SUBROUTINE SBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, \$ WORK, IWORK, INFO ) * * -- LAPACK routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. CHARACTER COMPQ, UPLO INTEGER INFO, LDU, LDVT, N * .. * .. Array Arguments .. INTEGER IQ( * ), IWORK( * ) REAL D( * ), E( * ), Q( * ), U( LDU, * ), \$ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * SBDSDC computes the singular value decomposition (SVD) of a real * N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT, * using a divide and conquer method, where S is a diagonal matrix * with non-negative diagonal elements (the singular values of B), and * U and VT are orthogonal matrices of left and right singular vectors, * respectively. SBDSDC can be used to compute all singular values, * and optionally, singular vectors or singular vectors in compact form. * * 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 X-MP, Cray Y-MP, Cray C-90, or Cray-2. * It could conceivably fail on hexadecimal or decimal machines * without guard digits, but we know of none. See SLASD3 for details. * * The code currently calls SLASDQ if singular values only are desired. * However, it can be slightly modified to compute singular values * using the divide and conquer method. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': B is upper bidiagonal. * = 'L': B is lower bidiagonal. * * COMPQ (input) CHARACTER*1 * Specifies whether singular vectors are to be computed * as follows: * = 'N': Compute singular values only; * = 'P': Compute singular values and compute singular * vectors in compact form; * = 'I': Compute singular values and singular vectors. * * N (input) INTEGER * The order of the matrix B. N >= 0. * * D (input/output) REAL array, dimension (N) * On entry, the n diagonal elements of the bidiagonal matrix B. * On exit, if INFO=0, the singular values of B. * * E (input/output) REAL array, dimension (N-1) * On entry, the elements of E contain the offdiagonal * elements of the bidiagonal matrix whose SVD is desired. * On exit, E has been destroyed. * * U (output) REAL array, dimension (LDU,N) * If COMPQ = 'I', then: * On exit, if INFO = 0, U contains the left singular vectors * of the bidiagonal matrix. * For other values of COMPQ, U is not referenced. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= 1. * If singular vectors are desired, then LDU >= max( 1, N ). * * VT (output) REAL array, dimension (LDVT,N) * If COMPQ = 'I', then: * On exit, if INFO = 0, VT' contains the right singular * vectors of the bidiagonal matrix. * For other values of COMPQ, VT is not referenced. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= 1. * If singular vectors are desired, then LDVT >= max( 1, N ). * * Q (output) REAL array, dimension (LDQ) * If COMPQ = 'P', then: * On exit, if INFO = 0, Q and IQ contain the left * and right singular vectors in a compact form, * requiring O(N log N) space instead of 2*N**2. * In particular, Q contains all the REAL data in * LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1)))) * words of memory, where SMLSIZ is returned by ILAENV and * is equal to the maximum size of the subproblems at the * bottom of the computation tree (usually about 25). * For other values of COMPQ, Q is not referenced. * * IQ (output) INTEGER array, dimension (LDIQ) * If COMPQ = 'P', then: * On exit, if INFO = 0, Q and IQ contain the left * and right singular vectors in a compact form, * requiring O(N log N) space instead of 2*N**2. * In particular, IQ contains all INTEGER data in * LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1)))) * words of memory, where SMLSIZ is returned by ILAENV and * is equal to the maximum size of the subproblems at the * bottom of the computation tree (usually about 25). * For other values of COMPQ, IQ is not referenced. * * WORK (workspace) REAL array, dimension (MAX(1,LWORK)) * If COMPQ = 'N' then LWORK >= (4 * N). * If COMPQ = 'P' then LWORK >= (6 * N). * If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N). * * IWORK (workspace) INTEGER array, dimension (8*N) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: The algorithm failed to compute an singular value. * The update process of divide and conquer failed. * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * ===================================================================== * Changed dimension statement in comment describing E from (N) to * (N-1). Sven, 17 Feb 05. * ===================================================================== * * .. Parameters .. REAL ZERO, ONE, TWO PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0, TWO = 2.0E+0 ) * .. * .. Local Scalars .. INTEGER DIFL, DIFR, GIVCOL, GIVNUM, GIVPTR, I, IC, \$ ICOMPQ, IERR, II, IS, IU, IUPLO, IVT, J, K, KK, \$ MLVL, NM1, NSIZE, PERM, POLES, QSTART, SMLSIZ, \$ SMLSZP, SQRE, START, WSTART, Z REAL CS, EPS, ORGNRM, P, R, SN * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV REAL SLAMCH, SLANST EXTERNAL SLAMCH, SLANST, ILAENV, LSAME * .. * .. External Subroutines .. EXTERNAL SCOPY, SLARTG, SLASCL, SLASD0, SLASDA, SLASDQ, \$ SLASET, SLASR, SSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC REAL, ABS, INT, LOG, SIGN * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IUPLO = 0 IF( LSAME( UPLO, 'U' ) ) \$ IUPLO = 1 IF( LSAME( UPLO, 'L' ) ) \$ IUPLO = 2 IF( LSAME( COMPQ, 'N' ) ) THEN ICOMPQ = 0 ELSE IF( LSAME( COMPQ, 'P' ) ) THEN ICOMPQ = 1 ELSE IF( LSAME( COMPQ, 'I' ) ) THEN ICOMPQ = 2 ELSE ICOMPQ = -1 END IF IF( IUPLO.EQ.0 ) THEN INFO = -1 ELSE IF( ICOMPQ.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( ( LDU.LT.1 ) .OR. ( ( ICOMPQ.EQ.2 ) .AND. ( LDU.LT. \$ N ) ) ) THEN INFO = -7 ELSE IF( ( LDVT.LT.1 ) .OR. ( ( ICOMPQ.EQ.2 ) .AND. ( LDVT.LT. \$ N ) ) ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'SBDSDC', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) \$ RETURN SMLSIZ = ILAENV( 9, 'SBDSDC', ' ', 0, 0, 0, 0 ) IF( N.EQ.1 ) THEN IF( ICOMPQ.EQ.1 ) THEN Q( 1 ) = SIGN( ONE, D( 1 ) ) Q( 1+SMLSIZ*N ) = ONE ELSE IF( ICOMPQ.EQ.2 ) THEN U( 1, 1 ) = SIGN( ONE, D( 1 ) ) VT( 1, 1 ) = ONE END IF D( 1 ) = ABS( D( 1 ) ) RETURN END IF NM1 = N - 1 * * If matrix lower bidiagonal, rotate to be upper bidiagonal * by applying Givens rotations on the left * WSTART = 1 QSTART = 3 IF( ICOMPQ.EQ.1 ) THEN CALL SCOPY( N, D, 1, Q( 1 ), 1 ) CALL SCOPY( N-1, E, 1, Q( N+1 ), 1 ) END IF IF( IUPLO.EQ.2 ) THEN QSTART = 5 WSTART = 2*N - 1 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( ICOMPQ.EQ.1 ) THEN Q( I+2*N ) = CS Q( I+3*N ) = SN ELSE IF( ICOMPQ.EQ.2 ) THEN WORK( I ) = CS WORK( NM1+I ) = -SN END IF 10 CONTINUE END IF * * If ICOMPQ = 0, use SLASDQ to compute the singular values. * IF( ICOMPQ.EQ.0 ) THEN CALL SLASDQ( 'U', 0, N, 0, 0, 0, D, E, VT, LDVT, U, LDU, U, \$ LDU, WORK( WSTART ), INFO ) GO TO 40 END IF * * If N is smaller than the minimum divide size SMLSIZ, then solve * the problem with another solver. * IF( N.LE.SMLSIZ ) THEN IF( ICOMPQ.EQ.2 ) THEN CALL SLASET( 'A', N, N, ZERO, ONE, U, LDU ) CALL SLASET( 'A', N, N, ZERO, ONE, VT, LDVT ) CALL SLASDQ( 'U', 0, N, N, N, 0, D, E, VT, LDVT, U, LDU, U, \$ LDU, WORK( WSTART ), INFO ) ELSE IF( ICOMPQ.EQ.1 ) THEN IU = 1 IVT = IU + N CALL SLASET( 'A', N, N, ZERO, ONE, Q( IU+( QSTART-1 )*N ), \$ N ) CALL SLASET( 'A', N, N, ZERO, ONE, Q( IVT+( QSTART-1 )*N ), \$ N ) CALL SLASDQ( 'U', 0, N, N, N, 0, D, E, \$ Q( IVT+( QSTART-1 )*N ), N, \$ Q( IU+( QSTART-1 )*N ), N, \$ Q( IU+( QSTART-1 )*N ), N, WORK( WSTART ), \$ INFO ) END IF GO TO 40 END IF * IF( ICOMPQ.EQ.2 ) THEN CALL SLASET( 'A', N, N, ZERO, ONE, U, LDU ) CALL SLASET( 'A', N, N, ZERO, ONE, VT, LDVT ) END IF * * Scale. * ORGNRM = SLANST( 'M', N, D, E ) IF( ORGNRM.EQ.ZERO ) \$ RETURN CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, IERR ) CALL SLASCL( 'G', 0, 0, ORGNRM, ONE, NM1, 1, E, NM1, IERR ) * EPS = SLAMCH( 'Epsilon' ) * MLVL = INT( LOG( REAL( N ) / REAL( SMLSIZ+1 ) ) / LOG( TWO ) ) + 1 SMLSZP = SMLSIZ + 1 * IF( ICOMPQ.EQ.1 ) THEN IU = 1 IVT = 1 + SMLSIZ DIFL = IVT + SMLSZP DIFR = DIFL + MLVL Z = DIFR + MLVL*2 IC = Z + MLVL IS = IC + 1 POLES = IS + 1 GIVNUM = POLES + 2*MLVL * K = 1 GIVPTR = 2 PERM = 3 GIVCOL = PERM + MLVL END IF * DO 20 I = 1, N IF( ABS( D( I ) ).LT.EPS ) THEN D( I ) = SIGN( EPS, D( I ) ) END IF 20 CONTINUE * START = 1 SQRE = 0 * DO 30 I = 1, NM1 IF( ( ABS( E( I ) ).LT.EPS ) .OR. ( I.EQ.NM1 ) ) THEN * * 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 - START + 1 ELSE IF( ABS( E( I ) ).GE.EPS ) THEN * * A subproblem with E(NM1) not too small but I = NM1. * NSIZE = N - START + 1 ELSE * * A subproblem with E(NM1) small. This implies an * 1-by-1 subproblem at D(N). Solve this 1-by-1 problem * first. * NSIZE = I - START + 1 IF( ICOMPQ.EQ.2 ) THEN U( N, N ) = SIGN( ONE, D( N ) ) VT( N, N ) = ONE ELSE IF( ICOMPQ.EQ.1 ) THEN Q( N+( QSTART-1 )*N ) = SIGN( ONE, D( N ) ) Q( N+( SMLSIZ+QSTART-1 )*N ) = ONE END IF D( N ) = ABS( D( N ) ) END IF IF( ICOMPQ.EQ.2 ) THEN CALL SLASD0( NSIZE, SQRE, D( START ), E( START ), \$ U( START, START ), LDU, VT( START, START ), \$ LDVT, SMLSIZ, IWORK, WORK( WSTART ), INFO ) ELSE CALL SLASDA( ICOMPQ, SMLSIZ, NSIZE, SQRE, D( START ), \$ E( START ), Q( START+( IU+QSTART-2 )*N ), N, \$ Q( START+( IVT+QSTART-2 )*N ), \$ IQ( START+K*N ), Q( START+( DIFL+QSTART-2 )* \$ N ), Q( START+( DIFR+QSTART-2 )*N ), \$ Q( START+( Z+QSTART-2 )*N ), \$ Q( START+( POLES+QSTART-2 )*N ), \$ IQ( START+GIVPTR*N ), IQ( START+GIVCOL*N ), \$ N, IQ( START+PERM*N ), \$ Q( START+( GIVNUM+QSTART-2 )*N ), \$ Q( START+( IC+QSTART-2 )*N ), \$ Q( START+( IS+QSTART-2 )*N ), \$ WORK( WSTART ), IWORK, INFO ) IF( INFO.NE.0 ) THEN RETURN END IF END IF START = I + 1 END IF 30 CONTINUE * * Unscale * CALL SLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, IERR ) 40 CONTINUE * * Use Selection Sort to minimize swaps of singular vectors * DO 60 II = 2, N I = II - 1 KK = I P = D( I ) DO 50 J = II, N IF( D( J ).GT.P ) THEN KK = J P = D( J ) END IF 50 CONTINUE IF( KK.NE.I ) THEN D( KK ) = D( I ) D( I ) = P IF( ICOMPQ.EQ.1 ) THEN IQ( I ) = KK ELSE IF( ICOMPQ.EQ.2 ) THEN CALL SSWAP( N, U( 1, I ), 1, U( 1, KK ), 1 ) CALL SSWAP( N, VT( I, 1 ), LDVT, VT( KK, 1 ), LDVT ) END IF ELSE IF( ICOMPQ.EQ.1 ) THEN IQ( I ) = I END IF 60 CONTINUE * * If ICOMPQ = 1, use IQ(N,1) as the indicator for UPLO * IF( ICOMPQ.EQ.1 ) THEN IF( IUPLO.EQ.1 ) THEN IQ( N ) = 1 ELSE IQ( N ) = 0 END IF END IF * * If B is lower bidiagonal, update U by those Givens rotations * which rotated B to be upper bidiagonal * IF( ( IUPLO.EQ.2 ) .AND. ( ICOMPQ.EQ.2 ) ) \$ CALL SLASR( 'L', 'V', 'B', N, N, WORK( 1 ), WORK( N ), U, LDU ) * RETURN * * End of SBDSDC * END