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502 lines
15 KiB
502 lines
15 KiB
*> \brief <b> ZGGSVD3 computes the singular value decomposition (SVD) for OTHER matrices</b>
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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 ZGGSVD3 + dependencies
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/zggsvd3.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/zggsvd3.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/zggsvd3.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 ZGGSVD3( JOBU, JOBV, JOBQ, M, N, P, K, L, A, LDA, B,
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* LDB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ, WORK,
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* LWORK, RWORK, IWORK, INFO )
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*
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* .. Scalar Arguments ..
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* CHARACTER JOBQ, JOBU, JOBV
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* INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N, P, LWORK
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* ..
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* .. Array Arguments ..
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* INTEGER IWORK( * )
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* DOUBLE PRECISION ALPHA( * ), BETA( * ), RWORK( * )
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* COMPLEX*16 A( LDA, * ), B( LDB, * ), Q( LDQ, * ),
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* $ U( LDU, * ), V( LDV, * ), 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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*> ZGGSVD3 computes the generalized singular value decomposition (GSVD)
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*> of an M-by-N complex matrix A and P-by-N complex matrix B:
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*>
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*> U**H*A*Q = D1*( 0 R ), V**H*B*Q = D2*( 0 R )
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*>
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*> where U, V and Q are unitary matrices.
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*> Let K+L = the effective numerical rank of the
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*> matrix (A**H,B**H)**H, then R is a (K+L)-by-(K+L) nonsingular upper
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*> triangular matrix, D1 and D2 are M-by-(K+L) and P-by-(K+L) "diagonal"
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*> matrices and of the following structures, respectively:
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*>
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*> If M-K-L >= 0,
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*>
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*> K L
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*> D1 = K ( I 0 )
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*> L ( 0 C )
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*> M-K-L ( 0 0 )
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*>
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*> K L
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*> D2 = L ( 0 S )
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*> P-L ( 0 0 )
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*>
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*> N-K-L K L
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*> ( 0 R ) = K ( 0 R11 R12 )
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*> L ( 0 0 R22 )
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*> where
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*>
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*> C = diag( ALPHA(K+1), ... , ALPHA(K+L) ),
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*> S = diag( BETA(K+1), ... , BETA(K+L) ),
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*> C**2 + S**2 = I.
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*>
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*> R is stored in A(1:K+L,N-K-L+1:N) on exit.
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*>
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*> If M-K-L < 0,
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*>
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*> K M-K K+L-M
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*> D1 = K ( I 0 0 )
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*> M-K ( 0 C 0 )
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*>
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*> K M-K K+L-M
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*> D2 = M-K ( 0 S 0 )
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*> K+L-M ( 0 0 I )
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*> P-L ( 0 0 0 )
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*>
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*> N-K-L K M-K K+L-M
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*> ( 0 R ) = K ( 0 R11 R12 R13 )
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*> M-K ( 0 0 R22 R23 )
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*> K+L-M ( 0 0 0 R33 )
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*>
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*> where
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*>
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*> C = diag( ALPHA(K+1), ... , ALPHA(M) ),
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*> S = diag( BETA(K+1), ... , BETA(M) ),
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*> C**2 + S**2 = I.
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*>
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*> (R11 R12 R13 ) is stored in A(1:M, N-K-L+1:N), and R33 is stored
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*> ( 0 R22 R23 )
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*> in B(M-K+1:L,N+M-K-L+1:N) on exit.
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*>
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*> The routine computes C, S, R, and optionally the unitary
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*> transformation matrices U, V and Q.
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*>
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*> In particular, if B is an N-by-N nonsingular matrix, then the GSVD of
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*> A and B implicitly gives the SVD of A*inv(B):
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*> A*inv(B) = U*(D1*inv(D2))*V**H.
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*> If ( A**H,B**H)**H has orthonormal columns, then the GSVD of A and B is also
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*> equal to the CS decomposition of A and B. Furthermore, the GSVD can
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*> be used to derive the solution of the eigenvalue problem:
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*> A**H*A x = lambda* B**H*B x.
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*> In some literature, the GSVD of A and B is presented in the form
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*> U**H*A*X = ( 0 D1 ), V**H*B*X = ( 0 D2 )
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*> where U and V are orthogonal and X is nonsingular, and D1 and D2 are
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*> ``diagonal''. The former GSVD form can be converted to the latter
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*> form by taking the nonsingular matrix X as
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*>
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*> X = Q*( I 0 )
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*> ( 0 inv(R) )
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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] JOBU
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*> \verbatim
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*> JOBU is CHARACTER*1
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*> = 'U': Unitary matrix U is computed;
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*> = 'N': U is not computed.
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*> \endverbatim
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*>
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*> \param[in] JOBV
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*> \verbatim
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*> JOBV is CHARACTER*1
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*> = 'V': Unitary matrix V is computed;
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*> = 'N': V is not computed.
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*> \endverbatim
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*>
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*> \param[in] JOBQ
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*> \verbatim
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*> JOBQ is CHARACTER*1
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*> = 'Q': Unitary matrix Q is computed;
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*> = 'N': Q is not computed.
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*> \endverbatim
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*>
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*> \param[in] M
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*> \verbatim
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*> M is INTEGER
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*> The number of rows of the matrix A. M >= 0.
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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 number of columns of the matrices A and B. N >= 0.
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*> \endverbatim
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*>
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*> \param[in] P
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*> \verbatim
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*> P is INTEGER
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*> The number of rows of the matrix B. P >= 0.
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*> \endverbatim
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*>
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*> \param[out] K
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*> \verbatim
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*> K is INTEGER
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*> \endverbatim
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*>
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*> \param[out] L
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*> \verbatim
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*> L is INTEGER
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*>
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*> On exit, K and L specify the dimension of the subblocks
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*> described in Purpose.
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*> K + L = effective numerical rank of (A**H,B**H)**H.
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*> \endverbatim
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*>
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*> \param[in,out] A
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*> \verbatim
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*> A is COMPLEX*16 array, dimension (LDA,N)
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*> On entry, the M-by-N matrix A.
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*> On exit, A contains the triangular matrix R, or part of R.
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*> See Purpose for details.
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*> \endverbatim
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*>
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*> \param[in] LDA
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*> \verbatim
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*> LDA is INTEGER
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*> The leading dimension of the array A. LDA >= max(1,M).
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*> \endverbatim
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*>
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*> \param[in,out] B
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*> \verbatim
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*> B is COMPLEX*16 array, dimension (LDB,N)
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*> On entry, the P-by-N matrix B.
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*> On exit, B contains part of the triangular matrix R if
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*> M-K-L < 0. See Purpose for details.
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*> \endverbatim
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*>
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*> \param[in] LDB
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*> \verbatim
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*> LDB is INTEGER
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*> The leading dimension of the array B. LDB >= max(1,P).
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*> \endverbatim
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*>
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*> \param[out] ALPHA
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*> \verbatim
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*> ALPHA is DOUBLE PRECISION array, dimension (N)
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*> \endverbatim
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*>
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*> \param[out] BETA
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*> \verbatim
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*> BETA is DOUBLE PRECISION array, dimension (N)
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*>
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*> On exit, ALPHA and BETA contain the generalized singular
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*> value pairs of A and B;
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*> ALPHA(1:K) = 1,
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*> BETA(1:K) = 0,
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*> and if M-K-L >= 0,
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*> ALPHA(K+1:K+L) = C,
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*> BETA(K+1:K+L) = S,
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*> or if M-K-L < 0,
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*> ALPHA(K+1:M)=C, ALPHA(M+1:K+L)=0
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*> BETA(K+1:M) =S, BETA(M+1:K+L) =1
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*> and
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*> ALPHA(K+L+1:N) = 0
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*> BETA(K+L+1:N) = 0
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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 COMPLEX*16 array, dimension (LDU,M)
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*> If JOBU = 'U', U contains the M-by-M unitary matrix U.
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*> If JOBU = 'N', 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 >= max(1,M) if
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*> JOBU = 'U'; LDU >= 1 otherwise.
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*> \endverbatim
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*>
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*> \param[out] V
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*> \verbatim
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*> V is COMPLEX*16 array, dimension (LDV,P)
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*> If JOBV = 'V', V contains the P-by-P unitary matrix V.
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*> If JOBV = 'N', V is not referenced.
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*> \endverbatim
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*>
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*> \param[in] LDV
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*> \verbatim
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*> LDV is INTEGER
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*> The leading dimension of the array V. LDV >= max(1,P) if
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*> JOBV = 'V'; LDV >= 1 otherwise.
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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 COMPLEX*16 array, dimension (LDQ,N)
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*> If JOBQ = 'Q', Q contains the N-by-N unitary matrix Q.
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*> If JOBQ = 'N', Q is not referenced.
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*> \endverbatim
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*>
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*> \param[in] LDQ
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*> \verbatim
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*> LDQ is INTEGER
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*> The leading dimension of the array Q. LDQ >= max(1,N) if
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*> JOBQ = 'Q'; LDQ >= 1 otherwise.
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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 COMPLEX*16 array, dimension (MAX(1,LWORK))
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*> On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
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*> \endverbatim
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*>
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*> \param[in] LWORK
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*> \verbatim
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*> LWORK is INTEGER
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*> The dimension of the array WORK.
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*>
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*> If LWORK = -1, then a workspace query is assumed; the routine
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*> only calculates the optimal size of the WORK array, returns
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*> this value as the first entry of the WORK array, and no error
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*> message related to LWORK is issued by XERBLA.
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*> \endverbatim
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*>
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*> \param[out] RWORK
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*> \verbatim
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*> RWORK is DOUBLE PRECISION array, dimension (2*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 (N)
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*> On exit, IWORK stores the sorting information. More
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*> precisely, the following loop will sort ALPHA
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*> for I = K+1, min(M,K+L)
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*> swap ALPHA(I) and ALPHA(IWORK(I))
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*> endfor
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*> such that ALPHA(1) >= ALPHA(2) >= ... >= ALPHA(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: if INFO = 1, the Jacobi-type procedure failed to
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*> converge. For further details, see subroutine ZTGSJA.
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*> \endverbatim
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*
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*> \par Internal Parameters:
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* =========================
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*>
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*> \verbatim
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*> TOLA DOUBLE PRECISION
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*> TOLB DOUBLE PRECISION
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*> TOLA and TOLB are the thresholds to determine the effective
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*> rank of (A**H,B**H)**H. Generally, they are set to
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*> TOLA = MAX(M,N)*norm(A)*MACHEPS,
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*> TOLB = MAX(P,N)*norm(B)*MACHEPS.
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*> The size of TOLA and TOLB may affect the size of backward
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*> errors of the decomposition.
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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 complex16GEsing
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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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*> \par Further Details:
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* =====================
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*>
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*> ZGGSVD3 replaces the deprecated subroutine ZGGSVD.
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*>
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* =====================================================================
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SUBROUTINE ZGGSVD3( JOBU, JOBV, JOBQ, M, N, P, K, L, A, LDA, B,
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$ LDB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ,
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$ WORK, LWORK, RWORK, IWORK, INFO )
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*
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* -- LAPACK driver 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 JOBQ, JOBU, JOBV
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INTEGER INFO, K, L, LDA, LDB, LDQ, LDU, LDV, M, N, P,
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$ LWORK
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* ..
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* .. Array Arguments ..
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INTEGER IWORK( * )
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DOUBLE PRECISION ALPHA( * ), BETA( * ), RWORK( * )
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COMPLEX*16 A( LDA, * ), B( LDB, * ), Q( LDQ, * ),
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$ U( LDU, * ), V( LDV, * ), WORK( * )
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* ..
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*
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* =====================================================================
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*
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* .. Local Scalars ..
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LOGICAL WANTQ, WANTU, WANTV, LQUERY
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INTEGER I, IBND, ISUB, J, NCYCLE, LWKOPT
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DOUBLE PRECISION ANORM, BNORM, SMAX, TEMP, TOLA, TOLB, ULP, UNFL
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* ..
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* .. External Functions ..
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LOGICAL LSAME
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DOUBLE PRECISION DLAMCH, ZLANGE
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EXTERNAL LSAME, DLAMCH, ZLANGE
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* ..
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* .. External Subroutines ..
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EXTERNAL DCOPY, XERBLA, ZGGSVP3, ZTGSJA
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* ..
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* .. Intrinsic Functions ..
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INTRINSIC MAX, MIN
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* ..
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* .. Executable Statements ..
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*
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* Decode and test the input parameters
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*
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WANTU = LSAME( JOBU, 'U' )
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WANTV = LSAME( JOBV, 'V' )
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WANTQ = LSAME( JOBQ, 'Q' )
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LQUERY = ( LWORK.EQ.-1 )
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LWKOPT = 1
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*
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* Test the input arguments
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*
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INFO = 0
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IF( .NOT.( WANTU .OR. LSAME( JOBU, 'N' ) ) ) THEN
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INFO = -1
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ELSE IF( .NOT.( WANTV .OR. LSAME( JOBV, 'N' ) ) ) THEN
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INFO = -2
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ELSE IF( .NOT.( WANTQ .OR. LSAME( JOBQ, 'N' ) ) ) THEN
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INFO = -3
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ELSE IF( M.LT.0 ) THEN
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INFO = -4
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ELSE IF( N.LT.0 ) THEN
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INFO = -5
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ELSE IF( P.LT.0 ) THEN
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INFO = -6
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ELSE IF( LDA.LT.MAX( 1, M ) ) THEN
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INFO = -10
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ELSE IF( LDB.LT.MAX( 1, P ) ) THEN
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INFO = -12
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ELSE IF( LDU.LT.1 .OR. ( WANTU .AND. LDU.LT.M ) ) THEN
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INFO = -16
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ELSE IF( LDV.LT.1 .OR. ( WANTV .AND. LDV.LT.P ) ) THEN
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INFO = -18
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ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.N ) ) THEN
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INFO = -20
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ELSE IF( LWORK.LT.1 .AND. .NOT.LQUERY ) THEN
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INFO = -24
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END IF
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*
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* Compute workspace
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*
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IF( INFO.EQ.0 ) THEN
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CALL ZGGSVP3( JOBU, JOBV, JOBQ, M, P, N, A, LDA, B, LDB, TOLA,
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$ TOLB, K, L, U, LDU, V, LDV, Q, LDQ, IWORK, RWORK,
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$ WORK, WORK, -1, INFO )
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LWKOPT = N + INT( WORK( 1 ) )
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LWKOPT = MAX( 2*N, LWKOPT )
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LWKOPT = MAX( 1, LWKOPT )
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WORK( 1 ) = DCMPLX( LWKOPT )
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END IF
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*
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IF( INFO.NE.0 ) THEN
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CALL XERBLA( 'ZGGSVD3', -INFO )
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RETURN
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END IF
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IF( LQUERY ) THEN
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RETURN
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ENDIF
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*
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* Compute the Frobenius norm of matrices A and B
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*
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ANORM = ZLANGE( '1', M, N, A, LDA, RWORK )
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BNORM = ZLANGE( '1', P, N, B, LDB, RWORK )
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*
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* Get machine precision and set up threshold for determining
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* the effective numerical rank of the matrices A and B.
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*
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ULP = DLAMCH( 'Precision' )
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UNFL = DLAMCH( 'Safe Minimum' )
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TOLA = MAX( M, N )*MAX( ANORM, UNFL )*ULP
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TOLB = MAX( P, N )*MAX( BNORM, UNFL )*ULP
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*
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CALL ZGGSVP3( JOBU, JOBV, JOBQ, M, P, N, A, LDA, B, LDB, TOLA,
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$ TOLB, K, L, U, LDU, V, LDV, Q, LDQ, IWORK, RWORK,
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$ WORK, WORK( N+1 ), LWORK-N, INFO )
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*
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* Compute the GSVD of two upper "triangular" matrices
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*
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CALL ZTGSJA( JOBU, JOBV, JOBQ, M, P, N, K, L, A, LDA, B, LDB,
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|
$ TOLA, TOLB, ALPHA, BETA, U, LDU, V, LDV, Q, LDQ,
|
|
$ WORK, NCYCLE, INFO )
|
|
*
|
|
* Sort the singular values and store the pivot indices in IWORK
|
|
* Copy ALPHA to RWORK, then sort ALPHA in RWORK
|
|
*
|
|
CALL DCOPY( N, ALPHA, 1, RWORK, 1 )
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|
IBND = MIN( L, M-K )
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|
DO 20 I = 1, IBND
|
|
*
|
|
* Scan for largest ALPHA(K+I)
|
|
*
|
|
ISUB = I
|
|
SMAX = RWORK( K+I )
|
|
DO 10 J = I + 1, IBND
|
|
TEMP = RWORK( K+J )
|
|
IF( TEMP.GT.SMAX ) THEN
|
|
ISUB = J
|
|
SMAX = TEMP
|
|
END IF
|
|
10 CONTINUE
|
|
IF( ISUB.NE.I ) THEN
|
|
RWORK( K+ISUB ) = RWORK( K+I )
|
|
RWORK( K+I ) = SMAX
|
|
IWORK( K+I ) = K + ISUB
|
|
ELSE
|
|
IWORK( K+I ) = K + I
|
|
END IF
|
|
20 CONTINUE
|
|
*
|
|
WORK( 1 ) = DCMPLX( LWKOPT )
|
|
RETURN
|
|
*
|
|
* End of ZGGSVD3
|
|
*
|
|
END
|
|
|