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cgsvj1.f
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*> \brief \b CGSVJ1 pre-processor for the routine cgesvj, applies Jacobi rotations targeting only particular pivots.
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
*> \htmlonly
*> Download CGSVJ1 + dependencies
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/cgsvj1.f">
*> [TGZ]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/cgsvj1.f">
*> [ZIP]</a>
*> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/cgsvj1.f">
*> [TXT]</a>
*> \endhtmlonly
*
* Definition:
* ===========
*
* SUBROUTINE CGSVJ1( JOBV, M, N, N1, A, LDA, D, SVA, MV, V, LDV,
* EPS, SFMIN, TOL, NSWEEP, WORK, LWORK, INFO )
*
* .. Scalar Arguments ..
* REAL EPS, SFMIN, TOL
* INTEGER INFO, LDA, LDV, LWORK, M, MV, N, N1, NSWEEP
* CHARACTER*1 JOBV
* ..
* .. Array Arguments ..
* COMPLEX A( LDA, * ), D( N ), V( LDV, * ), WORK( LWORK )
* REAL SVA( N )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> CGSVJ1 is called from CGESVJ as a pre-processor and that is its main
*> purpose. It applies Jacobi rotations in the same way as CGESVJ does, but
*> it targets only particular pivots and it does not check convergence
*> (stopping criterion). Few tuning parameters (marked by [TP]) are
*> available for the implementer.
*>
*> Further Details
*> ~~~~~~~~~~~~~~~
*> CGSVJ1 applies few sweeps of Jacobi rotations in the column space of
*> the input M-by-N matrix A. The pivot pairs are taken from the (1,2)
*> off-diagonal block in the corresponding N-by-N Gram matrix A^T * A. The
*> block-entries (tiles) of the (1,2) off-diagonal block are marked by the
*> [x]'s in the following scheme:
*>
*> | * * * [x] [x] [x]|
*> | * * * [x] [x] [x]| Row-cycling in the nblr-by-nblc [x] blocks.
*> | * * * [x] [x] [x]| Row-cyclic pivoting inside each [x] block.
*> |[x] [x] [x] * * * |
*> |[x] [x] [x] * * * |
*> |[x] [x] [x] * * * |
*>
*> In terms of the columns of A, the first N1 columns are rotated 'against'
*> the remaining N-N1 columns, trying to increase the angle between the
*> corresponding subspaces. The off-diagonal block is N1-by(N-N1) and it is
*> tiled using quadratic tiles of side KBL. Here, KBL is a tuning parameter.
*> The number of sweeps is given in NSWEEP and the orthogonality threshold
*> is given in TOL.
*> \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 postmultiplying the N-by-N array V.
*> (See the description of V.)
*> = 'A': the product of the Jacobi rotations is accumulated
*> by postmultiplying 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] N1
*> \verbatim
*> N1 is INTEGER
*> N1 specifies the 2 x 2 block partition, the first N1 columns are
*> rotated 'against' the remaining N-N1 columns of A.
*> \endverbatim
*>
*> \param[in,out] A
*> \verbatim
*> A is COMPLEX 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 N1, 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 COMPLEX 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 N1, 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 = 'A', then MV rows of V are post-multiplied by a
*> sequence of Jacobi rotations.
*> If JOBV = 'N', then MV is not referenced.
*> \endverbatim
*>
*> \param[in,out] V
*> \verbatim
*> V is COMPLEX array, dimension (LDV,N)
*> If JOBV = 'V' then N rows of V are post-multiplied by a
*> sequence of Jacobi rotations.
*> If JOBV = 'A' then MV rows of V are post-multiplied 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 >= N.
*> If JOBV = 'A', LDV >= 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)))) > 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 COMPLEX array, dimension (LWORK)
*> \endverbatim
*>
*> \param[in] LWORK
*> \verbatim
*> LWORK is INTEGER
*> LWORK is the dimension of WORK. LWORK >= 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.
*
*> \ingroup complexOTHERcomputational
*
*> \par Contributor:
* ==================
*>
*> Zlatko Drmac (Zagreb, Croatia)
*
* =====================================================================
SUBROUTINE CGSVJ1( JOBV, M, N, N1, A, LDA, D, SVA, MV, V, LDV,
$ EPS, SFMIN, TOL, NSWEEP, WORK, LWORK, INFO )
*
* -- LAPACK computational routine --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*
* .. Scalar Arguments ..
REAL EPS, SFMIN, TOL
INTEGER INFO, LDA, LDV, LWORK, M, MV, N, N1, NSWEEP
CHARACTER*1 JOBV
* ..
* .. Array Arguments ..
COMPLEX A( LDA, * ), D( N ), V( LDV, * ), WORK( LWORK )
REAL SVA( N )
* ..
*
* =====================================================================
*
* .. Local Parameters ..
REAL ZERO, HALF, ONE
PARAMETER ( ZERO = 0.0E0, HALF = 0.5E0, ONE = 1.0E0)
* ..
* .. Local Scalars ..
COMPLEX AAPQ, OMPQ
REAL AAPP, AAPP0, AAPQ1, AAQQ, APOAQ, AQOAP, BIG,
$ BIGTHETA, CS, MXAAPQ, MXSINJ, ROOTBIG,
$ ROOTEPS, ROOTSFMIN, ROOTTOL, SMALL, SN, T,
$ TEMP1, THETA, THSIGN
INTEGER BLSKIP, EMPTSW, i, ibr, igl, IERR, IJBLSK,
$ ISWROT, jbc, jgl, KBL, MVL, NOTROT, nblc, nblr,
$ p, PSKIPPED, q, ROWSKIP, SWBAND
LOGICAL APPLV, ROTOK, RSVEC
* ..
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, MAX, CONJG, REAL, MIN, SIGN, SQRT
* ..
* .. External Functions ..
REAL SCNRM2
COMPLEX CDOTC
INTEGER ISAMAX
LOGICAL LSAME
EXTERNAL ISAMAX, LSAME, CDOTC, SCNRM2
* ..
* .. External Subroutines ..
* .. from BLAS
EXTERNAL CCOPY, CROT, CSWAP, CAXPY
* .. from LAPACK
EXTERNAL CLASCL, CLASSQ, XERBLA
* ..
* .. Executable Statements ..
*
* Test the input parameters.
*
APPLV = LSAME( JOBV, 'A' )
RSVEC = LSAME( JOBV, 'V' )
IF( .NOT.( RSVEC .OR. APPLV .OR. LSAME( JOBV, 'N' ) ) ) THEN
INFO = -1
ELSE IF( M.LT.0 ) THEN
INFO = -2
ELSE IF( ( N.LT.0 ) .OR. ( N.GT.M ) ) THEN
INFO = -3
ELSE IF( N1.LT.0 ) THEN
INFO = -4
ELSE IF( LDA.LT.M ) THEN
INFO = -6
ELSE IF( ( RSVEC.OR.APPLV ) .AND. ( MV.LT.0 ) ) THEN
INFO = -9
ELSE IF( ( RSVEC.AND.( LDV.LT.N ) ).OR.
$ ( APPLV.AND.( LDV.LT.MV ) ) ) THEN
INFO = -11
ELSE IF( TOL.LE.EPS ) THEN
INFO = -14
ELSE IF( NSWEEP.LT.0 ) THEN
INFO = -15
ELSE IF( LWORK.LT.M ) THEN
INFO = -17
ELSE
INFO = 0
END IF
*
* #:(
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'CGSVJ1', -INFO )
RETURN
END IF
*
IF( RSVEC ) THEN
MVL = N
ELSE IF( APPLV ) THEN
MVL = MV
END IF
RSVEC = RSVEC .OR. APPLV
ROOTEPS = SQRT( EPS )
ROOTSFMIN = SQRT( SFMIN )
SMALL = SFMIN / EPS
BIG = ONE / SFMIN
ROOTBIG = ONE / ROOTSFMIN
* LARGE = BIG / SQRT( REAL( M*N ) )
BIGTHETA = ONE / ROOTEPS
ROOTTOL = SQRT( TOL )
*
* .. Initialize the right singular vector matrix ..
*
* RSVEC = LSAME( JOBV, 'Y' )
*
EMPTSW = N1*( N-N1 )
NOTROT = 0
*
* .. Row-cyclic pivot strategy with de Rijk's pivoting ..
*
KBL = MIN( 8, N )
NBLR = N1 / KBL
IF( ( NBLR*KBL ).NE.N1 )NBLR = NBLR + 1
* .. the tiling is nblr-by-nblc [tiles]
NBLC = ( N-N1 ) / KBL
IF( ( NBLC*KBL ).NE.( N-N1 ) )NBLC = NBLC + 1
BLSKIP = ( KBL**2 ) + 1
*[TP] BLKSKIP is a tuning parameter that depends on SWBAND and KBL.
ROWSKIP = MIN( 5, KBL )
*[TP] ROWSKIP is a tuning parameter.
SWBAND = 0
*[TP] SWBAND is a tuning parameter. It is meaningful and effective
* if CGESVJ is used as a computational routine in the preconditioned
* Jacobi SVD algorithm CGEJSV.
*
*
* | * * * [x] [x] [x]|
* | * * * [x] [x] [x]| Row-cycling in the nblr-by-nblc [x] blocks.
* | * * * [x] [x] [x]| Row-cyclic pivoting inside each [x] block.
* |[x] [x] [x] * * * |
* |[x] [x] [x] * * * |
* |[x] [x] [x] * * * |
*
*
DO 1993 i = 1, NSWEEP
*
* .. go go go ...
*
MXAAPQ = ZERO
MXSINJ = ZERO
ISWROT = 0
*
NOTROT = 0
PSKIPPED = 0
*
* Each sweep is unrolled using KBL-by-KBL tiles over the pivot pairs
* 1 <= p < q <= N. This is the first step toward a blocked implementation
* of the rotations. New implementation, based on block transformations,
* is under development.
*
DO 2000 ibr = 1, NBLR
*
igl = ( ibr-1 )*KBL + 1
*
*
* ... go to the off diagonal blocks
*
igl = ( ibr-1 )*KBL + 1
*
* DO 2010 jbc = ibr + 1, NBL
DO 2010 jbc = 1, NBLC
*
jgl = ( jbc-1 )*KBL + N1 + 1
*
* doing the block at ( ibr, jbc )
*
IJBLSK = 0
DO 2100 p = igl, MIN( igl+KBL-1, N1 )
*
AAPP = SVA( p )
IF( AAPP.GT.ZERO ) THEN
*
PSKIPPED = 0
*
DO 2200 q = jgl, MIN( jgl+KBL-1, N )
*
AAQQ = SVA( q )
IF( AAQQ.GT.ZERO ) THEN
AAPP0 = AAPP
*
* .. M x 2 Jacobi SVD ..
*
* Safe Gram matrix computation
*
IF( AAQQ.GE.ONE ) THEN
IF( AAPP.GE.AAQQ ) THEN
ROTOK = ( SMALL*AAPP ).LE.AAQQ
ELSE
ROTOK = ( SMALL*AAQQ ).LE.AAPP
END IF
IF( AAPP.LT.( BIG / AAQQ ) ) THEN
AAPQ = ( CDOTC( M, A( 1, p ), 1,
$ A( 1, q ), 1 ) / AAQQ ) / AAPP
ELSE
CALL CCOPY( M, A( 1, p ), 1,
$ WORK, 1 )
CALL CLASCL( 'G', 0, 0, AAPP,
$ ONE, M, 1,
$ WORK, LDA, IERR )
AAPQ = CDOTC( M, WORK, 1,
$ A( 1, q ), 1 ) / AAQQ
END IF
ELSE
IF( AAPP.GE.AAQQ ) THEN
ROTOK = AAPP.LE.( AAQQ / SMALL )
ELSE
ROTOK = AAQQ.LE.( AAPP / SMALL )
END IF
IF( AAPP.GT.( SMALL / AAQQ ) ) THEN
AAPQ = ( CDOTC( M, A( 1, p ), 1,
$ A( 1, q ), 1 ) / MAX(AAQQ,AAPP) )
$ / MIN(AAQQ,AAPP)
ELSE
CALL CCOPY( M, A( 1, q ), 1,
$ WORK, 1 )
CALL CLASCL( 'G', 0, 0, AAQQ,
$ ONE, M, 1,
$ WORK, LDA, IERR )
AAPQ = CDOTC( M, A( 1, p ), 1,
$ WORK, 1 ) / AAPP
END IF
END IF
*
* AAPQ = AAPQ * CONJG(CWORK(p))*CWORK(q)
AAPQ1 = -ABS(AAPQ)
MXAAPQ = MAX( MXAAPQ, -AAPQ1 )
*
* TO rotate or NOT to rotate, THAT is the question ...
*
IF( ABS( AAPQ1 ).GT.TOL ) THEN
OMPQ = AAPQ / ABS(AAPQ)
NOTROT = 0
*[RTD] ROTATED = ROTATED + 1
PSKIPPED = 0
ISWROT = ISWROT + 1
*
IF( ROTOK ) THEN
*
AQOAP = AAQQ / AAPP
APOAQ = AAPP / AAQQ
THETA = -HALF*ABS( AQOAP-APOAQ )/ AAPQ1
IF( AAQQ.GT.AAPP0 )THETA = -THETA
*
IF( ABS( THETA ).GT.BIGTHETA ) THEN
T = HALF / THETA
CS = ONE
CALL CROT( M, A(1,p), 1, A(1,q), 1,
$ CS, CONJG(OMPQ)*T )
IF( RSVEC ) THEN
CALL CROT( MVL, V(1,p), 1,
$ V(1,q), 1, CS, CONJG(OMPQ)*T )
END IF
SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ1 ) )
AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ1 ) )
MXSINJ = MAX( MXSINJ, ABS( T ) )
ELSE
*
* .. choose correct signum for THETA and rotate
*
THSIGN = -SIGN( ONE, AAPQ1 )
IF( AAQQ.GT.AAPP0 )THSIGN = -THSIGN
T = ONE / ( THETA+THSIGN*
$ SQRT( ONE+THETA*THETA ) )
CS = SQRT( ONE / ( ONE+T*T ) )
SN = T*CS
MXSINJ = MAX( MXSINJ, ABS( SN ) )
SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE+T*APOAQ*AAPQ1 ) )
AAPP = AAPP*SQRT( MAX( ZERO,
$ ONE-T*AQOAP*AAPQ1 ) )
*
CALL CROT( M, A(1,p), 1, A(1,q), 1,
$ CS, CONJG(OMPQ)*SN )
IF( RSVEC ) THEN
CALL CROT( MVL, V(1,p), 1,
$ V(1,q), 1, CS, CONJG(OMPQ)*SN )
END IF
END IF
D(p) = -D(q) * OMPQ
*
ELSE
* .. have to use modified Gram-Schmidt like transformation
IF( AAPP.GT.AAQQ ) THEN
CALL CCOPY( M, A( 1, p ), 1,
$ WORK, 1 )
CALL CLASCL( 'G', 0, 0, AAPP, ONE,
$ M, 1, WORK,LDA,
$ IERR )
CALL CLASCL( 'G', 0, 0, AAQQ, ONE,
$ M, 1, A( 1, q ), LDA,
$ IERR )
CALL CAXPY( M, -AAPQ, WORK,
$ 1, A( 1, q ), 1 )
CALL CLASCL( 'G', 0, 0, ONE, AAQQ,
$ M, 1, A( 1, q ), LDA,
$ IERR )
SVA( q ) = AAQQ*SQRT( MAX( ZERO,
$ ONE-AAPQ1*AAPQ1 ) )
MXSINJ = MAX( MXSINJ, SFMIN )
ELSE
CALL CCOPY( M, A( 1, q ), 1,
$ WORK, 1 )
CALL CLASCL( 'G', 0, 0, AAQQ, ONE,
$ M, 1, WORK,LDA,
$ IERR )
CALL CLASCL( 'G', 0, 0, AAPP, ONE,
$ M, 1, A( 1, p ), LDA,
$ IERR )
CALL CAXPY( M, -CONJG(AAPQ),
$ WORK, 1, A( 1, p ), 1 )
CALL CLASCL( 'G', 0, 0, ONE, AAPP,
$ M, 1, A( 1, p ), LDA,
$ IERR )
SVA( p ) = AAPP*SQRT( MAX( ZERO,
$ ONE-AAPQ1*AAPQ1 ) )
MXSINJ = MAX( MXSINJ, SFMIN )
END IF
END IF
* END IF ROTOK THEN ... ELSE
*
* In the case of cancellation in updating SVA(q), SVA(p)
* .. recompute SVA(q), SVA(p)
IF( ( SVA( q ) / AAQQ )**2.LE.ROOTEPS )
$ THEN
IF( ( AAQQ.LT.ROOTBIG ) .AND.
$ ( AAQQ.GT.ROOTSFMIN ) ) THEN
SVA( q ) = SCNRM2( M, A( 1, q ), 1)
ELSE
T = ZERO
AAQQ = ONE
CALL CLASSQ( M, A( 1, q ), 1, T,
$ AAQQ )
SVA( q ) = T*SQRT( AAQQ )
END IF
END IF
IF( ( AAPP / AAPP0 )**2.LE.ROOTEPS ) THEN
IF( ( AAPP.LT.ROOTBIG ) .AND.
$ ( AAPP.GT.ROOTSFMIN ) ) THEN
AAPP = SCNRM2( M, A( 1, p ), 1 )
ELSE
T = ZERO
AAPP = ONE
CALL CLASSQ( M, A( 1, p ), 1, T,
$ AAPP )
AAPP = T*SQRT( AAPP )
END IF
SVA( p ) = AAPP
END IF
* end of OK rotation
ELSE
NOTROT = NOTROT + 1
*[RTD] SKIPPED = SKIPPED + 1
PSKIPPED = PSKIPPED + 1
IJBLSK = IJBLSK + 1
END IF
ELSE
NOTROT = NOTROT + 1
PSKIPPED = PSKIPPED + 1
IJBLSK = IJBLSK + 1
END IF
*
IF( ( i.LE.SWBAND ) .AND. ( IJBLSK.GE.BLSKIP ) )
$ THEN
SVA( p ) = AAPP
NOTROT = 0
GO TO 2011
END IF
IF( ( i.LE.SWBAND ) .AND.
$ ( PSKIPPED.GT.ROWSKIP ) ) THEN
AAPP = -AAPP
NOTROT = 0
GO TO 2203
END IF
*
2200 CONTINUE
* end of the q-loop
2203 CONTINUE
*
SVA( p ) = AAPP
*
ELSE
*
IF( AAPP.EQ.ZERO )NOTROT = NOTROT +
$ MIN( jgl+KBL-1, N ) - jgl + 1
IF( AAPP.LT.ZERO )NOTROT = 0
*
END IF
*
2100 CONTINUE
* end of the p-loop
2010 CONTINUE
* end of the jbc-loop
2011 CONTINUE
*2011 bailed out of the jbc-loop
DO 2012 p = igl, MIN( igl+KBL-1, N )
SVA( p ) = ABS( SVA( p ) )
2012 CONTINUE
***
2000 CONTINUE
*2000 :: end of the ibr-loop
*
* .. update SVA(N)
IF( ( SVA( N ).LT.ROOTBIG ) .AND. ( SVA( N ).GT.ROOTSFMIN ) )
$ THEN
SVA( N ) = SCNRM2( M, A( 1, N ), 1 )
ELSE
T = ZERO
AAPP = ONE
CALL CLASSQ( M, A( 1, N ), 1, T, AAPP )
SVA( N ) = T*SQRT( AAPP )
END IF
*
* Additional steering devices
*
IF( ( i.LT.SWBAND ) .AND. ( ( MXAAPQ.LE.ROOTTOL ) .OR.
$ ( ISWROT.LE.N ) ) )SWBAND = i
*
IF( ( i.GT.SWBAND+1 ) .AND. ( MXAAPQ.LT.SQRT( REAL( N ) )*
$ TOL ) .AND. ( REAL( N )*MXAAPQ*MXSINJ.LT.TOL ) ) THEN
GO TO 1994
END IF
*
IF( NOTROT.GE.EMPTSW )GO TO 1994
*
1993 CONTINUE
* end i=1:NSWEEP loop
*
* #:( Reaching this point means that the procedure has not converged.
INFO = NSWEEP - 1
GO TO 1995
*
1994 CONTINUE
* #:) Reaching this point means numerical convergence after the i-th
* sweep.
*
INFO = 0
* #:) INFO = 0 confirms successful iterations.
1995 CONTINUE
*
* Sort the vector SVA() of column norms.
DO 5991 p = 1, N - 1
q = ISAMAX( N-p+1, SVA( p ), 1 ) + p - 1
IF( p.NE.q ) THEN
TEMP1 = SVA( p )
SVA( p ) = SVA( q )
SVA( q ) = TEMP1
AAPQ = D( p )
D( p ) = D( q )
D( q ) = AAPQ
CALL CSWAP( M, A( 1, p ), 1, A( 1, q ), 1 )
IF( RSVEC )CALL CSWAP( MVL, V( 1, p ), 1, V( 1, q ), 1 )
END IF
5991 CONTINUE
*
*
RETURN
* ..
* .. END OF CGSVJ1
* ..
END