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515 lines
16 KiB
515 lines
16 KiB
2 years ago
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*> \brief \b SBDSDC
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*
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* =========== DOCUMENTATION ===========
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*
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* Online html documentation available at
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* http://www.netlib.org/lapack/explore-html/
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*
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*> \htmlonly
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*> Download SBDSDC + dependencies
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/sbdsdc.f">
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*> [TGZ]</a>
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/sbdsdc.f">
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*> [ZIP]</a>
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/sbdsdc.f">
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*> [TXT]</a>
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*> \endhtmlonly
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*
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* Definition:
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* ===========
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*
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* SUBROUTINE SBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ,
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* WORK, IWORK, INFO )
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*
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* .. Scalar Arguments ..
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* CHARACTER COMPQ, UPLO
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* INTEGER INFO, LDU, LDVT, N
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* ..
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* .. Array Arguments ..
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* INTEGER IQ( * ), IWORK( * )
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* REAL D( * ), E( * ), Q( * ), U( LDU, * ),
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* $ VT( LDVT, * ), WORK( * )
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* ..
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*
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*
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*> \par Purpose:
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* =============
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*>
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*> \verbatim
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*>
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*> SBDSDC computes the singular value decomposition (SVD) of a real
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*> N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT,
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*> using a divide and conquer method, where S is a diagonal matrix
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*> with non-negative diagonal elements (the singular values of B), and
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*> U and VT are orthogonal matrices of left and right singular vectors,
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*> respectively. SBDSDC can be used to compute all singular values,
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*> and optionally, singular vectors or singular vectors in compact form.
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*>
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*> The code currently calls SLASDQ if singular values only are desired.
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*> However, it can be slightly modified to compute singular values
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*> using the divide and conquer method.
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*> \endverbatim
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*
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* Arguments:
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* ==========
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*
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*> \param[in] UPLO
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*> \verbatim
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*> UPLO is CHARACTER*1
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*> = 'U': B is upper bidiagonal.
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*> = 'L': B is lower bidiagonal.
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*> \endverbatim
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*>
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*> \param[in] COMPQ
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*> \verbatim
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*> COMPQ is CHARACTER*1
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*> Specifies whether singular vectors are to be computed
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*> as follows:
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*> = 'N': Compute singular values only;
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*> = 'P': Compute singular values and compute singular
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*> vectors in compact form;
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*> = 'I': Compute singular values and singular vectors.
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*> \endverbatim
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*>
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*> \param[in] N
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*> \verbatim
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*> N is INTEGER
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*> The order of the matrix B. N >= 0.
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*> \endverbatim
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*>
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*> \param[in,out] D
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*> \verbatim
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*> D is REAL array, dimension (N)
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*> On entry, the n diagonal elements of the bidiagonal matrix B.
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*> On exit, if INFO=0, the singular values of B.
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*> \endverbatim
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*>
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*> \param[in,out] E
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*> \verbatim
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*> E is REAL array, dimension (N-1)
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*> On entry, the elements of E contain the offdiagonal
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*> elements of the bidiagonal matrix whose SVD is desired.
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*> On exit, E has been destroyed.
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*> \endverbatim
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*>
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*> \param[out] U
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*> \verbatim
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*> U is REAL array, dimension (LDU,N)
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*> If COMPQ = 'I', then:
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*> On exit, if INFO = 0, U contains the left singular vectors
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*> of the bidiagonal matrix.
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*> For other values of COMPQ, U is not referenced.
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*> \endverbatim
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*>
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*> \param[in] LDU
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*> \verbatim
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*> LDU is INTEGER
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*> The leading dimension of the array U. LDU >= 1.
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*> If singular vectors are desired, then LDU >= max( 1, N ).
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*> \endverbatim
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*>
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*> \param[out] VT
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*> \verbatim
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*> VT is REAL array, dimension (LDVT,N)
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*> If COMPQ = 'I', then:
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*> On exit, if INFO = 0, VT**T contains the right singular
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*> vectors of the bidiagonal matrix.
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*> For other values of COMPQ, VT is not referenced.
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*> \endverbatim
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*>
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*> \param[in] LDVT
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*> \verbatim
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*> LDVT is INTEGER
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*> The leading dimension of the array VT. LDVT >= 1.
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*> If singular vectors are desired, then LDVT >= max( 1, N ).
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*> \endverbatim
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*>
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*> \param[out] Q
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*> \verbatim
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*> Q is REAL array, dimension (LDQ)
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*> If COMPQ = 'P', then:
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*> On exit, if INFO = 0, Q and IQ contain the left
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*> and right singular vectors in a compact form,
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*> requiring O(N log N) space instead of 2*N**2.
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*> In particular, Q contains all the REAL data in
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*> LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1))))
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*> words of memory, where SMLSIZ is returned by ILAENV and
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*> is equal to the maximum size of the subproblems at the
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*> bottom of the computation tree (usually about 25).
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*> For other values of COMPQ, Q is not referenced.
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*> \endverbatim
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*>
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*> \param[out] IQ
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*> \verbatim
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*> IQ is INTEGER array, dimension (LDIQ)
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*> If COMPQ = 'P', then:
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*> On exit, if INFO = 0, Q and IQ contain the left
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*> and right singular vectors in a compact form,
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*> requiring O(N log N) space instead of 2*N**2.
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*> In particular, IQ contains all INTEGER data in
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*> LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1))))
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*> words of memory, where SMLSIZ is returned by ILAENV and
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*> is equal to the maximum size of the subproblems at the
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*> bottom of the computation tree (usually about 25).
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*> For other values of COMPQ, IQ is not referenced.
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*> \endverbatim
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*>
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*> \param[out] WORK
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*> \verbatim
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*> WORK is REAL array, dimension (MAX(1,LWORK))
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*> If COMPQ = 'N' then LWORK >= (4 * N).
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*> If COMPQ = 'P' then LWORK >= (6 * N).
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*> If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N).
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*> \endverbatim
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*>
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*> \param[out] IWORK
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*> \verbatim
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*> IWORK is INTEGER array, dimension (8*N)
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*> \endverbatim
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*>
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*> \param[out] INFO
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*> \verbatim
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*> INFO is INTEGER
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*> = 0: successful exit.
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*> < 0: if INFO = -i, the i-th argument had an illegal value.
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*> > 0: The algorithm failed to compute a singular value.
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*> The update process of divide and conquer failed.
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*> \endverbatim
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*
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* Authors:
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* ========
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*
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*> \author Univ. of Tennessee
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*> \author Univ. of California Berkeley
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*> \author Univ. of Colorado Denver
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*> \author NAG Ltd.
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*
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*> \ingroup auxOTHERcomputational
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*
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*> \par Contributors:
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* ==================
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*>
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*> Ming Gu and Huan Ren, Computer Science Division, University of
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*> California at Berkeley, USA
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*>
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* =====================================================================
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SUBROUTINE SBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ,
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$ WORK, IWORK, INFO )
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*
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* -- LAPACK computational routine --
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* -- LAPACK is a software package provided by Univ. of Tennessee, --
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* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
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*
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* .. Scalar Arguments ..
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CHARACTER COMPQ, UPLO
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INTEGER INFO, LDU, LDVT, N
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* ..
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* .. Array Arguments ..
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INTEGER IQ( * ), IWORK( * )
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REAL D( * ), E( * ), Q( * ), U( LDU, * ),
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$ VT( LDVT, * ), WORK( * )
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* ..
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*
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* =====================================================================
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* Changed dimension statement in comment describing E from (N) to
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* (N-1). Sven, 17 Feb 05.
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* =====================================================================
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*
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* .. Parameters ..
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REAL ZERO, ONE, TWO
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PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0, TWO = 2.0E+0 )
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* ..
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* .. Local Scalars ..
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INTEGER DIFL, DIFR, GIVCOL, GIVNUM, GIVPTR, I, IC,
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$ ICOMPQ, IERR, II, IS, IU, IUPLO, IVT, J, K, KK,
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$ MLVL, NM1, NSIZE, PERM, POLES, QSTART, SMLSIZ,
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$ SMLSZP, SQRE, START, WSTART, Z
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REAL CS, EPS, ORGNRM, P, R, SN
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* ..
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* .. External Functions ..
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LOGICAL LSAME
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INTEGER ILAENV
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REAL SLAMCH, SLANST
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EXTERNAL SLAMCH, SLANST, ILAENV, LSAME
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* ..
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* .. External Subroutines ..
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EXTERNAL SCOPY, SLARTG, SLASCL, SLASD0, SLASDA, SLASDQ,
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$ SLASET, SLASR, SSWAP, XERBLA
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* ..
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* .. Intrinsic Functions ..
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INTRINSIC REAL, ABS, INT, LOG, SIGN
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* ..
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* .. Executable Statements ..
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*
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* Test the input parameters.
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*
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INFO = 0
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*
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IUPLO = 0
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IF( LSAME( UPLO, 'U' ) )
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$ IUPLO = 1
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IF( LSAME( UPLO, 'L' ) )
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$ IUPLO = 2
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IF( LSAME( COMPQ, 'N' ) ) THEN
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ICOMPQ = 0
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ELSE IF( LSAME( COMPQ, 'P' ) ) THEN
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ICOMPQ = 1
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ELSE IF( LSAME( COMPQ, 'I' ) ) THEN
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ICOMPQ = 2
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ELSE
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ICOMPQ = -1
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END IF
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IF( IUPLO.EQ.0 ) THEN
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INFO = -1
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ELSE IF( ICOMPQ.LT.0 ) THEN
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INFO = -2
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ELSE IF( N.LT.0 ) THEN
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INFO = -3
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ELSE IF( ( LDU.LT.1 ) .OR. ( ( ICOMPQ.EQ.2 ) .AND. ( LDU.LT.
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$ N ) ) ) THEN
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INFO = -7
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ELSE IF( ( LDVT.LT.1 ) .OR. ( ( ICOMPQ.EQ.2 ) .AND. ( LDVT.LT.
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$ N ) ) ) THEN
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INFO = -9
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END IF
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IF( INFO.NE.0 ) THEN
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CALL XERBLA( 'SBDSDC', -INFO )
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RETURN
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END IF
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*
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* Quick return if possible
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*
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IF( N.EQ.0 )
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$ RETURN
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SMLSIZ = ILAENV( 9, 'SBDSDC', ' ', 0, 0, 0, 0 )
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IF( N.EQ.1 ) THEN
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IF( ICOMPQ.EQ.1 ) THEN
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Q( 1 ) = SIGN( ONE, D( 1 ) )
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Q( 1+SMLSIZ*N ) = ONE
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ELSE IF( ICOMPQ.EQ.2 ) THEN
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U( 1, 1 ) = SIGN( ONE, D( 1 ) )
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VT( 1, 1 ) = ONE
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END IF
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D( 1 ) = ABS( D( 1 ) )
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RETURN
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END IF
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NM1 = N - 1
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*
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* If matrix lower bidiagonal, rotate to be upper bidiagonal
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* by applying Givens rotations on the left
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*
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WSTART = 1
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QSTART = 3
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IF( ICOMPQ.EQ.1 ) THEN
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CALL SCOPY( N, D, 1, Q( 1 ), 1 )
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CALL SCOPY( N-1, E, 1, Q( N+1 ), 1 )
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END IF
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IF( IUPLO.EQ.2 ) THEN
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QSTART = 5
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IF( ICOMPQ .EQ. 2 ) WSTART = 2*N - 1
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DO 10 I = 1, N - 1
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CALL SLARTG( D( I ), E( I ), CS, SN, R )
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D( I ) = R
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E( I ) = SN*D( I+1 )
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D( I+1 ) = CS*D( I+1 )
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IF( ICOMPQ.EQ.1 ) THEN
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Q( I+2*N ) = CS
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Q( I+3*N ) = SN
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ELSE IF( ICOMPQ.EQ.2 ) THEN
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WORK( I ) = CS
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WORK( NM1+I ) = -SN
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END IF
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10 CONTINUE
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END IF
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*
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* If ICOMPQ = 0, use SLASDQ to compute the singular values.
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*
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IF( ICOMPQ.EQ.0 ) THEN
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* Ignore WSTART, instead using WORK( 1 ), since the two vectors
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* for CS and -SN above are added only if ICOMPQ == 2,
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* and adding them exceeds documented WORK size of 4*n.
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CALL SLASDQ( 'U', 0, N, 0, 0, 0, D, E, VT, LDVT, U, LDU, U,
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$ LDU, WORK( 1 ), INFO )
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GO TO 40
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END IF
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*
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* If N is smaller than the minimum divide size SMLSIZ, then solve
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* the problem with another solver.
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*
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IF( N.LE.SMLSIZ ) THEN
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IF( ICOMPQ.EQ.2 ) THEN
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CALL SLASET( 'A', N, N, ZERO, ONE, U, LDU )
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CALL SLASET( 'A', N, N, ZERO, ONE, VT, LDVT )
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CALL SLASDQ( 'U', 0, N, N, N, 0, D, E, VT, LDVT, U, LDU, U,
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$ LDU, WORK( WSTART ), INFO )
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ELSE IF( ICOMPQ.EQ.1 ) THEN
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IU = 1
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IVT = IU + N
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CALL SLASET( 'A', N, N, ZERO, ONE, Q( IU+( QSTART-1 )*N ),
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$ N )
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CALL SLASET( 'A', N, N, ZERO, ONE, Q( IVT+( QSTART-1 )*N ),
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$ N )
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CALL SLASDQ( 'U', 0, N, N, N, 0, D, E,
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$ Q( IVT+( QSTART-1 )*N ), N,
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$ Q( IU+( QSTART-1 )*N ), N,
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$ Q( IU+( QSTART-1 )*N ), N, WORK( WSTART ),
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$ INFO )
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END IF
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GO TO 40
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END IF
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*
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IF( ICOMPQ.EQ.2 ) THEN
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CALL SLASET( 'A', N, N, ZERO, ONE, U, LDU )
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CALL SLASET( 'A', N, N, ZERO, ONE, VT, LDVT )
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END IF
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*
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* Scale.
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*
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ORGNRM = SLANST( 'M', N, D, E )
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IF( ORGNRM.EQ.ZERO )
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$ RETURN
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CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, IERR )
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CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, NM1, 1, E, NM1, IERR )
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*
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EPS = SLAMCH( 'Epsilon' )
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*
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MLVL = INT( LOG( REAL( N ) / REAL( SMLSIZ+1 ) ) / LOG( TWO ) ) + 1
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SMLSZP = SMLSIZ + 1
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*
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IF( ICOMPQ.EQ.1 ) THEN
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IU = 1
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IVT = 1 + SMLSIZ
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DIFL = IVT + SMLSZP
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DIFR = DIFL + MLVL
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Z = DIFR + MLVL*2
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IC = Z + MLVL
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IS = IC + 1
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POLES = IS + 1
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GIVNUM = POLES + 2*MLVL
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*
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K = 1
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GIVPTR = 2
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PERM = 3
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GIVCOL = PERM + MLVL
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END IF
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*
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DO 20 I = 1, N
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IF( ABS( D( I ) ).LT.EPS ) THEN
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D( I ) = SIGN( EPS, D( I ) )
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END IF
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20 CONTINUE
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*
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START = 1
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SQRE = 0
|
||
|
*
|
||
|
DO 30 I = 1, NM1
|
||
|
IF( ( ABS( E( I ) ).LT.EPS ) .OR. ( I.EQ.NM1 ) ) THEN
|
||
|
*
|
||
|
* Subproblem found. First determine its size and then
|
||
|
* apply divide and conquer on it.
|
||
|
*
|
||
|
IF( I.LT.NM1 ) THEN
|
||
|
*
|
||
|
* A subproblem with E(I) small for I < NM1.
|
||
|
*
|
||
|
NSIZE = I - START + 1
|
||
|
ELSE IF( ABS( E( I ) ).GE.EPS ) THEN
|
||
|
*
|
||
|
* A subproblem with E(NM1) not too small but I = NM1.
|
||
|
*
|
||
|
NSIZE = N - START + 1
|
||
|
ELSE
|
||
|
*
|
||
|
* A subproblem with E(NM1) small. This implies an
|
||
|
* 1-by-1 subproblem at D(N). Solve this 1-by-1 problem
|
||
|
* first.
|
||
|
*
|
||
|
NSIZE = I - START + 1
|
||
|
IF( ICOMPQ.EQ.2 ) THEN
|
||
|
U( N, N ) = SIGN( ONE, D( N ) )
|
||
|
VT( N, N ) = ONE
|
||
|
ELSE IF( ICOMPQ.EQ.1 ) THEN
|
||
|
Q( N+( QSTART-1 )*N ) = SIGN( ONE, D( N ) )
|
||
|
Q( N+( SMLSIZ+QSTART-1 )*N ) = ONE
|
||
|
END IF
|
||
|
D( N ) = ABS( D( N ) )
|
||
|
END IF
|
||
|
IF( ICOMPQ.EQ.2 ) THEN
|
||
|
CALL SLASD0( NSIZE, SQRE, D( START ), E( START ),
|
||
|
$ U( START, START ), LDU, VT( START, START ),
|
||
|
$ LDVT, SMLSIZ, IWORK, WORK( WSTART ), INFO )
|
||
|
ELSE
|
||
|
CALL SLASDA( ICOMPQ, SMLSIZ, NSIZE, SQRE, D( START ),
|
||
|
$ E( START ), Q( START+( IU+QSTART-2 )*N ), N,
|
||
|
$ Q( START+( IVT+QSTART-2 )*N ),
|
||
|
$ IQ( START+K*N ), Q( START+( DIFL+QSTART-2 )*
|
||
|
$ N ), Q( START+( DIFR+QSTART-2 )*N ),
|
||
|
$ Q( START+( Z+QSTART-2 )*N ),
|
||
|
$ Q( START+( POLES+QSTART-2 )*N ),
|
||
|
$ IQ( START+GIVPTR*N ), IQ( START+GIVCOL*N ),
|
||
|
$ N, IQ( START+PERM*N ),
|
||
|
$ Q( START+( GIVNUM+QSTART-2 )*N ),
|
||
|
$ Q( START+( IC+QSTART-2 )*N ),
|
||
|
$ Q( START+( IS+QSTART-2 )*N ),
|
||
|
$ WORK( WSTART ), IWORK, INFO )
|
||
|
END IF
|
||
|
IF( INFO.NE.0 ) THEN
|
||
|
RETURN
|
||
|
END IF
|
||
|
START = I + 1
|
||
|
END IF
|
||
|
30 CONTINUE
|
||
|
*
|
||
|
* Unscale
|
||
|
*
|
||
|
CALL SLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, IERR )
|
||
|
40 CONTINUE
|
||
|
*
|
||
|
* Use Selection Sort to minimize swaps of singular vectors
|
||
|
*
|
||
|
DO 60 II = 2, N
|
||
|
I = II - 1
|
||
|
KK = I
|
||
|
P = D( I )
|
||
|
DO 50 J = II, N
|
||
|
IF( D( J ).GT.P ) THEN
|
||
|
KK = J
|
||
|
P = D( J )
|
||
|
END IF
|
||
|
50 CONTINUE
|
||
|
IF( KK.NE.I ) THEN
|
||
|
D( KK ) = D( I )
|
||
|
D( I ) = P
|
||
|
IF( ICOMPQ.EQ.1 ) THEN
|
||
|
IQ( I ) = KK
|
||
|
ELSE IF( ICOMPQ.EQ.2 ) THEN
|
||
|
CALL SSWAP( N, U( 1, I ), 1, U( 1, KK ), 1 )
|
||
|
CALL SSWAP( N, VT( I, 1 ), LDVT, VT( KK, 1 ), LDVT )
|
||
|
END IF
|
||
|
ELSE IF( ICOMPQ.EQ.1 ) THEN
|
||
|
IQ( I ) = I
|
||
|
END IF
|
||
|
60 CONTINUE
|
||
|
*
|
||
|
* If ICOMPQ = 1, use IQ(N,1) as the indicator for UPLO
|
||
|
*
|
||
|
IF( ICOMPQ.EQ.1 ) THEN
|
||
|
IF( IUPLO.EQ.1 ) THEN
|
||
|
IQ( N ) = 1
|
||
|
ELSE
|
||
|
IQ( N ) = 0
|
||
|
END IF
|
||
|
END IF
|
||
|
*
|
||
|
* If B is lower bidiagonal, update U by those Givens rotations
|
||
|
* which rotated B to be upper bidiagonal
|
||
|
*
|
||
|
IF( ( IUPLO.EQ.2 ) .AND. ( ICOMPQ.EQ.2 ) )
|
||
|
$ CALL SLASR( 'L', 'V', 'B', N, N, WORK( 1 ), WORK( N ), U, LDU )
|
||
|
*
|
||
|
RETURN
|
||
|
*
|
||
|
* End of SBDSDC
|
||
|
*
|
||
|
END
|