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- *> \brief \b SLALSD uses the singular value decomposition of A to solve the least squares problem.
- *
- * =========== DOCUMENTATION ===========
- *
- * Online html documentation available at
- * http://www.netlib.org/lapack/explore-html/
- *
- *> \htmlonly
- *> Download SLALSD + dependencies
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/slalsd.f">
- *> [TGZ]</a>
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/slalsd.f">
- *> [ZIP]</a>
- *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/slalsd.f">
- *> [TXT]</a>
- *> \endhtmlonly
- *
- * Definition:
- * ===========
- *
- * SUBROUTINE SLALSD( UPLO, SMLSIZ, N, NRHS, D, E, B, LDB, RCOND,
- * RANK, WORK, IWORK, INFO )
- *
- * .. Scalar Arguments ..
- * CHARACTER UPLO
- * INTEGER INFO, LDB, N, NRHS, RANK, SMLSIZ
- * REAL RCOND
- * ..
- * .. Array Arguments ..
- * INTEGER IWORK( * )
- * REAL B( LDB, * ), D( * ), E( * ), WORK( * )
- * ..
- *
- *
- *> \par Purpose:
- * =============
- *>
- *> \verbatim
- *>
- *> SLALSD uses the singular value decomposition of A to solve the least
- *> squares problem of finding X to minimize the Euclidean norm of each
- *> column of A*X-B, where A is N-by-N upper bidiagonal, and X and B
- *> are N-by-NRHS. The solution X overwrites B.
- *>
- *> The singular values of A smaller than RCOND times the largest
- *> singular value are treated as zero in solving the least squares
- *> problem; in this case a minimum norm solution is returned.
- *> The actual singular values are returned in D in ascending order.
- *>
- *> This code makes very mild assumptions about floating point
- *> arithmetic. It will work on machines with a guard digit in
- *> add/subtract, or on those binary machines without guard digits
- *> which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2.
- *> It could conceivably fail on hexadecimal or decimal machines
- *> without guard digits, but we know of none.
- *> \endverbatim
- *
- * Arguments:
- * ==========
- *
- *> \param[in] UPLO
- *> \verbatim
- *> UPLO is CHARACTER*1
- *> = 'U': D and E define an upper bidiagonal matrix.
- *> = 'L': D and E define a lower bidiagonal matrix.
- *> \endverbatim
- *>
- *> \param[in] SMLSIZ
- *> \verbatim
- *> SMLSIZ is INTEGER
- *> The maximum size of the subproblems at the bottom of the
- *> computation tree.
- *> \endverbatim
- *>
- *> \param[in] N
- *> \verbatim
- *> N is INTEGER
- *> The dimension of the bidiagonal matrix. N >= 0.
- *> \endverbatim
- *>
- *> \param[in] NRHS
- *> \verbatim
- *> NRHS is INTEGER
- *> The number of columns of B. NRHS must be at least 1.
- *> \endverbatim
- *>
- *> \param[in,out] D
- *> \verbatim
- *> D is REAL array, dimension (N)
- *> On entry D contains the main diagonal of the bidiagonal
- *> matrix. On exit, if INFO = 0, D contains its singular values.
- *> \endverbatim
- *>
- *> \param[in,out] E
- *> \verbatim
- *> E is REAL array, dimension (N-1)
- *> Contains the super-diagonal entries of the bidiagonal matrix.
- *> On exit, E has been destroyed.
- *> \endverbatim
- *>
- *> \param[in,out] B
- *> \verbatim
- *> B is REAL array, dimension (LDB,NRHS)
- *> On input, B contains the right hand sides of the least
- *> squares problem. On output, B contains the solution X.
- *> \endverbatim
- *>
- *> \param[in] LDB
- *> \verbatim
- *> LDB is INTEGER
- *> The leading dimension of B in the calling subprogram.
- *> LDB must be at least max(1,N).
- *> \endverbatim
- *>
- *> \param[in] RCOND
- *> \verbatim
- *> RCOND is REAL
- *> The singular values of A less than or equal to RCOND times
- *> the largest singular value are treated as zero in solving
- *> the least squares problem. If RCOND is negative,
- *> machine precision is used instead.
- *> For example, if diag(S)*X=B were the least squares problem,
- *> where diag(S) is a diagonal matrix of singular values, the
- *> solution would be X(i) = B(i) / S(i) if S(i) is greater than
- *> RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to
- *> RCOND*max(S).
- *> \endverbatim
- *>
- *> \param[out] RANK
- *> \verbatim
- *> RANK is INTEGER
- *> The number of singular values of A greater than RCOND times
- *> the largest singular value.
- *> \endverbatim
- *>
- *> \param[out] WORK
- *> \verbatim
- *> WORK is REAL array, dimension at least
- *> (9*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2),
- *> where NLVL = max(0, INT(log_2 (N/(SMLSIZ+1))) + 1).
- *> \endverbatim
- *>
- *> \param[out] IWORK
- *> \verbatim
- *> IWORK is INTEGER array, dimension at least
- *> (3*N*NLVL + 11*N)
- *> \endverbatim
- *>
- *> \param[out] INFO
- *> \verbatim
- *> INFO is INTEGER
- *> = 0: successful exit.
- *> < 0: if INFO = -i, the i-th argument had an illegal value.
- *> > 0: The algorithm failed to compute a singular value while
- *> working on the submatrix lying in rows and columns
- *> INFO/(N+1) through MOD(INFO,N+1).
- *> \endverbatim
- *
- * Authors:
- * ========
- *
- *> \author Univ. of Tennessee
- *> \author Univ. of California Berkeley
- *> \author Univ. of Colorado Denver
- *> \author NAG Ltd.
- *
- *> \ingroup realOTHERcomputational
- *
- *> \par Contributors:
- * ==================
- *>
- *> Ming Gu and Ren-Cang Li, Computer Science Division, University of
- *> California at Berkeley, USA \n
- *> Osni Marques, LBNL/NERSC, USA \n
- *
- * =====================================================================
- SUBROUTINE SLALSD( UPLO, SMLSIZ, N, NRHS, D, E, B, LDB, RCOND,
- $ RANK, WORK, IWORK, 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 ..
- CHARACTER UPLO
- INTEGER INFO, LDB, N, NRHS, RANK, SMLSIZ
- REAL RCOND
- * ..
- * .. Array Arguments ..
- INTEGER IWORK( * )
- REAL B( LDB, * ), D( * ), E( * ), WORK( * )
- * ..
- *
- * =====================================================================
- *
- * .. Parameters ..
- REAL ZERO, ONE, TWO
- PARAMETER ( ZERO = 0.0E0, ONE = 1.0E0, TWO = 2.0E0 )
- * ..
- * .. Local Scalars ..
- INTEGER BX, BXST, C, DIFL, DIFR, GIVCOL, GIVNUM,
- $ GIVPTR, I, ICMPQ1, ICMPQ2, IWK, J, K, NLVL,
- $ NM1, NSIZE, NSUB, NWORK, PERM, POLES, S, SIZEI,
- $ SMLSZP, SQRE, ST, ST1, U, VT, Z
- REAL CS, EPS, ORGNRM, R, RCND, SN, TOL
- * ..
- * .. External Functions ..
- INTEGER ISAMAX
- REAL SLAMCH, SLANST
- EXTERNAL ISAMAX, SLAMCH, SLANST
- * ..
- * .. External Subroutines ..
- EXTERNAL SCOPY, SGEMM, SLACPY, SLALSA, SLARTG, SLASCL,
- $ SLASDA, SLASDQ, SLASET, SLASRT, SROT, XERBLA
- * ..
- * .. Intrinsic Functions ..
- INTRINSIC ABS, INT, LOG, REAL, SIGN
- * ..
- * .. Executable Statements ..
- *
- * Test the input parameters.
- *
- INFO = 0
- *
- IF( N.LT.0 ) THEN
- INFO = -3
- ELSE IF( NRHS.LT.1 ) THEN
- INFO = -4
- ELSE IF( ( LDB.LT.1 ) .OR. ( LDB.LT.N ) ) THEN
- INFO = -8
- END IF
- IF( INFO.NE.0 ) THEN
- CALL XERBLA( 'SLALSD', -INFO )
- RETURN
- END IF
- *
- EPS = SLAMCH( 'Epsilon' )
- *
- * Set up the tolerance.
- *
- IF( ( RCOND.LE.ZERO ) .OR. ( RCOND.GE.ONE ) ) THEN
- RCND = EPS
- ELSE
- RCND = RCOND
- END IF
- *
- RANK = 0
- *
- * Quick return if possible.
- *
- IF( N.EQ.0 ) THEN
- RETURN
- ELSE IF( N.EQ.1 ) THEN
- IF( D( 1 ).EQ.ZERO ) THEN
- CALL SLASET( 'A', 1, NRHS, ZERO, ZERO, B, LDB )
- ELSE
- RANK = 1
- CALL SLASCL( 'G', 0, 0, D( 1 ), ONE, 1, NRHS, B, LDB, INFO )
- D( 1 ) = ABS( D( 1 ) )
- END IF
- RETURN
- END IF
- *
- * Rotate the matrix if it is lower bidiagonal.
- *
- IF( UPLO.EQ.'L' ) THEN
- DO 10 I = 1, N - 1
- CALL SLARTG( D( I ), E( I ), CS, SN, R )
- D( I ) = R
- E( I ) = SN*D( I+1 )
- D( I+1 ) = CS*D( I+1 )
- IF( NRHS.EQ.1 ) THEN
- CALL SROT( 1, B( I, 1 ), 1, B( I+1, 1 ), 1, CS, SN )
- ELSE
- WORK( I*2-1 ) = CS
- WORK( I*2 ) = SN
- END IF
- 10 CONTINUE
- IF( NRHS.GT.1 ) THEN
- DO 30 I = 1, NRHS
- DO 20 J = 1, N - 1
- CS = WORK( J*2-1 )
- SN = WORK( J*2 )
- CALL SROT( 1, B( J, I ), 1, B( J+1, I ), 1, CS, SN )
- 20 CONTINUE
- 30 CONTINUE
- END IF
- END IF
- *
- * Scale.
- *
- NM1 = N - 1
- ORGNRM = SLANST( 'M', N, D, E )
- IF( ORGNRM.EQ.ZERO ) THEN
- CALL SLASET( 'A', N, NRHS, ZERO, ZERO, B, LDB )
- RETURN
- END IF
- *
- CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, INFO )
- CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, NM1, 1, E, NM1, INFO )
- *
- * If N is smaller than the minimum divide size SMLSIZ, then solve
- * the problem with another solver.
- *
- IF( N.LE.SMLSIZ ) THEN
- NWORK = 1 + N*N
- CALL SLASET( 'A', N, N, ZERO, ONE, WORK, N )
- CALL SLASDQ( 'U', 0, N, N, 0, NRHS, D, E, WORK, N, WORK, N, B,
- $ LDB, WORK( NWORK ), INFO )
- IF( INFO.NE.0 ) THEN
- RETURN
- END IF
- TOL = RCND*ABS( D( ISAMAX( N, D, 1 ) ) )
- DO 40 I = 1, N
- IF( D( I ).LE.TOL ) THEN
- CALL SLASET( 'A', 1, NRHS, ZERO, ZERO, B( I, 1 ), LDB )
- ELSE
- CALL SLASCL( 'G', 0, 0, D( I ), ONE, 1, NRHS, B( I, 1 ),
- $ LDB, INFO )
- RANK = RANK + 1
- END IF
- 40 CONTINUE
- CALL SGEMM( 'T', 'N', N, NRHS, N, ONE, WORK, N, B, LDB, ZERO,
- $ WORK( NWORK ), N )
- CALL SLACPY( 'A', N, NRHS, WORK( NWORK ), N, B, LDB )
- *
- * Unscale.
- *
- CALL SLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, INFO )
- CALL SLASRT( 'D', N, D, INFO )
- CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, N, NRHS, B, LDB, INFO )
- *
- RETURN
- END IF
- *
- * Book-keeping and setting up some constants.
- *
- NLVL = INT( LOG( REAL( N ) / REAL( SMLSIZ+1 ) ) / LOG( TWO ) ) + 1
- *
- SMLSZP = SMLSIZ + 1
- *
- U = 1
- VT = 1 + SMLSIZ*N
- DIFL = VT + SMLSZP*N
- DIFR = DIFL + NLVL*N
- Z = DIFR + NLVL*N*2
- C = Z + NLVL*N
- S = C + N
- POLES = S + N
- GIVNUM = POLES + 2*NLVL*N
- BX = GIVNUM + 2*NLVL*N
- NWORK = BX + N*NRHS
- *
- SIZEI = 1 + N
- K = SIZEI + N
- GIVPTR = K + N
- PERM = GIVPTR + N
- GIVCOL = PERM + NLVL*N
- IWK = GIVCOL + NLVL*N*2
- *
- ST = 1
- SQRE = 0
- ICMPQ1 = 1
- ICMPQ2 = 0
- NSUB = 0
- *
- DO 50 I = 1, N
- IF( ABS( D( I ) ).LT.EPS ) THEN
- D( I ) = SIGN( EPS, D( I ) )
- END IF
- 50 CONTINUE
- *
- DO 60 I = 1, NM1
- IF( ( ABS( E( I ) ).LT.EPS ) .OR. ( I.EQ.NM1 ) ) THEN
- NSUB = NSUB + 1
- IWORK( NSUB ) = ST
- *
- * Subproblem found. First determine its size and then
- * apply divide and conquer on it.
- *
- IF( I.LT.NM1 ) THEN
- *
- * A subproblem with E(I) small for I < NM1.
- *
- NSIZE = I - ST + 1
- IWORK( SIZEI+NSUB-1 ) = NSIZE
- ELSE IF( ABS( E( I ) ).GE.EPS ) THEN
- *
- * A subproblem with E(NM1) not too small but I = NM1.
- *
- NSIZE = N - ST + 1
- IWORK( SIZEI+NSUB-1 ) = NSIZE
- ELSE
- *
- * A subproblem with E(NM1) small. This implies an
- * 1-by-1 subproblem at D(N), which is not solved
- * explicitly.
- *
- NSIZE = I - ST + 1
- IWORK( SIZEI+NSUB-1 ) = NSIZE
- NSUB = NSUB + 1
- IWORK( NSUB ) = N
- IWORK( SIZEI+NSUB-1 ) = 1
- CALL SCOPY( NRHS, B( N, 1 ), LDB, WORK( BX+NM1 ), N )
- END IF
- ST1 = ST - 1
- IF( NSIZE.EQ.1 ) THEN
- *
- * This is a 1-by-1 subproblem and is not solved
- * explicitly.
- *
- CALL SCOPY( NRHS, B( ST, 1 ), LDB, WORK( BX+ST1 ), N )
- ELSE IF( NSIZE.LE.SMLSIZ ) THEN
- *
- * This is a small subproblem and is solved by SLASDQ.
- *
- CALL SLASET( 'A', NSIZE, NSIZE, ZERO, ONE,
- $ WORK( VT+ST1 ), N )
- CALL SLASDQ( 'U', 0, NSIZE, NSIZE, 0, NRHS, D( ST ),
- $ E( ST ), WORK( VT+ST1 ), N, WORK( NWORK ),
- $ N, B( ST, 1 ), LDB, WORK( NWORK ), INFO )
- IF( INFO.NE.0 ) THEN
- RETURN
- END IF
- CALL SLACPY( 'A', NSIZE, NRHS, B( ST, 1 ), LDB,
- $ WORK( BX+ST1 ), N )
- ELSE
- *
- * A large problem. Solve it using divide and conquer.
- *
- CALL SLASDA( ICMPQ1, SMLSIZ, NSIZE, SQRE, D( ST ),
- $ E( ST ), WORK( U+ST1 ), N, WORK( VT+ST1 ),
- $ IWORK( K+ST1 ), WORK( DIFL+ST1 ),
- $ WORK( DIFR+ST1 ), WORK( Z+ST1 ),
- $ WORK( POLES+ST1 ), IWORK( GIVPTR+ST1 ),
- $ IWORK( GIVCOL+ST1 ), N, IWORK( PERM+ST1 ),
- $ WORK( GIVNUM+ST1 ), WORK( C+ST1 ),
- $ WORK( S+ST1 ), WORK( NWORK ), IWORK( IWK ),
- $ INFO )
- IF( INFO.NE.0 ) THEN
- RETURN
- END IF
- BXST = BX + ST1
- CALL SLALSA( ICMPQ2, SMLSIZ, NSIZE, NRHS, B( ST, 1 ),
- $ LDB, WORK( BXST ), N, WORK( U+ST1 ), N,
- $ WORK( VT+ST1 ), IWORK( K+ST1 ),
- $ WORK( DIFL+ST1 ), WORK( DIFR+ST1 ),
- $ WORK( Z+ST1 ), WORK( POLES+ST1 ),
- $ IWORK( GIVPTR+ST1 ), IWORK( GIVCOL+ST1 ), N,
- $ IWORK( PERM+ST1 ), WORK( GIVNUM+ST1 ),
- $ WORK( C+ST1 ), WORK( S+ST1 ), WORK( NWORK ),
- $ IWORK( IWK ), INFO )
- IF( INFO.NE.0 ) THEN
- RETURN
- END IF
- END IF
- ST = I + 1
- END IF
- 60 CONTINUE
- *
- * Apply the singular values and treat the tiny ones as zero.
- *
- TOL = RCND*ABS( D( ISAMAX( N, D, 1 ) ) )
- *
- DO 70 I = 1, N
- *
- * Some of the elements in D can be negative because 1-by-1
- * subproblems were not solved explicitly.
- *
- IF( ABS( D( I ) ).LE.TOL ) THEN
- CALL SLASET( 'A', 1, NRHS, ZERO, ZERO, WORK( BX+I-1 ), N )
- ELSE
- RANK = RANK + 1
- CALL SLASCL( 'G', 0, 0, D( I ), ONE, 1, NRHS,
- $ WORK( BX+I-1 ), N, INFO )
- END IF
- D( I ) = ABS( D( I ) )
- 70 CONTINUE
- *
- * Now apply back the right singular vectors.
- *
- ICMPQ2 = 1
- DO 80 I = 1, NSUB
- ST = IWORK( I )
- ST1 = ST - 1
- NSIZE = IWORK( SIZEI+I-1 )
- BXST = BX + ST1
- IF( NSIZE.EQ.1 ) THEN
- CALL SCOPY( NRHS, WORK( BXST ), N, B( ST, 1 ), LDB )
- ELSE IF( NSIZE.LE.SMLSIZ ) THEN
- CALL SGEMM( 'T', 'N', NSIZE, NRHS, NSIZE, ONE,
- $ WORK( VT+ST1 ), N, WORK( BXST ), N, ZERO,
- $ B( ST, 1 ), LDB )
- ELSE
- CALL SLALSA( ICMPQ2, SMLSIZ, NSIZE, NRHS, WORK( BXST ), N,
- $ B( ST, 1 ), LDB, WORK( U+ST1 ), N,
- $ WORK( VT+ST1 ), IWORK( K+ST1 ),
- $ WORK( DIFL+ST1 ), WORK( DIFR+ST1 ),
- $ WORK( Z+ST1 ), WORK( POLES+ST1 ),
- $ IWORK( GIVPTR+ST1 ), IWORK( GIVCOL+ST1 ), N,
- $ IWORK( PERM+ST1 ), WORK( GIVNUM+ST1 ),
- $ WORK( C+ST1 ), WORK( S+ST1 ), WORK( NWORK ),
- $ IWORK( IWK ), INFO )
- IF( INFO.NE.0 ) THEN
- RETURN
- END IF
- END IF
- 80 CONTINUE
- *
- * Unscale and sort the singular values.
- *
- CALL SLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, INFO )
- CALL SLASRT( 'D', N, D, INFO )
- CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, N, NRHS, B, LDB, INFO )
- *
- RETURN
- *
- * End of SLALSD
- *
- END
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