414 lines
		
	
	
		
			13 KiB
		
	
	
	
		
			Fortran
		
	
	
	
			
		
		
	
	
			414 lines
		
	
	
		
			13 KiB
		
	
	
	
		
			Fortran
		
	
	
	
*> \brief \b SLASDQ computes the SVD of a real bidiagonal matrix with diagonal d and off-diagonal e. Used by 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 SLASDQ + dependencies 
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/slasdq.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/slasdq.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/slasdq.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 SLASDQ( UPLO, SQRE, N, NCVT, NRU, NCC, D, E, VT, LDVT,
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*                          U, LDU, C, LDC, WORK, INFO )
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* 
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*       .. Scalar Arguments ..
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*       CHARACTER          UPLO
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*       INTEGER            INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU, SQRE
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*       ..
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*       .. Array Arguments ..
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*       REAL               C( LDC, * ), D( * ), E( * ), 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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*> SLASDQ computes the singular value decomposition (SVD) of a real
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*> (upper or lower) bidiagonal matrix with diagonal D and offdiagonal
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*> E, accumulating the transformations if desired. Letting B denote
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*> the input bidiagonal matrix, the algorithm computes orthogonal
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*> matrices Q and P such that B = Q * S * P**T (P**T denotes the transpose
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*> of P). The singular values S are overwritten on D.
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*>
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*> The input matrix U  is changed to U  * Q  if desired.
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*> The input matrix VT is changed to P**T * VT if desired.
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*> The input matrix C  is changed to Q**T * C  if desired.
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*>
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*> See "Computing  Small Singular Values of Bidiagonal Matrices With
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*> Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan,
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*> LAPACK Working Note #3, for a detailed description of the algorithm.
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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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*>        On entry, UPLO specifies whether the input bidiagonal matrix
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*>        is upper or lower bidiagonal, and wether it is square are
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*>        not.
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*>           UPLO = 'U' or 'u'   B is upper bidiagonal.
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*>           UPLO = 'L' or 'l'   B is lower bidiagonal.
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*> \endverbatim
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*>
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*> \param[in] SQRE
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*> \verbatim
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*>          SQRE is INTEGER
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*>        = 0: then the input matrix is N-by-N.
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*>        = 1: then the input matrix is N-by-(N+1) if UPLU = 'U' and
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*>             (N+1)-by-N if UPLU = 'L'.
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*>
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*>        The bidiagonal matrix has
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*>        N = NL + NR + 1 rows and
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*>        M = N + SQRE >= N columns.
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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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*>        On entry, N specifies the number of rows and columns
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*>        in the matrix. N must be at least 0.
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*> \endverbatim
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*>
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*> \param[in] NCVT
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*> \verbatim
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*>          NCVT is INTEGER
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*>        On entry, NCVT specifies the number of columns of
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*>        the matrix VT. NCVT must be at least 0.
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*> \endverbatim
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*>
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*> \param[in] NRU
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*> \verbatim
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*>          NRU is INTEGER
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*>        On entry, NRU specifies the number of rows of
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*>        the matrix U. NRU must be at least 0.
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*> \endverbatim
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*>
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*> \param[in] NCC
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*> \verbatim
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*>          NCC is INTEGER
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*>        On entry, NCC specifies the number of columns of
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*>        the matrix C. NCC must be at least 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, D contains the diagonal entries of the
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*>        bidiagonal matrix whose SVD is desired. On normal exit,
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*>        D contains the singular values in ascending order.
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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.
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*>        dimension is (N-1) if SQRE = 0 and N if SQRE = 1.
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*>        On entry, the entries of E contain the offdiagonal entries
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*>        of the bidiagonal matrix whose SVD is desired. On normal
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*>        exit, E will contain 0. If the algorithm does not converge,
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*>        D and E will contain the diagonal and superdiagonal entries
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*>        of a bidiagonal matrix orthogonally equivalent to the one
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*>        given as input.
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*> \endverbatim
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*>
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*> \param[in,out] VT
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*> \verbatim
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*>          VT is REAL array, dimension (LDVT, NCVT)
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*>        On entry, contains a matrix which on exit has been
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*>        premultiplied by P**T, dimension N-by-NCVT if SQRE = 0
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*>        and (N+1)-by-NCVT if SQRE = 1 (not referenced if NCVT=0).
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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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*>        On entry, LDVT specifies the leading dimension of VT as
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*>        declared in the calling (sub) program. LDVT must be at
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*>        least 1. If NCVT is nonzero LDVT must also be at least N.
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*> \endverbatim
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*>
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*> \param[in,out] U
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*> \verbatim
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*>          U is REAL array, dimension (LDU, N)
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*>        On entry, contains a  matrix which on exit has been
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*>        postmultiplied by Q, dimension NRU-by-N if SQRE = 0
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*>        and NRU-by-(N+1) if SQRE = 1 (not referenced if NRU=0).
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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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*>        On entry, LDU  specifies the leading dimension of U as
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*>        declared in the calling (sub) program. LDU must be at
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*>        least max( 1, NRU ) .
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*> \endverbatim
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*>
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*> \param[in,out] C
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*> \verbatim
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*>          C is REAL array, dimension (LDC, NCC)
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*>        On entry, contains an N-by-NCC matrix which on exit
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*>        has been premultiplied by Q**T  dimension N-by-NCC if SQRE = 0
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*>        and (N+1)-by-NCC if SQRE = 1 (not referenced if NCC=0).
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*> \endverbatim
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*>
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*> \param[in] LDC
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*> \verbatim
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*>          LDC is INTEGER
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*>        On entry, LDC  specifies the leading dimension of C as
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*>        declared in the calling (sub) program. LDC must be at
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*>        least 1. If NCC is nonzero, LDC must also be at least N.
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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 (4*N)
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*>        Workspace. Only referenced if one of NCVT, NRU, or NCC is
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*>        nonzero, and if N is at least 2.
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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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*>        On exit, a value of 0 indicates a successful exit.
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*>        If INFO < 0, argument number -INFO is illegal.
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*>        If INFO > 0, the algorithm did not converge, and INFO
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*>        specifies how many superdiagonals did not converge.
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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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*> \date September 2012
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*
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*> \ingroup auxOTHERauxiliary
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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 SLASDQ( UPLO, SQRE, N, NCVT, NRU, NCC, D, E, VT, LDVT,
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     $                   U, LDU, C, LDC, WORK, INFO )
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*
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*  -- LAPACK auxiliary routine (version 3.4.2) --
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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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*     September 2012
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*
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*     .. Scalar Arguments ..
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      CHARACTER          UPLO
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      INTEGER            INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU, SQRE
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*     ..
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*     .. Array Arguments ..
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      REAL               C( LDC, * ), D( * ), E( * ), 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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*
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*     .. Parameters ..
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      REAL               ZERO
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      PARAMETER          ( ZERO = 0.0E+0 )
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*     ..
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*     .. Local Scalars ..
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      LOGICAL            ROTATE
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      INTEGER            I, ISUB, IUPLO, J, NP1, SQRE1
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      REAL               CS, R, SMIN, SN
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*     ..
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*     .. External Subroutines ..
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      EXTERNAL           SBDSQR, SLARTG, SLASR, SSWAP, XERBLA
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*     ..
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*     .. External Functions ..
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      LOGICAL            LSAME
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      EXTERNAL           LSAME
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*     ..
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*     .. Intrinsic Functions ..
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      INTRINSIC          MAX
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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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      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( IUPLO.EQ.0 ) THEN
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         INFO = -1
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      ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) 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( NCVT.LT.0 ) THEN
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         INFO = -4
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      ELSE IF( NRU.LT.0 ) THEN
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         INFO = -5
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      ELSE IF( NCC.LT.0 ) THEN
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         INFO = -6
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      ELSE IF( ( NCVT.EQ.0 .AND. LDVT.LT.1 ) .OR.
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     $         ( NCVT.GT.0 .AND. LDVT.LT.MAX( 1, N ) ) ) THEN
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         INFO = -10
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      ELSE IF( LDU.LT.MAX( 1, NRU ) ) THEN
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         INFO = -12
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      ELSE IF( ( NCC.EQ.0 .AND. LDC.LT.1 ) .OR.
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     $         ( NCC.GT.0 .AND. LDC.LT.MAX( 1, N ) ) ) THEN
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         INFO = -14
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      END IF
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      IF( INFO.NE.0 ) THEN
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         CALL XERBLA( 'SLASDQ', -INFO )
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         RETURN
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      END IF
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      IF( N.EQ.0 )
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     $   RETURN
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*
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*     ROTATE is true if any singular vectors desired, false otherwise
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*
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      ROTATE = ( NCVT.GT.0 ) .OR. ( NRU.GT.0 ) .OR. ( NCC.GT.0 )
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      NP1 = N + 1
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      SQRE1 = SQRE
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*
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*     If matrix non-square upper bidiagonal, rotate to be lower
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*     bidiagonal.  The rotations are on the right.
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*
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      IF( ( IUPLO.EQ.1 ) .AND. ( SQRE1.EQ.1 ) ) THEN
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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( ROTATE ) THEN
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               WORK( I ) = CS
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               WORK( N+I ) = SN
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            END IF
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   10    CONTINUE
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         CALL SLARTG( D( N ), E( N ), CS, SN, R )
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         D( N ) = R
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         E( N ) = ZERO
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         IF( ROTATE ) THEN
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            WORK( N ) = CS
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            WORK( N+N ) = SN
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         END IF
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         IUPLO = 2
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         SQRE1 = 0
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*
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*        Update singular vectors if desired.
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*
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         IF( NCVT.GT.0 )
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     $      CALL SLASR( 'L', 'V', 'F', NP1, NCVT, WORK( 1 ),
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     $                  WORK( NP1 ), VT, LDVT )
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      END IF
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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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      IF( IUPLO.EQ.2 ) THEN
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         DO 20 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( ROTATE ) THEN
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               WORK( I ) = CS
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               WORK( N+I ) = SN
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            END IF
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   20    CONTINUE
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*
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*        If matrix (N+1)-by-N lower bidiagonal, one additional
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*        rotation is needed.
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*
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         IF( SQRE1.EQ.1 ) THEN
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            CALL SLARTG( D( N ), E( N ), CS, SN, R )
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            D( N ) = R
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            IF( ROTATE ) THEN
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               WORK( N ) = CS
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               WORK( N+N ) = SN
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            END IF
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         END IF
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*
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*        Update singular vectors if desired.
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*
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         IF( NRU.GT.0 ) THEN
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            IF( SQRE1.EQ.0 ) THEN
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               CALL SLASR( 'R', 'V', 'F', NRU, N, WORK( 1 ),
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     $                     WORK( NP1 ), U, LDU )
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            ELSE
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               CALL SLASR( 'R', 'V', 'F', NRU, NP1, WORK( 1 ),
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     $                     WORK( NP1 ), U, LDU )
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            END IF
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         END IF
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         IF( NCC.GT.0 ) THEN
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            IF( SQRE1.EQ.0 ) THEN
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               CALL SLASR( 'L', 'V', 'F', N, NCC, WORK( 1 ),
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     $                     WORK( NP1 ), C, LDC )
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            ELSE
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               CALL SLASR( 'L', 'V', 'F', NP1, NCC, WORK( 1 ),
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     $                     WORK( NP1 ), C, LDC )
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            END IF
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         END IF
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      END IF
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*
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*     Call SBDSQR to compute the SVD of the reduced real
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*     N-by-N upper bidiagonal matrix.
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*
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      CALL SBDSQR( 'U', N, NCVT, NRU, NCC, D, E, VT, LDVT, U, LDU, C,
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     $             LDC, WORK, INFO )
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*
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*     Sort the singular values into ascending order (insertion sort on
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*     singular values, but only one transposition per singular vector)
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*
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      DO 40 I = 1, N
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*
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*        Scan for smallest D(I).
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*
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         ISUB = I
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         SMIN = D( I )
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         DO 30 J = I + 1, N
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            IF( D( J ).LT.SMIN ) THEN
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               ISUB = J
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               SMIN = D( J )
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            END IF
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   30    CONTINUE
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         IF( ISUB.NE.I ) THEN
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*
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*           Swap singular values and vectors.
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*
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            D( ISUB ) = D( I )
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            D( I ) = SMIN
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            IF( NCVT.GT.0 )
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     $         CALL SSWAP( NCVT, VT( ISUB, 1 ), LDVT, VT( I, 1 ), LDVT )
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            IF( NRU.GT.0 )
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     $         CALL SSWAP( NRU, U( 1, ISUB ), 1, U( 1, I ), 1 )
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            IF( NCC.GT.0 )
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     $         CALL SSWAP( NCC, C( ISUB, 1 ), LDC, C( I, 1 ), LDC )
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         END IF
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   40 CONTINUE
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*
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      RETURN
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*
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*     End of SLASDQ
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*
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      END
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