📄 dbdsdc.f
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SUBROUTINE DBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, $ WORK, IWORK, INFO )** -- LAPACK routine (instrumented to count ops, version 3.0) --* Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,* Courant Institute, Argonne National Lab, and Rice University* October 31, 1999** .. Scalar Arguments .. CHARACTER COMPQ, UPLO INTEGER INFO, LDU, LDVT, N* ..* .. Array Arguments .. INTEGER IQ( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), Q( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * )* ..* .. Common blocks .. COMMON / LATIME / OPS, ITCNT* ..* .. Scalars in Common .. DOUBLE PRECISION ITCNT, OPS* ..** Purpose* =======** DBDSDC 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. DBDSDC 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 DLASD3 for details.** The code currently call DLASDQ 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) DOUBLE PRECISION 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) DOUBLE PRECISION array, dimension (N)* 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) DOUBLE PRECISION 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) DOUBLE PRECISION 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) DOUBLE PRECISION 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 DOUBLE PRECISION 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) DOUBLE PRECISION array, dimension (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 (7*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** =====================================================================** .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+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 DOUBLE PRECISION CS, EPS, ORGNRM, P, R, SN* ..* .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, ILAENV, DLAMCH, DLANST* ..* .. External Subroutines .. EXTERNAL DCOPY, DLARTG, DLASCL, DLASD0, DLASDA, DLASDQ, $ DLASET, DLASR, DSWAP, XERBLA* ..* .. Intrinsic Functions .. INTRINSIC ABS, DBLE, 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( 'DBDSDC', -INFO ) RETURN END IF** Quick return if possible* IF( N.EQ.0 ) $ RETURN SMLSIZ = ILAENV( 9, 'DBDSDC', ' ', 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 DCOPY( N, D, 1, Q( 1 ), 1 ) CALL DCOPY( N-1, E, 1, Q( N+1 ), 1 ) END IF IF( IUPLO.EQ.2 ) THEN QSTART = 5 WSTART = 2*N - 1 OPS = OPS + DBLE( 8*( N-1 ) ) DO 10 I = 1, N - 1 CALL DLARTG( 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 DLASDQ to compute the singular values.* IF( ICOMPQ.EQ.0 ) THEN CALL DLASDQ( '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 DLASET( 'A', N, N, ZERO, ONE, U, LDU ) CALL DLASET( 'A', N, N, ZERO, ONE, VT, LDVT ) CALL DLASDQ( '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 DLASET( 'A', N, N, ZERO, ONE, Q( IU+( QSTART-1 )*N ), $ N ) CALL DLASET( 'A', N, N, ZERO, ONE, Q( IVT+( QSTART-1 )*N ), $ N ) CALL DLASDQ( '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 DLASET( 'A', N, N, ZERO, ONE, U, LDU ) CALL DLASET( 'A', N, N, ZERO, ONE, VT, LDVT ) END IF** Scale.* ORGNRM = DLANST( 'M', N, D, E ) IF( ORGNRM.EQ.ZERO ) $ RETURN OPS = OPS + DBLE( N+NM1 ) CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, IERR ) CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, NM1, 1, E, NM1, IERR )* EPS = DLAMCH( 'Epsilon' )* MLVL = INT( LOG( DBLE( N ) / DBLE( 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 DLASD0( NSIZE, SQRE, D( START ), E( START ), $ U( START, START ), LDU, VT( START, START ), $ LDVT, SMLSIZ, IWORK, WORK( WSTART ), INFO ) ELSE CALL DLASDA( 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* OPS = OPS + DBLE( N ) CALL DLASCL( '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 DSWAP( N, U( 1, I ), 1, U( 1, KK ), 1 ) CALL DSWAP( 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 ) ) THEN OPS = OPS + DBLE( 6*( N-1 )*N ) CALL DLASR( 'L', 'V', 'B', N, N, WORK( 1 ), WORK( N ), U, LDU ) END IF* RETURN** End of DBDSDC* END
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