF ( CONDA ) RWORK(1) = -1
- RWORK(2) = -1
- RETURN
- END IF
- *
- IF ( RWORK(1) .GT. BIG / SQRT(DBLE(M)) ) THEN
- * .. to prevent overflow in the QR factorization, scale the
- * matrix by 1/sqrt(M) if too large entry detected
- CALL DLASCL('G',0,0,SQRT(DBLE(M)),ONE, M,N, A,LDA, IERR)
- ASCALED = .TRUE.
- END IF
- CALL DLASWP( N, A, LDA, 1, M-1, IWORK(N+1), 1 )
- END IF
- *
- * .. At this stage, preemptive scaling is done only to avoid column
- * norms overflows during the QR factorization. The SVD procedure should
- * have its own scaling to save the singular values from overflows and
- * underflows. That depends on the SVD procedure.
- *
- IF ( .NOT.ROWPRM ) THEN
- RTMP = DLANGE( 'M', M, N, A, LDA, RDUMMY )
- IF ( ( RTMP .NE. RTMP ) .OR.
- $ ( (RTMP*ZERO) .NE. ZERO ) ) THEN
- INFO = -8
- CALL XERBLA( 'DGESVDQ', -INFO )
- RETURN
- END IF
- IF ( RTMP .GT. BIG / SQRT(DBLE(M)) ) THEN
- * .. to prevent overflow in the QR factorization, scale the
- * matrix by 1/sqrt(M) if too large entry detected
- CALL DLASCL('G',0,0, SQRT(DBLE(M)),ONE, M,N, A,LDA, IERR)
- ASCALED = .TRUE.
- END IF
- END IF
- *
- * .. QR factorization with column pivoting
- *
- * A * P = Q * [ R ]
- * [ 0 ]
- *
- DO 1963 p = 1, N
- * .. all columns are free columns
- IWORK(p) = 0
- 1963 CONTINUE
- CALL DGEQP3( M, N, A, LDA, IWORK, WORK, WORK(N+1), LWORK-N,
- $ IERR )
- *
- * If the user requested accuracy level allows truncation in the
- * computed upper triangular factor, the matrix R is examined and,
- * if possible, replaced with its leading upper trapezoidal part.
- *
- EPSLN = DLAMCH('E')
- SFMIN = DLAMCH('S')
- * SMALL = SFMIN / EPSLN
- NR = N
- *
- IF ( ACCLA ) THEN
- *
- * Standard absolute error bound suffices. All sigma_i with
- * sigma_i < N*EPS*||A||_F are flushed to zero. This is an
- * aggressive enforcement of lower numerical rank by introducing a
- * backward error of the order of N*EPS*||A||_F.
- NR = 1
- RTMP = SQRT(DBLE(N))*EPSLN
- DO 3001 p = 2, N
- IF ( ABS(A(p,p)) .LT. (RTMP*ABS(A(1,1))) ) GO TO 3002
- NR = NR + 1
- 3001 CONTINUE
- 3002 CONTINUE
- *
- ELSEIF ( ACCLM ) THEN
- * .. similarly as above, only slightly more gentle (less aggressive).
- * Sudden drop on the diagonal of R is used as the criterion for being
- * close-to-rank-deficient. The threshold is set to EPSLN=DLAMCH('E').
- * [[This can be made more flexible by replacing this hard-coded value
- * with a user specified threshold.]] Also, the values that underflow
- * will be truncated.
- NR = 1
- DO 3401 p = 2, N
- IF ( ( ABS(A(p,p)) .LT. (EPSLN*ABS(A(p-1,p-1))) ) .OR.
- $ ( ABS(A(p,p)) .LT. SFMIN ) ) GO TO 3402
- NR = NR + 1
- 3401 CONTINUE
- 3402 CONTINUE
- *
- ELSE
- * .. RRQR not authorized to determine numerical rank except in the
- * obvious case of zero pivots.
- * .. inspect R for exact zeros on the diagonal;
- * R(i,i)=0 => R(i:N,i:N)=0.
- NR = 1
- DO 3501 p = 2, N
- IF ( ABS(A(p,p)) .EQ. ZERO ) GO TO 3502
- NR = NR + 1
- 3501 CONTINUE
- 3502 CONTINUE
- *
- IF ( CONDA ) THEN
- * Estimate the scaled condition number of A. Use the fact that it is
- * the same as the scaled condition number of R.
- * .. V is used as workspace
- CALL DLACPY( 'U', N, N, A, LDA, V, LDV )
- * Only the leading NR x NR submatrix of the triangular factor
- * is considered. Only if NR=N will this give a reliable error
- * bound. However, even for NR < N, this can be used on an
- * expert level and obtain useful information in the sense of
- * perturbation theory.
- DO 3053 p = 1, NR
- RTMP = DNRM2( p, V(1,p), 1 )
- CALL DSCAL( p, ONE/RTMP, V(1,p), 1 )
- 3053 CONTINUE
- IF ( .NOT. ( LSVEC .OR. RSVEC ) ) THEN
- CALL DPOCON( 'U', NR, V, LDV, ONE, RTMP,
- $ WORK, IWORK(N+IWOFF), IERR )
- ELSE
- CALL DPOCON( 'U', NR, V, LDV, ONE, RTMP,
- $ WORK(N+1), IWORK(N+IWOFF), IERR )
- END IF
- SCONDA = ONE / SQRT(RTMP)
- * For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1),
- * N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA
- * See the reference [1] for more details.
- END IF
- *
- ENDIF
- *
- IF ( WNTUR ) THEN
- N1 = NR
- ELSE IF ( WNTUS .OR. WNTUF) THEN
- N1 = N
- ELSE IF ( WNTUA ) THEN
- N1 = M
- END IF
- *
- IF ( .NOT. ( RSVEC .OR. LSVEC ) ) THEN
- *.......................................................................
- * .. only the singular values are requested
- *.......................................................................
- IF ( RTRANS ) THEN
- *
- * .. compute the singular values of R**T = [A](1:NR,1:N)**T
- * .. set the lower triangle of [A] to [A](1:NR,1:N)**T and
- * the upper triangle of [A] to zero.
- DO 1146 p = 1, MIN( N, NR )
- DO 1147 q = p + 1, N
- A(q,p) = A(p,q)
- IF ( q .LE. NR ) A(p,q) = ZERO
- 1147 CONTINUE
- 1146 CONTINUE
- *
- CALL DGESVD( 'N', 'N', N, NR, A, LDA, S, U, LDU,
- $ V, LDV, WORK, LWORK, INFO )
- *
- ELSE
- *
- * .. compute the singular values of R = [A](1:NR,1:N)
- *
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'L', NR-1,NR-1, ZERO,ZERO, A(2,1), LDA )
- CALL DGESVD( 'N', 'N', NR, N, A, LDA, S, U, LDU,
- $ V, LDV, WORK, LWORK, INFO )
- *
- END IF
- *
- ELSE IF ( LSVEC .AND. ( .NOT. RSVEC) ) THEN
- *.......................................................................
- * .. the singular values and the left singular vectors requested
- *.......................................................................""""""""
- IF ( RTRANS ) THEN
- * .. apply DGESVD to R**T
- * .. copy R**T into [U] and overwrite [U] with the right singular
- * vectors of R
- DO 1192 p = 1, NR
- DO 1193 q = p, N
- U(q,p) = A(p,q)
- 1193 CONTINUE
- 1192 CONTINUE
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, U(1,2), LDU )
- * .. the left singular vectors not computed, the NR right singular
- * vectors overwrite [U](1:NR,1:NR) as transposed. These
- * will be pre-multiplied by Q to build the left singular vectors of A.
- CALL DGESVD( 'N', 'O', N, NR, U, LDU, S, U, LDU,
- $ U, LDU, WORK(N+1), LWORK-N, INFO )
- *
- DO 1119 p = 1, NR
- DO 1120 q = p + 1, NR
- RTMP = U(q,p)
- U(q,p) = U(p,q)
- U(p,q) = RTMP
- 1120 CONTINUE
- 1119 CONTINUE
- *
- ELSE
- * .. apply DGESVD to R
- * .. copy R into [U] and overwrite [U] with the left singular vectors
- CALL DLACPY( 'U', NR, N, A, LDA, U, LDU )
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'L', NR-1, NR-1, ZERO, ZERO, U(2,1), LDU )
- * .. the right singular vectors not computed, the NR left singular
- * vectors overwrite [U](1:NR,1:NR)
- CALL DGESVD( 'O', 'N', NR, N, U, LDU, S, U, LDU,
- $ V, LDV, WORK(N+1), LWORK-N, INFO )
- * .. now [U](1:NR,1:NR) contains the NR left singular vectors of
- * R. These will be pre-multiplied by Q to build the left singular
- * vectors of A.
- END IF
- *
- * .. assemble the left singular vector matrix U of dimensions
- * (M x NR) or (M x N) or (M x M).
- IF ( ( NR .LT. M ) .AND. ( .NOT.WNTUF ) ) THEN
- CALL DLASET('A', M-NR, NR, ZERO, ZERO, U(NR+1,1), LDU)
- IF ( NR .LT. N1 ) THEN
- CALL DLASET( 'A',NR,N1-NR,ZERO,ZERO,U(1,NR+1), LDU )
- CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
- $ U(NR+1,NR+1), LDU )
- END IF
- END IF
- *
- * The Q matrix from the first QRF is built into the left singular
- * vectors matrix U.
- *
- IF ( .NOT.WNTUF )
- $ CALL DORMQR( 'L', 'N', M, N1, N, A, LDA, WORK, U,
- $ LDU, WORK(N+1), LWORK-N, IERR )
- IF ( ROWPRM .AND. .NOT.WNTUF )
- $ CALL DLASWP( N1, U, LDU, 1, M-1, IWORK(N+1), -1 )
- *
- ELSE IF ( RSVEC .AND. ( .NOT. LSVEC ) ) THEN
- *.......................................................................
- * .. the singular values and the right singular vectors requested
- *.......................................................................
- IF ( RTRANS ) THEN
- * .. apply DGESVD to R**T
- * .. copy R**T into V and overwrite V with the left singular vectors
- DO 1165 p = 1, NR
- DO 1166 q = p, N
- V(q,p) = (A(p,q))
- 1166 CONTINUE
- 1165 CONTINUE
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, V(1,2), LDV )
- * .. the left singular vectors of R**T overwrite V, the right singular
- * vectors not computed
- IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
- CALL DGESVD( 'O', 'N', N, NR, V, LDV, S, U, LDU,
- $ U, LDU, WORK(N+1), LWORK-N, INFO )
- *
- DO 1121 p = 1, NR
- DO 1122 q = p + 1, NR
- RTMP = V(q,p)
- V(q,p) = V(p,q)
- V(p,q) = RTMP
- 1122 CONTINUE
- 1121 CONTINUE
- *
- IF ( NR .LT. N ) THEN
- DO 1103 p = 1, NR
- DO 1104 q = NR + 1, N
- V(p,q) = V(q,p)
- 1104 CONTINUE
- 1103 CONTINUE
- END IF
- CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
- ELSE
- * .. need all N right singular vectors and NR < N
- * [!] This is simple implementation that augments [V](1:N,1:NR)
- * by padding a zero block. In the case NR << N, a more efficient
- * way is to first use the QR factorization. For more details
- * how to implement this, see the " FULL SVD " branch.
- CALL DLASET('G', N, N-NR, ZERO, ZERO, V(1,NR+1), LDV)
- CALL DGESVD( 'O', 'N', N, N, V, LDV, S, U, LDU,
- $ U, LDU, WORK(N+1), LWORK-N, INFO )
- *
- DO 1123 p = 1, N
- DO 1124 q = p + 1, N
- RTMP = V(q,p)
- V(q,p) = V(p,q)
- V(p,q) = RTMP
- 1124 CONTINUE
- 1123 CONTINUE
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- END IF
- *
- ELSE
- * .. aply DGESVD to R
- * .. copy R into V and overwrite V with the right singular vectors
- CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'L', NR-1, NR-1, ZERO, ZERO, V(2,1), LDV )
- * .. the right singular vectors overwrite V, the NR left singular
- * vectors stored in U(1:NR,1:NR)
- IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
- CALL DGESVD( 'N', 'O', NR, N, V, LDV, S, U, LDU,
- $ V, LDV, WORK(N+1), LWORK-N, INFO )
- CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
- * .. now [V](1:NR,1:N) contains V(1:N,1:NR)**T
- ELSE
- * .. need all N right singular vectors and NR < N
- * [!] This is simple implementation that augments [V](1:NR,1:N)
- * by padding a zero block. In the case NR << N, a more efficient
- * way is to first use the LQ factorization. For more details
- * how to implement this, see the " FULL SVD " branch.
- CALL DLASET('G', N-NR, N, ZERO,ZERO, V(NR+1,1), LDV)
- CALL DGESVD( 'N', 'O', N, N, V, LDV, S, U, LDU,
- $ V, LDV, WORK(N+1), LWORK-N, INFO )
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- END IF
- * .. now [V] contains the transposed matrix of the right singular
- * vectors of A.
- END IF
- *
- ELSE
- *.......................................................................
- * .. FULL SVD requested
- *.......................................................................
- IF ( RTRANS ) THEN
- *
- * .. apply DGESVD to R**T [[this option is left for R&D&T]]
- *
- IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
- * .. copy R**T into [V] and overwrite [V] with the left singular
- * vectors of R**T
- DO 1168 p = 1, NR
- DO 1169 q = p, N
- V(q,p) = A(p,q)
- 1169 CONTINUE
- 1168 CONTINUE
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'U', NR-1,NR-1, ZERO,ZERO, V(1,2), LDV )
- *
- * .. the left singular vectors of R**T overwrite [V], the NR right
- * singular vectors of R**T stored in [U](1:NR,1:NR) as transposed
- CALL DGESVD( 'O', 'A', N, NR, V, LDV, S, V, LDV,
- $ U, LDU, WORK(N+1), LWORK-N, INFO )
- * .. assemble V
- DO 1115 p = 1, NR
- DO 1116 q = p + 1, NR
- RTMP = V(q,p)
- V(q,p) = V(p,q)
- V(p,q) = RTMP
- 1116 CONTINUE
- 1115 CONTINUE
- IF ( NR .LT. N ) THEN
- DO 1101 p = 1, NR
- DO 1102 q = NR+1, N
- V(p,q) = V(q,p)
- 1102 CONTINUE
- 1101 CONTINUE
- END IF
- CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
- *
- DO 1117 p = 1, NR
- DO 1118 q = p + 1, NR
- RTMP = U(q,p)
- U(q,p) = U(p,q)
- U(p,q) = RTMP
- 1118 CONTINUE
- 1117 CONTINUE
- *
- IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A', M-NR,NR, ZERO,ZERO, U(NR+1,1), LDU)
- IF ( NR .LT. N1 ) THEN
- CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
- CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
- $ U(NR+1,NR+1), LDU )
- END IF
- END IF
- *
- ELSE
- * .. need all N right singular vectors and NR < N
- * .. copy R**T into [V] and overwrite [V] with the left singular
- * vectors of R**T
- * [[The optimal ratio N/NR for using QRF instead of padding
- * with zeros. Here hard coded to 2; it must be at least
- * two due to work space constraints.]]
- * OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0)
- * OPTRATIO = MAX( OPTRATIO, 2 )
- OPTRATIO = 2
- IF ( OPTRATIO*NR .GT. N ) THEN
- DO 1198 p = 1, NR
- DO 1199 q = p, N
- V(q,p) = A(p,q)
- 1199 CONTINUE
- 1198 CONTINUE
- IF ( NR .GT. 1 )
- $ CALL DLASET('U',NR-1,NR-1, ZERO,ZERO, V(1,2),LDV)
- *
- CALL DLASET('A',N,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
- CALL DGESVD( 'O', 'A', N, N, V, LDV, S, V, LDV,
- $ U, LDU, WORK(N+1), LWORK-N, INFO )
- *
- DO 1113 p = 1, N
- DO 1114 q = p + 1, N
- RTMP = V(q,p)
- V(q,p) = V(p,q)
- V(p,q) = RTMP
- 1114 CONTINUE
- 1113 CONTINUE
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- * .. assemble the left singular vector matrix U of dimensions
- * (M x N1), i.e. (M x N) or (M x M).
- *
- DO 1111 p = 1, N
- DO 1112 q = p + 1, N
- RTMP = U(q,p)
- U(q,p) = U(p,q)
- U(p,q) = RTMP
- 1112 CONTINUE
- 1111 CONTINUE
- *
- IF ( ( N .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A',M-N,N,ZERO,ZERO,U(N+1,1),LDU)
- IF ( N .LT. N1 ) THEN
- CALL DLASET('A',N,N1-N,ZERO,ZERO,U(1,N+1),LDU)
- CALL DLASET('A',M-N,N1-N,ZERO,ONE,
- $ U(N+1,N+1), LDU )
- END IF
- END IF
- ELSE
- * .. copy R**T into [U] and overwrite [U] with the right
- * singular vectors of R
- DO 1196 p = 1, NR
- DO 1197 q = p, N
- U(q,NR+p) = A(p,q)
- 1197 CONTINUE
- 1196 CONTINUE
- IF ( NR .GT. 1 )
- $ CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,U(1,NR+2),LDU)
- CALL DGEQRF( N, NR, U(1,NR+1), LDU, WORK(N+1),
- $ WORK(N+NR+1), LWORK-N-NR, IERR )
- DO 1143 p = 1, NR
- DO 1144 q = 1, N
- V(q,p) = U(p,NR+q)
- 1144 CONTINUE
- 1143 CONTINUE
- CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,V(1,2),LDV)
- CALL DGESVD( 'S', 'O', NR, NR, V, LDV, S, U, LDU,
- $ V,LDV, WORK(N+NR+1),LWORK-N-NR, INFO )
- CALL DLASET('A',N-NR,NR,ZERO,ZERO,V(NR+1,1),LDV)
- CALL DLASET('A',NR,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
- CALL DLASET('A',N-NR,N-NR,ZERO,ONE,V(NR+1,NR+1),LDV)
- CALL DORMQR('R','C', N, N, NR, U(1,NR+1), LDU,
- $ WORK(N+1),V,LDV,WORK(N+NR+1),LWORK-N-NR,IERR)
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- * .. assemble the left singular vector matrix U of dimensions
- * (M x NR) or (M x N) or (M x M).
- IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A',M-NR,NR,ZERO,ZERO,U(NR+1,1),LDU)
- IF ( NR .LT. N1 ) THEN
- CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
- CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
- $ U(NR+1,NR+1),LDU)
- END IF
- END IF
- END IF
- END IF
- *
- ELSE
- *
- * .. apply DGESVD to R [[this is the recommended option]]
- *
- IF ( WNTVR .OR. ( NR .EQ. N ) ) THEN
- * .. copy R into [V] and overwrite V with the right singular vectors
- CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
- IF ( NR .GT. 1 )
- $ CALL DLASET( 'L', NR-1,NR-1, ZERO,ZERO, V(2,1), LDV )
- * .. the right singular vectors of R overwrite [V], the NR left
- * singular vectors of R stored in [U](1:NR,1:NR)
- CALL DGESVD( 'S', 'O', NR, N, V, LDV, S, U, LDU,
- $ V, LDV, WORK(N+1), LWORK-N, INFO )
- CALL DLAPMT( .FALSE., NR, N, V, LDV, IWORK )
- * .. now [V](1:NR,1:N) contains V(1:N,1:NR)**T
- * .. assemble the left singular vector matrix U of dimensions
- * (M x NR) or (M x N) or (M x M).
- IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A', M-NR,NR, ZERO,ZERO, U(NR+1,1), LDU)
- IF ( NR .LT. N1 ) THEN
- CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
- CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
- $ U(NR+1,NR+1), LDU )
- END IF
- END IF
- *
- ELSE
- * .. need all N right singular vectors and NR < N
- * .. the requested number of the left singular vectors
- * is then N1 (N or M)
- * [[The optimal ratio N/NR for using LQ instead of padding
- * with zeros. Here hard coded to 2; it must be at least
- * two due to work space constraints.]]
- * OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0)
- * OPTRATIO = MAX( OPTRATIO, 2 )
- OPTRATIO = 2
- IF ( OPTRATIO * NR .GT. N ) THEN
- CALL DLACPY( 'U', NR, N, A, LDA, V, LDV )
- IF ( NR .GT. 1 )
- $ CALL DLASET('L', NR-1,NR-1, ZERO,ZERO, V(2,1),LDV)
- * .. the right singular vectors of R overwrite [V], the NR left
- * singular vectors of R stored in [U](1:NR,1:NR)
- CALL DLASET('A', N-NR,N, ZERO,ZERO, V(NR+1,1),LDV)
- CALL DGESVD( 'S', 'O', N, N, V, LDV, S, U, LDU,
- $ V, LDV, WORK(N+1), LWORK-N, INFO )
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- * .. now [V] contains the transposed matrix of the right
- * singular vectors of A. The leading N left singular vectors
- * are in [U](1:N,1:N)
- * .. assemble the left singular vector matrix U of dimensions
- * (M x N1), i.e. (M x N) or (M x M).
- IF ( ( N .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A',M-N,N,ZERO,ZERO,U(N+1,1),LDU)
- IF ( N .LT. N1 ) THEN
- CALL DLASET('A',N,N1-N,ZERO,ZERO,U(1,N+1),LDU)
- CALL DLASET( 'A',M-N,N1-N,ZERO,ONE,
- $ U(N+1,N+1), LDU )
- END IF
- END IF
- ELSE
- CALL DLACPY( 'U', NR, N, A, LDA, U(NR+1,1), LDU )
- IF ( NR .GT. 1 )
- $ CALL DLASET('L',NR-1,NR-1,ZERO,ZERO,U(NR+2,1),LDU)
- CALL DGELQF( NR, N, U(NR+1,1), LDU, WORK(N+1),
- $ WORK(N+NR+1), LWORK-N-NR, IERR )
- CALL DLACPY('L',NR,NR,U(NR+1,1),LDU,V,LDV)
- IF ( NR .GT. 1 )
- $ CALL DLASET('U',NR-1,NR-1,ZERO,ZERO,V(1,2),LDV)
- CALL DGESVD( 'S', 'O', NR, NR, V, LDV, S, U, LDU,
- $ V, LDV, WORK(N+NR+1), LWORK-N-NR, INFO )
- CALL DLASET('A',N-NR,NR,ZERO,ZERO,V(NR+1,1),LDV)
- CALL DLASET('A',NR,N-NR,ZERO,ZERO,V(1,NR+1),LDV)
- CALL DLASET('A',N-NR,N-NR,ZERO,ONE,V(NR+1,NR+1),LDV)
- CALL DORMLQ('R','N',N,N,NR,U(NR+1,1),LDU,WORK(N+1),
- $ V, LDV, WORK(N+NR+1),LWORK-N-NR,IERR)
- CALL DLAPMT( .FALSE., N, N, V, LDV, IWORK )
- * .. assemble the left singular vector matrix U of dimensions
- * (M x NR) or (M x N) or (M x M).
- IF ( ( NR .LT. M ) .AND. .NOT.(WNTUF)) THEN
- CALL DLASET('A',M-NR,NR,ZERO,ZERO,U(NR+1,1),LDU)
- IF ( NR .LT. N1 ) THEN
- CALL DLASET('A',NR,N1-NR,ZERO,ZERO,U(1,NR+1),LDU)
- CALL DLASET( 'A',M-NR,N1-NR,ZERO,ONE,
- $ U(NR+1,NR+1), LDU )
- END IF
- END IF
- END IF
- END IF
- * .. end of the "R**T or R" branch
- END IF
- *
- * The Q matrix from the first QRF is built into the left singular
- * vectors matrix U.
- *
- IF ( .NOT. WNTUF )
- $ CALL DORMQR( 'L', 'N', M, N1, N, A, LDA, WORK, U,
- $ LDU, WORK(N+1), LWORK-N, IERR )
- IF ( ROWPRM .AND. .NOT.WNTUF )
- $ CALL DLASWP( N1, U, LDU, 1, M-1, IWORK(N+1), -1 )
- *
- * ... end of the "full SVD" branch
- END IF
- *
- * Check whether some singular values are returned as zeros, e.g.
- * due to underflow, and update the numerical rank.
- p = NR
- DO 4001 q = p, 1, -1
- IF ( S(q) .GT. ZERO ) GO TO 4002
- NR = NR - 1
- 4001 CONTINUE
- 4002 CONTINUE
- *
- * .. if numerical rank deficiency is detected, the truncated
- * singular values are set to zero.
- IF ( NR .LT. N ) CALL DLASET( 'G', N-NR,1, ZERO,ZERO, S(NR+1), N )
- * .. undo scaling; this may cause overflow in the largest singular
- * values.
- IF ( ASCALED )
- $ CALL DLASCL( 'G',0,0, ONE,SQRT(DBLE(M)), NR,1, S, N, IERR )
- IF ( CONDA ) RWORK(1) = SCONDA
- RWORK(2) = p - NR
- * .. p-NR is the number of singular values that are computed as
- * exact zeros in DGESVD() applied to the (possibly truncated)
- * full row rank triangular (trapezoidal) factor of A.
- NUMRANK = NR
- *
- RETURN
- *
- * End of DGESVDQ
- *
- END
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