714 lines
24 KiB
Fortran
714 lines
24 KiB
Fortran
*> \brief \b SLAQP2RK computes truncated QR factorization with column pivoting of a real matrix block using Level 2 BLAS and overwrites a real m-by-nrhs matrix B with Q**T * 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 SLAQP2RK + dependencies
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*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/slaqp2rk.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/slaqp2rk.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/slaqp2rk.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 SLAQP2RK( M, N, NRHS, IOFFSET, KMAX, ABSTOL, RELTOL,
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* $ KP1, MAXC2NRM, A, LDA, K, MAXC2NRMK,
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* $ RELMAXC2NRMK, JPIV, TAU, VN1, VN2, WORK,
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* $ INFO )
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* IMPLICIT NONE
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*
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* .. Scalar Arguments ..
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* INTEGER INFO, IOFFSET, KP1, K, KMAX, LDA, M, N, NRHS
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* REAL ABSTOL, MAXC2NRM, MAXC2NRMK, RELMAXC2NRMK,
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* $ RELTOL
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* ..
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* .. Array Arguments ..
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* INTEGER JPIV( * )
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* REAL A( LDA, * ), TAU( * ), VN1( * ), VN2( * ),
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* $ 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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*> SLAQP2RK computes a truncated (rank K) or full rank Householder QR
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*> factorization with column pivoting of a real matrix
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*> block A(IOFFSET+1:M,1:N) as
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*>
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*> A * P(K) = Q(K) * R(K).
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*>
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*> The routine uses Level 2 BLAS. The block A(1:IOFFSET,1:N)
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*> is accordingly pivoted, but not factorized.
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*>
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*> The routine also overwrites the right-hand-sides matrix block B
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*> stored in A(IOFFSET+1:M,N+1:N+NRHS) with Q(K)**T * B.
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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] 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 matrix A. N >= 0.
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*> \endverbatim
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*>
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*> \param[in] NRHS
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*> \verbatim
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*> NRHS is INTEGER
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*> The number of right hand sides, i.e., the number of
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*> columns of the matrix B. NRHS >= 0.
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*> \endverbatim
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*>
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*> \param[in] IOFFSET
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*> \verbatim
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*> IOFFSET is INTEGER
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*> The number of rows of the matrix A that must be pivoted
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*> but not factorized. IOFFSET >= 0.
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*>
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*> IOFFSET also represents the number of columns of the whole
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*> original matrix A_orig that have been factorized
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*> in the previous steps.
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*> \endverbatim
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*>
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*> \param[in] KMAX
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*> \verbatim
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*> KMAX is INTEGER
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*>
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*> The first factorization stopping criterion. KMAX >= 0.
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*>
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*> The maximum number of columns of the matrix A to factorize,
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*> i.e. the maximum factorization rank.
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*>
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*> a) If KMAX >= min(M-IOFFSET,N), then this stopping
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*> criterion is not used, factorize columns
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*> depending on ABSTOL and RELTOL.
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*>
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*> b) If KMAX = 0, then this stopping criterion is
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*> satisfied on input and the routine exits immediately.
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*> This means that the factorization is not performed,
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*> the matrices A and B and the arrays TAU, IPIV
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*> are not modified.
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*> \endverbatim
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*>
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*> \param[in] ABSTOL
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*> \verbatim
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*> ABSTOL is DOUBLE PRECISION, cannot be NaN.
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*>
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*> The second factorization stopping criterion.
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*>
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*> The absolute tolerance (stopping threshold) for
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*> maximum column 2-norm of the residual matrix.
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*> The algorithm converges (stops the factorization) when
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*> the maximum column 2-norm of the residual matrix
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*> is less than or equal to ABSTOL.
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*>
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*> a) If ABSTOL < 0.0, then this stopping criterion is not
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*> used, the routine factorizes columns depending
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*> on KMAX and RELTOL.
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*> This includes the case ABSTOL = -Inf.
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*>
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*> b) If 0.0 <= ABSTOL then the input value
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*> of ABSTOL is used.
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*> \endverbatim
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*>
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*> \param[in] RELTOL
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*> \verbatim
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*> RELTOL is DOUBLE PRECISION, cannot be NaN.
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*>
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*> The third factorization stopping criterion.
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*>
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*> The tolerance (stopping threshold) for the ratio of the
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*> maximum column 2-norm of the residual matrix to the maximum
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*> column 2-norm of the original matrix A_orig. The algorithm
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*> converges (stops the factorization), when this ratio is
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*> less than or equal to RELTOL.
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*>
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*> a) If RELTOL < 0.0, then this stopping criterion is not
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*> used, the routine factorizes columns depending
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*> on KMAX and ABSTOL.
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*> This includes the case RELTOL = -Inf.
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*>
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*> d) If 0.0 <= RELTOL then the input value of RELTOL
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*> is used.
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*> \endverbatim
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*>
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*> \param[in] KP1
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*> \verbatim
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*> KP1 is INTEGER
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*> The index of the column with the maximum 2-norm in
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*> the whole original matrix A_orig determined in the
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*> main routine SGEQP3RK. 1 <= KP1 <= N_orig_mat.
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*> \endverbatim
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*>
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*> \param[in] MAXC2NRM
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*> \verbatim
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*> MAXC2NRM is DOUBLE PRECISION
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*> The maximum column 2-norm of the whole original
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*> matrix A_orig computed in the main routine SGEQP3RK.
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*> MAXC2NRM >= 0.
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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 REAL array, dimension (LDA,N+NRHS)
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*> On entry:
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*> the M-by-N matrix A and M-by-NRHS matrix B, as in
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*>
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*> N NRHS
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*> array_A = M [ mat_A, mat_B ]
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*>
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*> On exit:
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*> 1. The elements in block A(IOFFSET+1:M,1:K) below
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*> the diagonal together with the array TAU represent
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*> the orthogonal matrix Q(K) as a product of elementary
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*> reflectors.
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*> 2. The upper triangular block of the matrix A stored
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*> in A(IOFFSET+1:M,1:K) is the triangular factor obtained.
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*> 3. The block of the matrix A stored in A(1:IOFFSET,1:N)
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*> has been accordingly pivoted, but not factorized.
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*> 4. The rest of the array A, block A(IOFFSET+1:M,K+1:N+NRHS).
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*> The left part A(IOFFSET+1:M,K+1:N) of this block
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*> contains the residual of the matrix A, and,
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*> if NRHS > 0, the right part of the block
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*> A(IOFFSET+1:M,N+1:N+NRHS) contains the block of
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*> the right-hand-side matrix B. Both these blocks have been
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*> updated by multiplication from the left by Q(K)**T.
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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[out] K
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*> \verbatim
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*> K is INTEGER
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*> Factorization rank of the matrix A, i.e. the rank of
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*> the factor R, which is the same as the number of non-zero
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*> rows of the factor R. 0 <= K <= min(M-IOFFSET,KMAX,N).
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*>
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*> K also represents the number of non-zero Householder
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*> vectors.
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*> \endverbatim
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*>
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*> \param[out] MAXC2NRMK
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*> \verbatim
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*> MAXC2NRMK is DOUBLE PRECISION
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*> The maximum column 2-norm of the residual matrix,
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*> when the factorization stopped at rank K. MAXC2NRMK >= 0.
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*> \endverbatim
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*>
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*> \param[out] RELMAXC2NRMK
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*> \verbatim
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*> RELMAXC2NRMK is DOUBLE PRECISION
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*> The ratio MAXC2NRMK / MAXC2NRM of the maximum column
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*> 2-norm of the residual matrix (when the factorization
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*> stopped at rank K) to the maximum column 2-norm of the
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*> whole original matrix A. RELMAXC2NRMK >= 0.
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*> \endverbatim
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*>
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*> \param[out] JPIV
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*> \verbatim
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*> JPIV is INTEGER array, dimension (N)
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*> Column pivot indices, for 1 <= j <= N, column j
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*> of the matrix A was interchanged with column JPIV(j).
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*> \endverbatim
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*>
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*> \param[out] TAU
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*> \verbatim
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*> TAU is REAL array, dimension (min(M-IOFFSET,N))
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*> The scalar factors of the elementary reflectors.
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*> \endverbatim
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*>
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*> \param[in,out] VN1
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*> \verbatim
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*> VN1 is REAL array, dimension (N)
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*> The vector with the partial column norms.
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*> \endverbatim
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*>
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*> \param[in,out] VN2
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*> \verbatim
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*> VN2 is REAL array, dimension (N)
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*> The vector with the exact column norms.
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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 (N-1)
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*> Used in SLARF subroutine to apply an elementary
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*> reflector from the left.
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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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*> 1) INFO = 0: successful exit.
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*> 2) If INFO = j_1, where 1 <= j_1 <= N, then NaN was
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*> detected and the routine stops the computation.
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*> The j_1-th column of the matrix A or the j_1-th
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*> element of array TAU contains the first occurrence
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*> of NaN in the factorization step K+1 ( when K columns
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*> have been factorized ).
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*>
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*> On exit:
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*> K is set to the number of
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*> factorized columns without
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*> exception.
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*> MAXC2NRMK is set to NaN.
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*> RELMAXC2NRMK is set to NaN.
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*> TAU(K+1:min(M,N)) is not set and contains undefined
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*> elements. If j_1=K+1, TAU(K+1)
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*> may contain NaN.
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*> 3) If INFO = j_2, where N+1 <= j_2 <= 2*N, then no NaN
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*> was detected, but +Inf (or -Inf) was detected and
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*> the routine continues the computation until completion.
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*> The (j_2-N)-th column of the matrix A contains the first
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*> occurrence of +Inf (or -Inf) in the factorization
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*> step K+1 ( when K columns have been factorized ).
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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 laqp2rk
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*
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*> \par References:
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* ================
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*> [1] A Level 3 BLAS QR factorization algorithm with column pivoting developed in 1996.
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*> G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain.
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*> X. Sun, Computer Science Dept., Duke University, USA.
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*> C. H. Bischof, Math. and Comp. Sci. Div., Argonne National Lab, USA.
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*> A BLAS-3 version of the QR factorization with column pivoting.
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*> LAPACK Working Note 114
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*> \htmlonly
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*> <a href="https://www.netlib.org/lapack/lawnspdf/lawn114.pdf">https://www.netlib.org/lapack/lawnspdf/lawn114.pdf</a>
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*> \endhtmlonly
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*> and in
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*> SIAM J. Sci. Comput., 19(5):1486-1494, Sept. 1998.
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*> \htmlonly
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*> <a href="https://doi.org/10.1137/S1064827595296732">https://doi.org/10.1137/S1064827595296732</a>
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*> \endhtmlonly
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*>
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*> [2] A partial column norm updating strategy developed in 2006.
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*> Z. Drmac and Z. Bujanovic, Dept. of Math., University of Zagreb, Croatia.
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*> On the failure of rank revealing QR factorization software – a case study.
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*> LAPACK Working Note 176.
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*> \htmlonly
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*> <a href="http://www.netlib.org/lapack/lawnspdf/lawn176.pdf">http://www.netlib.org/lapack/lawnspdf/lawn176.pdf</a>
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*> \endhtmlonly
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*> and in
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*> ACM Trans. Math. Softw. 35, 2, Article 12 (July 2008), 28 pages.
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*> \htmlonly
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*> <a href="https://doi.org/10.1145/1377612.1377616">https://doi.org/10.1145/1377612.1377616</a>
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*> \endhtmlonly
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*
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*> \par Contributors:
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* ==================
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*>
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*> \verbatim
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*>
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*> November 2023, Igor Kozachenko, James Demmel,
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*> EECS Department,
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*> University of California, Berkeley, USA.
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*>
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*> \endverbatim
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*
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* =====================================================================
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SUBROUTINE SLAQP2RK( M, N, NRHS, IOFFSET, KMAX, ABSTOL, RELTOL,
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$ KP1, MAXC2NRM, A, LDA, K, MAXC2NRMK,
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$ RELMAXC2NRMK, JPIV, TAU, VN1, VN2, WORK,
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$ INFO )
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IMPLICIT NONE
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*
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* -- LAPACK auxiliary 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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INTEGER INFO, IOFFSET, KP1, K, KMAX, LDA, M, N, NRHS
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REAL ABSTOL, MAXC2NRM, MAXC2NRMK, RELMAXC2NRMK,
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$ RELTOL
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* ..
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* .. Array Arguments ..
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INTEGER JPIV( * )
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REAL A( LDA, * ), TAU( * ), VN1( * ), VN2( * ),
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$ 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, ONE
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PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 )
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* ..
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* .. Local Scalars ..
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INTEGER I, ITEMP, J, JMAXC2NRM, KK, KP, MINMNFACT,
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$ MINMNUPDT
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REAL AIKK, HUGEVAL, TEMP, TEMP2, TOL3Z
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* ..
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* .. External Subroutines ..
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EXTERNAL SLARF, SLARFG, SSWAP
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* ..
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* .. Intrinsic Functions ..
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INTRINSIC ABS, MAX, MIN, SQRT
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* ..
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* .. External Functions ..
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LOGICAL SISNAN
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INTEGER ISAMAX
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REAL SLAMCH, SNRM2
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EXTERNAL SISNAN, SLAMCH, ISAMAX, SNRM2
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* ..
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* .. Executable Statements ..
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*
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* Initialize INFO
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*
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INFO = 0
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*
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* MINMNFACT in the smallest dimension of the submatrix
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* A(IOFFSET+1:M,1:N) to be factorized.
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*
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* MINMNUPDT is the smallest dimension
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* of the subarray A(IOFFSET+1:M,1:N+NRHS) to be udated, which
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* contains the submatrices A(IOFFSET+1:M,1:N) and
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* B(IOFFSET+1:M,1:NRHS) as column blocks.
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*
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MINMNFACT = MIN( M-IOFFSET, N )
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MINMNUPDT = MIN( M-IOFFSET, N+NRHS )
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KMAX = MIN( KMAX, MINMNFACT )
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TOL3Z = SQRT( SLAMCH( 'Epsilon' ) )
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HUGEVAL = SLAMCH( 'Overflow' )
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*
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* Compute the factorization, KK is the lomn loop index.
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*
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DO KK = 1, KMAX
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*
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I = IOFFSET + KK
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*
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IF( I.EQ.1 ) THEN
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*
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* ============================================================
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*
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* We are at the first column of the original whole matrix A,
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* therefore we use the computed KP1 and MAXC2NRM from the
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* main routine.
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*
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KP = KP1
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*
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* ============================================================
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*
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ELSE
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*
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* ============================================================
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*
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* Determine the pivot column in KK-th step, i.e. the index
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* of the column with the maximum 2-norm in the
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* submatrix A(I:M,K:N).
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*
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KP = ( KK-1 ) + ISAMAX( N-KK+1, VN1( KK ), 1 )
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*
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* Determine the maximum column 2-norm and the relative maximum
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* column 2-norm of the submatrix A(I:M,KK:N) in step KK.
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* RELMAXC2NRMK will be computed later, after somecondition
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* checks on MAXC2NRMK.
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*
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MAXC2NRMK = VN1( KP )
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*
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* ============================================================
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*
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* Check if the submatrix A(I:M,KK:N) contains NaN, and set
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* INFO parameter to the column number, where the first NaN
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* is found and return from the routine.
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* We need to check the condition only if the
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* column index (same as row index) of the original whole
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* matrix is larger than 1, since the condition for whole
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* original matrix is checked in the main routine.
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*
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IF( SISNAN( MAXC2NRMK ) ) THEN
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*
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* Set K, the number of factorized columns.
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* that are not zero.
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*
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K = KK - 1
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INFO = K + KP
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*
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* Set RELMAXC2NRMK to NaN.
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*
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RELMAXC2NRMK = MAXC2NRMK
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*
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* Array TAU(K+1:MINMNFACT) is not set and contains
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* undefined elements.
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*
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RETURN
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END IF
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*
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* ============================================================
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*
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* Quick return, if the submatrix A(I:M,KK:N) is
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* a zero matrix.
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* We need to check the condition only if the
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* column index (same as row index) of the original whole
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* matrix is larger than 1, since the condition for whole
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* original matrix is checked in the main routine.
|
||
*
|
||
IF( MAXC2NRMK.EQ.ZERO ) THEN
|
||
*
|
||
* Set K, the number of factorized columns.
|
||
* that are not zero.
|
||
*
|
||
K = KK - 1
|
||
RELMAXC2NRMK = ZERO
|
||
*
|
||
* Set TAUs corresponding to the columns that were not
|
||
* factorized to ZERO, i.e. set TAU(KK:MINMNFACT) to ZERO.
|
||
*
|
||
DO J = KK, MINMNFACT
|
||
TAU( J ) = ZERO
|
||
END DO
|
||
*
|
||
* Return from the routine.
|
||
*
|
||
RETURN
|
||
*
|
||
END IF
|
||
*
|
||
* ============================================================
|
||
*
|
||
* Check if the submatrix A(I:M,KK:N) contains Inf,
|
||
* set INFO parameter to the column number, where
|
||
* the first Inf is found plus N, and continue
|
||
* the computation.
|
||
* We need to check the condition only if the
|
||
* column index (same as row index) of the original whole
|
||
* matrix is larger than 1, since the condition for whole
|
||
* original matrix is checked in the main routine.
|
||
*
|
||
IF( INFO.EQ.0 .AND. MAXC2NRMK.GT.HUGEVAL ) THEN
|
||
INFO = N + KK - 1 + KP
|
||
END IF
|
||
*
|
||
* ============================================================
|
||
*
|
||
* Test for the second and third stopping criteria.
|
||
* NOTE: There is no need to test for ABSTOL >= ZERO, since
|
||
* MAXC2NRMK is non-negative. Similarly, there is no need
|
||
* to test for RELTOL >= ZERO, since RELMAXC2NRMK is
|
||
* non-negative.
|
||
* We need to check the condition only if the
|
||
* column index (same as row index) of the original whole
|
||
* matrix is larger than 1, since the condition for whole
|
||
* original matrix is checked in the main routine.
|
||
|
||
RELMAXC2NRMK = MAXC2NRMK / MAXC2NRM
|
||
*
|
||
IF( MAXC2NRMK.LE.ABSTOL .OR. RELMAXC2NRMK.LE.RELTOL ) THEN
|
||
*
|
||
* Set K, the number of factorized columns.
|
||
*
|
||
K = KK - 1
|
||
*
|
||
* Set TAUs corresponding to the columns that were not
|
||
* factorized to ZERO, i.e. set TAU(KK:MINMNFACT) to ZERO.
|
||
*
|
||
DO J = KK, MINMNFACT
|
||
TAU( J ) = ZERO
|
||
END DO
|
||
*
|
||
* Return from the routine.
|
||
*
|
||
RETURN
|
||
*
|
||
END IF
|
||
*
|
||
* ============================================================
|
||
*
|
||
* End ELSE of IF(I.EQ.1)
|
||
*
|
||
END IF
|
||
*
|
||
* ===============================================================
|
||
*
|
||
* If the pivot column is not the first column of the
|
||
* subblock A(1:M,KK:N):
|
||
* 1) swap the KK-th column and the KP-th pivot column
|
||
* in A(1:M,1:N);
|
||
* 2) copy the KK-th element into the KP-th element of the partial
|
||
* and exact 2-norm vectors VN1 and VN2. ( Swap is not needed
|
||
* for VN1 and VN2 since we use the element with the index
|
||
* larger than KK in the next loop step.)
|
||
* 3) Save the pivot interchange with the indices relative to the
|
||
* the original matrix A, not the block A(1:M,1:N).
|
||
*
|
||
IF( KP.NE.KK ) THEN
|
||
CALL SSWAP( M, A( 1, KP ), 1, A( 1, KK ), 1 )
|
||
VN1( KP ) = VN1( KK )
|
||
VN2( KP ) = VN2( KK )
|
||
ITEMP = JPIV( KP )
|
||
JPIV( KP ) = JPIV( KK )
|
||
JPIV( KK ) = ITEMP
|
||
END IF
|
||
*
|
||
* Generate elementary reflector H(KK) using the column A(I:M,KK),
|
||
* if the column has more than one element, otherwise
|
||
* the elementary reflector would be an identity matrix,
|
||
* and TAU(KK) = ZERO.
|
||
*
|
||
IF( I.LT.M ) THEN
|
||
CALL SLARFG( M-I+1, A( I, KK ), A( I+1, KK ), 1,
|
||
$ TAU( KK ) )
|
||
ELSE
|
||
TAU( KK ) = ZERO
|
||
END IF
|
||
*
|
||
* Check if TAU(KK) contains NaN, set INFO parameter
|
||
* to the column number where NaN is found and return from
|
||
* the routine.
|
||
* NOTE: There is no need to check TAU(KK) for Inf,
|
||
* since SLARFG cannot produce TAU(KK) or Householder vector
|
||
* below the diagonal containing Inf. Only BETA on the diagonal,
|
||
* returned by SLARFG can contain Inf, which requires
|
||
* TAU(KK) to contain NaN. Therefore, this case of generating Inf
|
||
* by SLARFG is covered by checking TAU(KK) for NaN.
|
||
*
|
||
IF( SISNAN( TAU(KK) ) ) THEN
|
||
K = KK - 1
|
||
INFO = KK
|
||
*
|
||
* Set MAXC2NRMK and RELMAXC2NRMK to NaN.
|
||
*
|
||
MAXC2NRMK = TAU( KK )
|
||
RELMAXC2NRMK = TAU( KK )
|
||
*
|
||
* Array TAU(KK:MINMNFACT) is not set and contains
|
||
* undefined elements, except the first element TAU(KK) = NaN.
|
||
*
|
||
RETURN
|
||
END IF
|
||
*
|
||
* Apply H(KK)**T to A(I:M,KK+1:N+NRHS) from the left.
|
||
* ( If M >= N, then at KK = N there is no residual matrix,
|
||
* i.e. no columns of A to update, only columns of B.
|
||
* If M < N, then at KK = M-IOFFSET, I = M and we have a
|
||
* one-row residual matrix in A and the elementary
|
||
* reflector is a unit matrix, TAU(KK) = ZERO, i.e. no update
|
||
* is needed for the residual matrix in A and the
|
||
* right-hand-side-matrix in B.
|
||
* Therefore, we update only if
|
||
* KK < MINMNUPDT = min(M-IOFFSET, N+NRHS)
|
||
* condition is satisfied, not only KK < N+NRHS )
|
||
*
|
||
IF( KK.LT.MINMNUPDT ) THEN
|
||
AIKK = A( I, KK )
|
||
A( I, KK ) = ONE
|
||
CALL SLARF( 'Left', M-I+1, N+NRHS-KK, A( I, KK ), 1,
|
||
$ TAU( KK ), A( I, KK+1 ), LDA, WORK( 1 ) )
|
||
A( I, KK ) = AIKK
|
||
END IF
|
||
*
|
||
IF( KK.LT.MINMNFACT ) THEN
|
||
*
|
||
* Update the partial column 2-norms for the residual matrix,
|
||
* only if the residual matrix A(I+1:M,KK+1:N) exists, i.e.
|
||
* when KK < min(M-IOFFSET, N).
|
||
*
|
||
DO J = KK + 1, N
|
||
IF( VN1( J ).NE.ZERO ) THEN
|
||
*
|
||
* NOTE: The following lines follow from the analysis in
|
||
* Lapack Working Note 176.
|
||
*
|
||
TEMP = ONE - ( ABS( A( I, J ) ) / VN1( J ) )**2
|
||
TEMP = MAX( TEMP, ZERO )
|
||
TEMP2 = TEMP*( VN1( J ) / VN2( J ) )**2
|
||
IF( TEMP2 .LE. TOL3Z ) THEN
|
||
*
|
||
* Compute the column 2-norm for the partial
|
||
* column A(I+1:M,J) by explicitly computing it,
|
||
* and store it in both partial 2-norm vector VN1
|
||
* and exact column 2-norm vector VN2.
|
||
*
|
||
VN1( J ) = SNRM2( M-I, A( I+1, J ), 1 )
|
||
VN2( J ) = VN1( J )
|
||
*
|
||
ELSE
|
||
*
|
||
* Update the column 2-norm for the partial
|
||
* column A(I+1:M,J) by removing one
|
||
* element A(I,J) and store it in partial
|
||
* 2-norm vector VN1.
|
||
*
|
||
VN1( J ) = VN1( J )*SQRT( TEMP )
|
||
*
|
||
END IF
|
||
END IF
|
||
END DO
|
||
*
|
||
END IF
|
||
*
|
||
* End factorization loop
|
||
*
|
||
END DO
|
||
*
|
||
* If we reached this point, all colunms have been factorized,
|
||
* i.e. no condition was triggered to exit the routine.
|
||
* Set the number of factorized columns.
|
||
*
|
||
K = KMAX
|
||
*
|
||
* We reached the end of the loop, i.e. all KMAX columns were
|
||
* factorized, we need to set MAXC2NRMK and RELMAXC2NRMK before
|
||
* we return.
|
||
*
|
||
IF( K.LT.MINMNFACT ) THEN
|
||
*
|
||
JMAXC2NRM = K + ISAMAX( N-K, VN1( K+1 ), 1 )
|
||
MAXC2NRMK = VN1( JMAXC2NRM )
|
||
*
|
||
IF( K.EQ.0 ) THEN
|
||
RELMAXC2NRMK = ONE
|
||
ELSE
|
||
RELMAXC2NRMK = MAXC2NRMK / MAXC2NRM
|
||
END IF
|
||
*
|
||
ELSE
|
||
MAXC2NRMK = ZERO
|
||
RELMAXC2NRMK = ZERO
|
||
END IF
|
||
*
|
||
* We reached the end of the loop, i.e. all KMAX columns were
|
||
* factorized, set TAUs corresponding to the columns that were
|
||
* not factorized to ZERO, i.e. TAU(K+1:MINMNFACT) set to ZERO.
|
||
*
|
||
DO J = K + 1, MINMNFACT
|
||
TAU( J ) = ZERO
|
||
END DO
|
||
*
|
||
RETURN
|
||
*
|
||
* End of SLAQP2RK
|
||
*
|
||
END
|