+*> \brief \b SGSVJ0 pre-processor for the routine sgesvj.
+*
+* =========== DOCUMENTATION ===========
+*
+* Online html documentation available at
+* http://www.netlib.org/lapack/explore-html/
+*
+*> \htmlonly
+*> Download SGSVJ0 + dependencies
+*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/sgsvj0.f">
+*> [TGZ]</a>
+*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/sgsvj0.f">
+*> [ZIP]</a>
+*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/sgsvj0.f">
+*> [TXT]</a>
+*> \endhtmlonly
+*
+* Definition:
+* ===========
+*
+* SUBROUTINE SGSVJ0( JOBV, M, N, A, LDA, D, SVA, MV, V, LDV, EPS,
+* SFMIN, TOL, NSWEEP, WORK, LWORK, INFO )
+*
+* .. Scalar Arguments ..
+* INTEGER INFO, LDA, LDV, LWORK, M, MV, N, NSWEEP
+* REAL EPS, SFMIN, TOL
+* CHARACTER*1 JOBV
+* ..
+* .. Array Arguments ..
+* REAL A( LDA, * ), SVA( N ), D( N ), V( LDV, * ),
+* $ WORK( LWORK )
+* ..
+*
+*
+*> \par Purpose:
+* =============
+*>
+*> \verbatim
+*>
+*> SGSVJ0 is called from SGESVJ as a pre-processor and that is its main
+*> purpose. It applies Jacobi rotations in the same way as SGESVJ does, but
+*> it does not check convergence (stopping criterion). Few tuning
+*> parameters (marked by [TP]) are available for the implementer.
+*> \endverbatim
+*
+* Arguments:
+* ==========
+*
+*> \param[in] JOBV
+*> \verbatim
+*> JOBV is CHARACTER*1
+*> Specifies whether the output from this procedure is used
+*> to compute the matrix V:
+*> = 'V': the product of the Jacobi rotations is accumulated
+*> by postmulyiplying the N-by-N array V.
+*> (See the description of V.)
+*> = 'A': the product of the Jacobi rotations is accumulated
+*> by postmulyiplying the MV-by-N array V.
+*> (See the descriptions of MV and V.)
+*> = 'N': the Jacobi rotations are not accumulated.
+*> \endverbatim
+*>
+*> \param[in] M
+*> \verbatim
+*> M is INTEGER
+*> The number of rows of the input matrix A. M >= 0.
+*> \endverbatim
+*>
+*> \param[in] N
+*> \verbatim
+*> N is INTEGER
+*> The number of columns of the input matrix A.
+*> M >= N >= 0.
+*> \endverbatim
+*>
+*> \param[in,out] A
+*> \verbatim
+*> A is REAL array, dimension (LDA,N)
+*> On entry, M-by-N matrix A, such that A*diag(D) represents
+*> the input matrix.
+*> On exit,
+*> A_onexit * D_onexit represents the input matrix A*diag(D)
+*> post-multiplied by a sequence of Jacobi rotations, where the
+*> rotation threshold and the total number of sweeps are given in
+*> TOL and NSWEEP, respectively.
+*> (See the descriptions of D, TOL and NSWEEP.)
+*> \endverbatim
+*>
+*> \param[in] LDA
+*> \verbatim
+*> LDA is INTEGER
+*> The leading dimension of the array A. LDA >= max(1,M).
+*> \endverbatim
+*>
+*> \param[in,out] D
+*> \verbatim
+*> D is REAL array, dimension (N)
+*> The array D accumulates the scaling factors from the fast scaled
+*> Jacobi rotations.
+*> On entry, A*diag(D) represents the input matrix.
+*> On exit, A_onexit*diag(D_onexit) represents the input matrix
+*> post-multiplied by a sequence of Jacobi rotations, where the
+*> rotation threshold and the total number of sweeps are given in
+*> TOL and NSWEEP, respectively.
+*> (See the descriptions of A, TOL and NSWEEP.)
+*> \endverbatim
+*>
+*> \param[in,out] SVA
+*> \verbatim
+*> SVA is REAL array, dimension (N)
+*> On entry, SVA contains the Euclidean norms of the columns of
+*> the matrix A*diag(D).
+*> On exit, SVA contains the Euclidean norms of the columns of
+*> the matrix onexit*diag(D_onexit).
+*> \endverbatim
+*>
+*> \param[in] MV
+*> \verbatim
+*> MV is INTEGER
+*> If JOBV .EQ. 'A', then MV rows of V are post-multipled by a
+*> sequence of Jacobi rotations.
+*> If JOBV = 'N', then MV is not referenced.
+*> \endverbatim
+*>
+*> \param[in,out] V
+*> \verbatim
+*> V is REAL array, dimension (LDV,N)
+*> If JOBV .EQ. 'V' then N rows of V are post-multipled by a
+*> sequence of Jacobi rotations.
+*> If JOBV .EQ. 'A' then MV rows of V are post-multipled by a
+*> sequence of Jacobi rotations.
+*> If JOBV = 'N', then V is not referenced.
+*> \endverbatim
+*>
+*> \param[in] LDV
+*> \verbatim
+*> LDV is INTEGER
+*> The leading dimension of the array V, LDV >= 1.
+*> If JOBV = 'V', LDV .GE. N.
+*> If JOBV = 'A', LDV .GE. MV.
+*> \endverbatim
+*>
+*> \param[in] EPS
+*> \verbatim
+*> EPS is REAL
+*> EPS = SLAMCH('Epsilon')
+*> \endverbatim
+*>
+*> \param[in] SFMIN
+*> \verbatim
+*> SFMIN is REAL
+*> SFMIN = SLAMCH('Safe Minimum')
+*> \endverbatim
+*>
+*> \param[in] TOL
+*> \verbatim
+*> TOL is REAL
+*> TOL is the threshold for Jacobi rotations. For a pair
+*> A(:,p), A(:,q) of pivot columns, the Jacobi rotation is
+*> applied only if ABS(COS(angle(A(:,p),A(:,q)))) .GT. TOL.
+*> \endverbatim
+*>
+*> \param[in] NSWEEP
+*> \verbatim
+*> NSWEEP is INTEGER
+*> NSWEEP is the number of sweeps of Jacobi rotations to be
+*> performed.
+*> \endverbatim
+*>
+*> \param[out] WORK
+*> \verbatim
+*> WORK is REAL array, dimension (LWORK)
+*> \endverbatim
+*>
+*> \param[in] LWORK
+*> \verbatim
+*> LWORK is INTEGER
+*> LWORK is the dimension of WORK. LWORK .GE. M.
+*> \endverbatim
+*>
+*> \param[out] INFO
+*> \verbatim
+*> INFO is INTEGER
+*> = 0 : successful exit.
+*> < 0 : if INFO = -i, then the i-th argument had an illegal value
+*> \endverbatim
+*
+* Authors:
+* ========
+*
+*> \author Univ. of Tennessee
+*> \author Univ. of California Berkeley
+*> \author Univ. of Colorado Denver
+*> \author NAG Ltd.
+*
+*> \date December 2016
+*
+*> \ingroup realOTHERcomputational
+*
+*> \par Further Details:
+* =====================
+*>
+*> SGSVJ0 is used just to enable SGESVJ to call a simplified version of
+*> itself to work on a submatrix of the original matrix.
+*>
+*> \par Contributors:
+* ==================
+*>
+*> Zlatko Drmac (Zagreb, Croatia) and Kresimir Veselic (Hagen, Germany)
+*>
+*> \par Bugs, Examples and Comments:
+* =================================
+*>
+*> Please report all bugs and send interesting test examples and comments to
+*> drmac@math.hr. Thank you.
+*
+* =====================================================================
SUBROUTINE SGSVJ0( JOBV, M, N, A, LDA, D, SVA, MV, V, LDV, EPS,
$ SFMIN, TOL, NSWEEP, WORK, LWORK, INFO )
*
-* -- LAPACK routine (version 3.3.1) --
-*
-* -- Contributed by Zlatko Drmac of the University of Zagreb and --
-* -- Kresimir Veselic of the Fernuniversitaet Hagen --
-* -- April 2011 --
-*
+* -- LAPACK computational routine (version 3.7.0) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
+* December 2016
*
-* This routine is also part of SIGMA (version 1.23, October 23. 2008.)
-* SIGMA is a library of algorithms for highly accurate algorithms for
-* computation of SVD, PSVD, QSVD, (H,K)-SVD, and for solution of the
-* eigenvalue problems Hx = lambda M x, H M x = lambda x with H, M > 0.
-*
- IMPLICIT NONE
-* ..
* .. Scalar Arguments ..
INTEGER INFO, LDA, LDV, LWORK, M, MV, N, NSWEEP
REAL EPS, SFMIN, TOL
$ WORK( LWORK )
* ..
*
-* Purpose
-* =======
-*
-* SGSVJ0 is called from SGESVJ as a pre-processor and that is its main
-* purpose. It applies Jacobi rotations in the same way as SGESVJ does, but
-* it does not check convergence (stopping criterion). Few tuning
-* parameters (marked by [TP]) are available for the implementer.
-*
-* Further Details
-* ~~~~~~~~~~~~~~~
-* SGSVJ0 is used just to enable SGESVJ to call a simplified version of
-* itself to work on a submatrix of the original matrix.
-*
-* Contributors
-* ~~~~~~~~~~~~
-* Zlatko Drmac (Zagreb, Croatia) and Kresimir Veselic (Hagen, Germany)
-*
-* Bugs, Examples and Comments
-* ~~~~~~~~~~~~~~~~~~~~~~~~~~~
-* Please report all bugs and send interesting test examples and comments to
-* drmac@math.hr. Thank you.
-*
-* Arguments
-* =========
-*
-* JOBV (input) CHARACTER*1
-* Specifies whether the output from this procedure is used
-* to compute the matrix V:
-* = 'V': the product of the Jacobi rotations is accumulated
-* by postmulyiplying the N-by-N array V.
-* (See the description of V.)
-* = 'A': the product of the Jacobi rotations is accumulated
-* by postmulyiplying the MV-by-N array V.
-* (See the descriptions of MV and V.)
-* = 'N': the Jacobi rotations are not accumulated.
-*
-* M (input) INTEGER
-* The number of rows of the input matrix A. M >= 0.
-*
-* N (input) INTEGER
-* The number of columns of the input matrix A.
-* M >= N >= 0.
-*
-* A (input/output) REAL array, dimension (LDA,N)
-* On entry, M-by-N matrix A, such that A*diag(D) represents
-* the input matrix.
-* On exit,
-* A_onexit * D_onexit represents the input matrix A*diag(D)
-* post-multiplied by a sequence of Jacobi rotations, where the
-* rotation threshold and the total number of sweeps are given in
-* TOL and NSWEEP, respectively.
-* (See the descriptions of D, TOL and NSWEEP.)
-*
-* LDA (input) INTEGER
-* The leading dimension of the array A. LDA >= max(1,M).
-*
-* D (input/workspace/output) REAL array, dimension (N)
-* The array D accumulates the scaling factors from the fast scaled
-* Jacobi rotations.
-* On entry, A*diag(D) represents the input matrix.
-* On exit, A_onexit*diag(D_onexit) represents the input matrix
-* post-multiplied by a sequence of Jacobi rotations, where the
-* rotation threshold and the total number of sweeps are given in
-* TOL and NSWEEP, respectively.
-* (See the descriptions of A, TOL and NSWEEP.)
-*
-* SVA (input/workspace/output) REAL array, dimension (N)
-* On entry, SVA contains the Euclidean norms of the columns of
-* the matrix A*diag(D).
-* On exit, SVA contains the Euclidean norms of the columns of
-* the matrix onexit*diag(D_onexit).
-*
-* MV (input) INTEGER
-* If JOBV .EQ. 'A', then MV rows of V are post-multipled by a
-* sequence of Jacobi rotations.
-* If JOBV = 'N', then MV is not referenced.
-*
-* V (input/output) REAL array, dimension (LDV,N)
-* If JOBV .EQ. 'V' then N rows of V are post-multipled by a
-* sequence of Jacobi rotations.
-* If JOBV .EQ. 'A' then MV rows of V are post-multipled by a
-* sequence of Jacobi rotations.
-* If JOBV = 'N', then V is not referenced.
-*
-* LDV (input) INTEGER
-* The leading dimension of the array V, LDV >= 1.
-* If JOBV = 'V', LDV .GE. N.
-* If JOBV = 'A', LDV .GE. MV.
-*
-* EPS (input) INTEGER
-* EPS = SLAMCH('Epsilon')
-*
-* SFMIN (input) INTEGER
-* SFMIN = SLAMCH('Safe Minimum')
-*
-* TOL (input) REAL
-* TOL is the threshold for Jacobi rotations. For a pair
-* A(:,p), A(:,q) of pivot columns, the Jacobi rotation is
-* applied only if ABS(COS(angle(A(:,p),A(:,q)))) .GT. TOL.
-*
-* NSWEEP (input) INTEGER
-* NSWEEP is the number of sweeps of Jacobi rotations to be
-* performed.
-*
-* WORK (workspace) REAL array, dimension LWORK.
-*
-* LWORK (input) INTEGER
-* LWORK is the dimension of WORK. LWORK .GE. M.
-*
-* INFO (output) INTEGER
-* = 0 : successful exit.
-* < 0 : if INFO = -i, then the i-th argument had an illegal value
-*
* =====================================================================
*
* .. Local Parameters ..
- REAL ZERO, HALF, ONE, TWO
- PARAMETER ( ZERO = 0.0E0, HALF = 0.5E0, ONE = 1.0E0,
- $ TWO = 2.0E0 )
+ REAL ZERO, HALF, ONE
+ PARAMETER ( ZERO = 0.0E0, HALF = 0.5E0, ONE = 1.0E0)
* ..
* .. Local Scalars ..
REAL AAPP, AAPP0, AAPQ, AAQQ, APOAQ, AQOAP, BIG,
REAL FASTR( 5 )
* ..
* .. Intrinsic Functions ..
- INTRINSIC ABS, AMAX1, AMIN1, FLOAT, MIN0, SIGN, SQRT
+ INTRINSIC ABS, MAX, FLOAT, MIN, SIGN, SQRT
* ..
* .. External Functions ..
REAL SDOT, SNRM2
INFO = -5
ELSE IF( ( RSVEC.OR.APPLV ) .AND. ( MV.LT.0 ) ) THEN
INFO = -8
- ELSE IF( ( RSVEC.AND.( LDV.LT.N ) ).OR.
+ ELSE IF( ( RSVEC.AND.( LDV.LT.N ) ).OR.
$ ( APPLV.AND.( LDV.LT.MV ) ) ) THEN
INFO = -10
ELSE IF( TOL.LE.EPS ) THEN
* Jacobi SVD algorithm SGESVJ. For sweeps i=1:SWBAND the procedure
* ......
- KBL = MIN0( 8, N )
+ KBL = MIN( 8, N )
*[TP] KBL is a tuning parameter that defines the tile size in the
* tiling of the p-q loops of pivot pairs. In general, an optimal
* value of KBL depends on the matrix dimensions and on the
BLSKIP = ( KBL**2 ) + 1
*[TP] BLKSKIP is a tuning parameter that depends on SWBAND and KBL.
- ROWSKIP = MIN0( 5, KBL )
+ ROWSKIP = MIN( 5, KBL )
*[TP] ROWSKIP is a tuning parameter.
LKAHEAD = 1
igl = ( ibr-1 )*KBL + 1
*
- DO 1002 ir1 = 0, MIN0( LKAHEAD, NBL-ibr )
+ DO 1002 ir1 = 0, MIN( LKAHEAD, NBL-ibr )
*
igl = igl + ir1*KBL
*
- DO 2001 p = igl, MIN0( igl+KBL-1, N-1 )
+ DO 2001 p = igl, MIN( igl+KBL-1, N-1 )
* .. de Rijk's pivoting
q = ISAMAX( N-p+1, SVA( p ), 1 ) + p - 1
*
PSKIPPED = 0
*
- DO 2002 q = p + 1, MIN0( igl+KBL-1, N )
+ DO 2002 q = p + 1, MIN( igl+KBL-1, N )
*
AAQQ = SVA( q )
END IF
END IF
*
- MXAAPQ = AMAX1( MXAAPQ, ABS( AAPQ ) )
+ MXAAPQ = MAX( MXAAPQ, ABS( AAPQ ) )
*
* TO rotate or NOT to rotate, THAT is the question ...
*
$ V( 1, p ), 1,
$ V( 1, q ), 1,
$ FASTR )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ ) )
- AAPP = AAPP*SQRT( AMAX1( ZERO,
+ AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ ) )
- MXSINJ = AMAX1( MXSINJ, ABS( T ) )
+ MXSINJ = MAX( MXSINJ, ABS( T ) )
*
ELSE
*
CS = SQRT( ONE / ( ONE+T*T ) )
SN = T*CS
*
- MXSINJ = AMAX1( MXSINJ, ABS( SN ) )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ MXSINJ = MAX( MXSINJ, ABS( SN ) )
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ ) )
- AAPP = AAPP*SQRT( AMAX1( ZERO,
+ AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ ) )
*
APOAQ = D( p ) / D( q )
$ A( 1, q ), 1 )
CALL SLASCL( 'G', 0, 0, ONE, AAQQ, M,
$ 1, A( 1, q ), LDA, IERR )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE-AAPQ*AAPQ ) )
- MXSINJ = AMAX1( MXSINJ, SFMIN )
+ MXSINJ = MAX( MXSINJ, SFMIN )
END IF
* END IF ROTOK THEN ... ELSE
*
ELSE
SVA( p ) = AAPP
IF( ( ir1.EQ.0 ) .AND. ( AAPP.EQ.ZERO ) )
- $ NOTROT = NOTROT + MIN0( igl+KBL-1, N ) - p
+ $ NOTROT = NOTROT + MIN( igl+KBL-1, N ) - p
END IF
*
2001 CONTINUE
* doing the block at ( ibr, jbc )
*
IJBLSK = 0
- DO 2100 p = igl, MIN0( igl+KBL-1, N )
+ DO 2100 p = igl, MIN( igl+KBL-1, N )
*
AAPP = SVA( p )
*
*
PSKIPPED = 0
*
- DO 2200 q = jgl, MIN0( jgl+KBL-1, N )
+ DO 2200 q = jgl, MIN( jgl+KBL-1, N )
*
AAQQ = SVA( q )
*
END IF
END IF
*
- MXAAPQ = AMAX1( MXAAPQ, ABS( AAPQ ) )
+ MXAAPQ = MAX( MXAAPQ, ABS( AAPQ ) )
*
* TO rotate or NOT to rotate, THAT is the question ...
*
$ V( 1, p ), 1,
$ V( 1, q ), 1,
$ FASTR )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ ) )
- AAPP = AAPP*SQRT( AMAX1( ZERO,
+ AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ ) )
- MXSINJ = AMAX1( MXSINJ, ABS( T ) )
+ MXSINJ = MAX( MXSINJ, ABS( T ) )
ELSE
*
* .. choose correct signum for THETA and rotate
$ SQRT( ONE+THETA*THETA ) )
CS = SQRT( ONE / ( ONE+T*T ) )
SN = T*CS
- MXSINJ = AMAX1( MXSINJ, ABS( SN ) )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ MXSINJ = MAX( MXSINJ, ABS( SN ) )
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ ) )
- AAPP = AAPP*SQRT( AMAX1( ZERO,
+ AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ ) )
*
APOAQ = D( p ) / D( q )
CALL SLASCL( 'G', 0, 0, ONE, AAQQ,
$ M, 1, A( 1, q ), LDA,
$ IERR )
- SVA( q ) = AAQQ*SQRT( AMAX1( ZERO,
+ SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE-AAPQ*AAPQ ) )
- MXSINJ = AMAX1( MXSINJ, SFMIN )
+ MXSINJ = MAX( MXSINJ, SFMIN )
ELSE
CALL SCOPY( M, A( 1, q ), 1, WORK,
$ 1 )
CALL SLASCL( 'G', 0, 0, ONE, AAPP,
$ M, 1, A( 1, p ), LDA,
$ IERR )
- SVA( p ) = AAPP*SQRT( AMAX1( ZERO,
+ SVA( p ) = AAPP*SQRT( MAX( ZERO,
$ ONE-AAPQ*AAPQ ) )
- MXSINJ = AMAX1( MXSINJ, SFMIN )
+ MXSINJ = MAX( MXSINJ, SFMIN )
END IF
END IF
* END IF ROTOK THEN ... ELSE
*
ELSE
IF( AAPP.EQ.ZERO )NOTROT = NOTROT +
- $ MIN0( jgl+KBL-1, N ) - jgl + 1
+ $ MIN( jgl+KBL-1, N ) - jgl + 1
IF( AAPP.LT.ZERO )NOTROT = 0
END IF
* end of the jbc-loop
2011 CONTINUE
*2011 bailed out of the jbc-loop
- DO 2012 p = igl, MIN0( igl+KBL-1, N )
+ DO 2012 p = igl, MIN( igl+KBL-1, N )
SVA( p ) = ABS( SVA( p ) )
2012 CONTINUE
*