SUBROUTINE DBDSQR( UPLO, N, NCVT, NRU, NCC, D, E, VT, LDVT, U, $ LDU, C, LDC, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU * .. * .. Array Arguments .. DOUBLE PRECISION C( LDC, * ), D( * ), E( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DBDSQR computes the singular value decomposition (SVD) of a real * N-by-N (upper or lower) bidiagonal matrix B: B = Q * S * P' (P' * denotes the transpose of P), where S is a diagonal matrix with * non-negative diagonal elements (the singular values of B), and Q * and P are orthogonal matrices. * * The routine computes S, and optionally computes U * Q, P' * VT, * or Q' * C, for given real input matrices U, VT, and C. * * See "Computing Small Singular Values of Bidiagonal Matrices With * Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan, * LAPACK Working Note #3 (or SIAM J. Sci. Statist. Comput. vol. 11, * no. 5, pp. 873-912, Sept 1990) and * "Accurate singular values and differential qd algorithms," by * B. Parlett and V. Fernando, Technical Report CPAM-554, Mathematics * Department, University of California at Berkeley, July 1992 * for a detailed description of the algorithm. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': B is upper bidiagonal; * = 'L': B is lower bidiagonal. * * N (input) INTEGER * The order of the matrix B. N >= 0. * * NCVT (input) INTEGER * The number of columns of the matrix VT. NCVT >= 0. * * NRU (input) INTEGER * The number of rows of the matrix U. NRU >= 0. * * NCC (input) INTEGER * The number of columns of the matrix C. NCC >= 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 in decreasing * order. * * 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 normal exit (INFO = 0), E is destroyed. * If the algorithm does not converge (INFO > 0), D and E * will contain the diagonal and superdiagonal elements of a * bidiagonal matrix orthogonally equivalent to the one given * as input. E(N) is used for workspace. * * VT (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT) * On entry, an N-by-NCVT matrix VT. * On exit, VT is overwritten by P' * VT. * VT is not referenced if NCVT = 0. * * LDVT (input) INTEGER * The leading dimension of the array VT. * LDVT >= max(1,N) if NCVT > 0; LDVT >= 1 if NCVT = 0. * * U (input/output) DOUBLE PRECISION array, dimension (LDU, N) * On entry, an NRU-by-N matrix U. * On exit, U is overwritten by U * Q. * U is not referenced if NRU = 0. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= max(1,NRU). * * C (input/output) DOUBLE PRECISION array, dimension (LDC, NCC) * On entry, an N-by-NCC matrix C. * On exit, C is overwritten by Q' * C. * C is not referenced if NCC = 0. * * LDC (input) INTEGER * The leading dimension of the array C. * LDC >= max(1,N) if NCC > 0; LDC >=1 if NCC = 0. * * WORK (workspace) DOUBLE PRECISION array, dimension * 4*N if only singular values wanted (NCVT = NRU = NCC = 0) * max( 1, 4*N-4 ) otherwise * * INFO (output) INTEGER * = 0: successful exit * < 0: If INFO = -i, the i-th argument had an illegal value * > 0: the algorithm did not converge; D and E contain the * elements of a bidiagonal matrix which is orthogonally * similar to the input matrix B; if INFO = i, i * elements of E have not converged to zero. * * Internal Parameters * =================== * * TOLMUL DOUBLE PRECISION, default = max(10,min(100,EPS**(-1/8))) * TOLMUL controls the convergence criterion of the QR loop. * If it is positive, TOLMUL*EPS is the desired relative * precision in the computed singular values. * If it is negative, abs(TOLMUL*EPS*sigma_max) is the * desired absolute accuracy in the computed singular * values (corresponds to relative accuracy * abs(TOLMUL*EPS) in the largest singular value. * abs(TOLMUL) should be between 1 and 1/EPS, and preferably * between 10 (for fast convergence) and .1/EPS * (for there to be some accuracy in the results). * Default is to lose at either one eighth or 2 of the * available decimal digits in each computed singular value * (whichever is smaller). * * MAXITR INTEGER, default = 6 * MAXITR controls the maximum number of passes of the * algorithm through its inner loop. The algorithms stops * (and so fails to converge) if the number of passes * through the inner loop exceeds MAXITR*N**2. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION NEGONE PARAMETER ( NEGONE = -1.0D0 ) DOUBLE PRECISION HNDRTH PARAMETER ( HNDRTH = 0.01D0 ) DOUBLE PRECISION TEN PARAMETER ( TEN = 10.0D0 ) DOUBLE PRECISION HNDRD PARAMETER ( HNDRD = 100.0D0 ) DOUBLE PRECISION MEIGTH PARAMETER ( MEIGTH = -0.125D0 ) INTEGER MAXITR PARAMETER ( MAXITR = 6 ) * .. * .. Local Scalars .. LOGICAL LOWER, ROTATE INTEGER I, IDIR, ISUB, ITER, J, LL, LLL, M, MAXIT, NM1, $ NM12, NM13, OLDLL, OLDM DOUBLE PRECISION ABSE, ABSS, COSL, COSR, CS, EPS, F, G, H, MU, $ OLDCS, OLDSN, R, SHIFT, SIGMN, SIGMX, SINL, $ SINR, SLL, SMAX, SMIN, SMINL, SMINLO, SMINOA, $ SN, THRESH, TOL, TOLMUL, UNFL * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH EXTERNAL LSAME, DLAMCH * .. * .. External Subroutines .. EXTERNAL DLARTG, DLAS2, DLASQ1, DLASR, DLASV2, DROT, $ DSCAL, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, MAX, MIN, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 LOWER = LSAME( UPLO, 'L' ) IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LOWER ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( NCVT.LT.0 ) THEN INFO = -3 ELSE IF( NRU.LT.0 ) THEN INFO = -4 ELSE IF( NCC.LT.0 ) THEN INFO = -5 ELSE IF( ( NCVT.EQ.0 .AND. LDVT.LT.1 ) .OR. $ ( NCVT.GT.0 .AND. LDVT.LT.MAX( 1, N ) ) ) THEN INFO = -9 ELSE IF( LDU.LT.MAX( 1, NRU ) ) THEN INFO = -11 ELSE IF( ( NCC.EQ.0 .AND. LDC.LT.1 ) .OR. $ ( NCC.GT.0 .AND. LDC.LT.MAX( 1, N ) ) ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DBDSQR', -INFO ) RETURN END IF IF( N.EQ.0 ) $ RETURN IF( N.EQ.1 ) $ GO TO 160 * * ROTATE is true if any singular vectors desired, false otherwise * ROTATE = ( NCVT.GT.0 ) .OR. ( NRU.GT.0 ) .OR. ( NCC.GT.0 ) * * If no singular vectors desired, use qd algorithm * IF( .NOT.ROTATE ) THEN CALL DLASQ1( N, D, E, WORK, INFO ) RETURN END IF * NM1 = N - 1 NM12 = NM1 + NM1 NM13 = NM12 + NM1 IDIR = 0 * * Get machine constants * EPS = DLAMCH( 'Epsilon' ) UNFL = DLAMCH( 'Safe minimum' ) * * If matrix lower bidiagonal, rotate to be upper bidiagonal * by applying Givens rotations on the left * IF( LOWER ) THEN 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 ) WORK( I ) = CS WORK( NM1+I ) = SN 10 CONTINUE * * Update singular vectors if desired * IF( NRU.GT.0 ) $ CALL DLASR( 'R', 'V', 'F', NRU, N, WORK( 1 ), WORK( N ), U, $ LDU ) IF( NCC.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', N, NCC, WORK( 1 ), WORK( N ), C, $ LDC ) END IF * * Compute singular values to relative accuracy TOL * (By setting TOL to be negative, algorithm will compute * singular values to absolute accuracy ABS(TOL)*norm(input matrix)) * TOLMUL = MAX( TEN, MIN( HNDRD, EPS**MEIGTH ) ) TOL = TOLMUL*EPS * * Compute approximate maximum, minimum singular values * SMAX = ZERO DO 20 I = 1, N SMAX = MAX( SMAX, ABS( D( I ) ) ) 20 CONTINUE DO 30 I = 1, N - 1 SMAX = MAX( SMAX, ABS( E( I ) ) ) 30 CONTINUE SMINL = ZERO IF( TOL.GE.ZERO ) THEN * * Relative accuracy desired * SMINOA = ABS( D( 1 ) ) IF( SMINOA.EQ.ZERO ) $ GO TO 50 MU = SMINOA DO 40 I = 2, N MU = ABS( D( I ) )*( MU / ( MU+ABS( E( I-1 ) ) ) ) SMINOA = MIN( SMINOA, MU ) IF( SMINOA.EQ.ZERO ) $ GO TO 50 40 CONTINUE 50 CONTINUE SMINOA = SMINOA / SQRT( DBLE( N ) ) THRESH = MAX( TOL*SMINOA, MAXITR*N*N*UNFL ) ELSE * * Absolute accuracy desired * THRESH = MAX( ABS( TOL )*SMAX, MAXITR*N*N*UNFL ) END IF * * Prepare for main iteration loop for the singular values * (MAXIT is the maximum number of passes through the inner * loop permitted before nonconvergence signalled.) * MAXIT = MAXITR*N*N ITER = 0 OLDLL = -1 OLDM = -1 * * M points to last element of unconverged part of matrix * M = N * * Begin main iteration loop * 60 CONTINUE * * Check for convergence or exceeding iteration count * IF( M.LE.1 ) $ GO TO 160 IF( ITER.GT.MAXIT ) $ GO TO 200 * * Find diagonal block of matrix to work on * IF( TOL.LT.ZERO .AND. ABS( D( M ) ).LE.THRESH ) $ D( M ) = ZERO SMAX = ABS( D( M ) ) SMIN = SMAX DO 70 LLL = 1, M - 1 LL = M - LLL ABSS = ABS( D( LL ) ) ABSE = ABS( E( LL ) ) IF( TOL.LT.ZERO .AND. ABSS.LE.THRESH ) $ D( LL ) = ZERO IF( ABSE.LE.THRESH ) $ GO TO 80 SMIN = MIN( SMIN, ABSS ) SMAX = MAX( SMAX, ABSS, ABSE ) 70 CONTINUE LL = 0 GO TO 90 80 CONTINUE E( LL ) = ZERO * * Matrix splits since E(LL) = 0 * IF( LL.EQ.M-1 ) THEN * * Convergence of bottom singular value, return to top of loop * M = M - 1 GO TO 60 END IF 90 CONTINUE LL = LL + 1 * * E(LL) through E(M-1) are nonzero, E(LL-1) is zero * IF( LL.EQ.M-1 ) THEN * * 2 by 2 block, handle separately * CALL DLASV2( D( M-1 ), E( M-1 ), D( M ), SIGMN, SIGMX, SINR, $ COSR, SINL, COSL ) D( M-1 ) = SIGMX E( M-1 ) = ZERO D( M ) = SIGMN * * Compute singular vectors, if desired * IF( NCVT.GT.0 ) $ CALL DROT( NCVT, VT( M-1, 1 ), LDVT, VT( M, 1 ), LDVT, COSR, $ SINR ) IF( NRU.GT.0 ) $ CALL DROT( NRU, U( 1, M-1 ), 1, U( 1, M ), 1, COSL, SINL ) IF( NCC.GT.0 ) $ CALL DROT( NCC, C( M-1, 1 ), LDC, C( M, 1 ), LDC, COSL, $ SINL ) M = M - 2 GO TO 60 END IF * * If working on new submatrix, choose shift direction * (from larger end diagonal element towards smaller) * IF( LL.GT.OLDM .OR. M.LT.OLDLL ) THEN IF( ABS( D( LL ) ).GE.ABS( D( M ) ) ) THEN * * Chase bulge from top (big end) to bottom (small end) * IDIR = 1 ELSE * * Chase bulge from bottom (big end) to top (small end) * IDIR = 2 END IF END IF * * Apply convergence tests * IF( IDIR.EQ.1 ) THEN * * Run convergence test in forward direction * First apply standard test to bottom of matrix * IF( ABS( E( M-1 ) ).LE.ABS( TOL )*ABS( D( M ) ) .OR. $ ( TOL.LT.ZERO .AND. ABS( E( M-1 ) ).LE.THRESH ) ) THEN E( M-1 ) = ZERO GO TO 60 END IF * IF( TOL.GE.ZERO ) THEN * * If relative accuracy desired, * apply convergence criterion forward * MU = ABS( D( LL ) ) SMINL = MU DO 100 LLL = LL, M - 1 IF( ABS( E( LLL ) ).LE.TOL*MU ) THEN E( LLL ) = ZERO GO TO 60 END IF SMINLO = SMINL MU = ABS( D( LLL+1 ) )*( MU / ( MU+ABS( E( LLL ) ) ) ) SMINL = MIN( SMINL, MU ) 100 CONTINUE END IF * ELSE * * Run convergence test in backward direction * First apply standard test to top of matrix * IF( ABS( E( LL ) ).LE.ABS( TOL )*ABS( D( LL ) ) .OR. $ ( TOL.LT.ZERO .AND. ABS( E( LL ) ).LE.THRESH ) ) THEN E( LL ) = ZERO GO TO 60 END IF * IF( TOL.GE.ZERO ) THEN * * If relative accuracy desired, * apply convergence criterion backward * MU = ABS( D( M ) ) SMINL = MU DO 110 LLL = M - 1, LL, -1 IF( ABS( E( LLL ) ).LE.TOL*MU ) THEN E( LLL ) = ZERO GO TO 60 END IF SMINLO = SMINL MU = ABS( D( LLL ) )*( MU / ( MU+ABS( E( LLL ) ) ) ) SMINL = MIN( SMINL, MU ) 110 CONTINUE END IF END IF OLDLL = LL OLDM = M * * Compute shift. First, test if shifting would ruin relative * accuracy, and if so set the shift to zero. * IF( TOL.GE.ZERO .AND. N*TOL*( SMINL / SMAX ).LE. $ MAX( EPS, HNDRTH*TOL ) ) THEN * * Use a zero shift to avoid loss of relative accuracy * SHIFT = ZERO ELSE * * Compute the shift from 2-by-2 block at end of matrix * IF( IDIR.EQ.1 ) THEN SLL = ABS( D( LL ) ) CALL DLAS2( D( M-1 ), E( M-1 ), D( M ), SHIFT, R ) ELSE SLL = ABS( D( M ) ) CALL DLAS2( D( LL ), E( LL ), D( LL+1 ), SHIFT, R ) END IF * * Test if shift negligible, and if so set to zero * IF( SLL.GT.ZERO ) THEN IF( ( SHIFT / SLL )**2.LT.EPS ) $ SHIFT = ZERO END IF END IF * * Increment iteration count * ITER = ITER + M - LL * * If SHIFT = 0, do simplified QR iteration * IF( SHIFT.EQ.ZERO ) THEN IF( IDIR.EQ.1 ) THEN * * Chase bulge from top to bottom * Save cosines and sines for later singular vector updates * CS = ONE OLDCS = ONE DO 120 I = LL, M - 1 CALL DLARTG( D( I )*CS, E( I ), CS, SN, R ) IF( I.GT.LL ) $ E( I-1 ) = OLDSN*R CALL DLARTG( OLDCS*R, D( I+1 )*SN, OLDCS, OLDSN, D( I ) ) WORK( I-LL+1 ) = CS WORK( I-LL+1+NM1 ) = SN WORK( I-LL+1+NM12 ) = OLDCS WORK( I-LL+1+NM13 ) = OLDSN 120 CONTINUE H = D( M )*CS D( M ) = H*OLDCS E( M-1 ) = H*OLDSN * * Update singular vectors * IF( NCVT.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', M-LL+1, NCVT, WORK( 1 ), $ WORK( N ), VT( LL, 1 ), LDVT ) IF( NRU.GT.0 ) $ CALL DLASR( 'R', 'V', 'F', NRU, M-LL+1, WORK( NM12+1 ), $ WORK( NM13+1 ), U( 1, LL ), LDU ) IF( NCC.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', M-LL+1, NCC, WORK( NM12+1 ), $ WORK( NM13+1 ), C( LL, 1 ), LDC ) * * Test convergence * IF( ABS( E( M-1 ) ).LE.THRESH ) $ E( M-1 ) = ZERO * ELSE * * Chase bulge from bottom to top * Save cosines and sines for later singular vector updates * CS = ONE OLDCS = ONE DO 130 I = M, LL + 1, -1 CALL DLARTG( D( I )*CS, E( I-1 ), CS, SN, R ) IF( I.LT.M ) $ E( I ) = OLDSN*R CALL DLARTG( OLDCS*R, D( I-1 )*SN, OLDCS, OLDSN, D( I ) ) WORK( I-LL ) = CS WORK( I-LL+NM1 ) = -SN WORK( I-LL+NM12 ) = OLDCS WORK( I-LL+NM13 ) = -OLDSN 130 CONTINUE H = D( LL )*CS D( LL ) = H*OLDCS E( LL ) = H*OLDSN * * Update singular vectors * IF( NCVT.GT.0 ) $ CALL DLASR( 'L', 'V', 'B', M-LL+1, NCVT, WORK( NM12+1 ), $ WORK( NM13+1 ), VT( LL, 1 ), LDVT ) IF( NRU.GT.0 ) $ CALL DLASR( 'R', 'V', 'B', NRU, M-LL+1, WORK( 1 ), $ WORK( N ), U( 1, LL ), LDU ) IF( NCC.GT.0 ) $ CALL DLASR( 'L', 'V', 'B', M-LL+1, NCC, WORK( 1 ), $ WORK( N ), C( LL, 1 ), LDC ) * * Test convergence * IF( ABS( E( LL ) ).LE.THRESH ) $ E( LL ) = ZERO END IF ELSE * * Use nonzero shift * IF( IDIR.EQ.1 ) THEN * * Chase bulge from top to bottom * Save cosines and sines for later singular vector updates * F = ( ABS( D( LL ) )-SHIFT )* $ ( SIGN( ONE, D( LL ) )+SHIFT / D( LL ) ) G = E( LL ) DO 140 I = LL, M - 1 CALL DLARTG( F, G, COSR, SINR, R ) IF( I.GT.LL ) $ E( I-1 ) = R F = COSR*D( I ) + SINR*E( I ) E( I ) = COSR*E( I ) - SINR*D( I ) G = SINR*D( I+1 ) D( I+1 ) = COSR*D( I+1 ) CALL DLARTG( F, G, COSL, SINL, R ) D( I ) = R F = COSL*E( I ) + SINL*D( I+1 ) D( I+1 ) = COSL*D( I+1 ) - SINL*E( I ) IF( I.LT.M-1 ) THEN G = SINL*E( I+1 ) E( I+1 ) = COSL*E( I+1 ) END IF WORK( I-LL+1 ) = COSR WORK( I-LL+1+NM1 ) = SINR WORK( I-LL+1+NM12 ) = COSL WORK( I-LL+1+NM13 ) = SINL 140 CONTINUE E( M-1 ) = F * * Update singular vectors * IF( NCVT.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', M-LL+1, NCVT, WORK( 1 ), $ WORK( N ), VT( LL, 1 ), LDVT ) IF( NRU.GT.0 ) $ CALL DLASR( 'R', 'V', 'F', NRU, M-LL+1, WORK( NM12+1 ), $ WORK( NM13+1 ), U( 1, LL ), LDU ) IF( NCC.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', M-LL+1, NCC, WORK( NM12+1 ), $ WORK( NM13+1 ), C( LL, 1 ), LDC ) * * Test convergence * IF( ABS( E( M-1 ) ).LE.THRESH ) $ E( M-1 ) = ZERO * ELSE * * Chase bulge from bottom to top * Save cosines and sines for later singular vector updates * F = ( ABS( D( M ) )-SHIFT )*( SIGN( ONE, D( M ) )+SHIFT / $ D( M ) ) G = E( M-1 ) DO 150 I = M, LL + 1, -1 CALL DLARTG( F, G, COSR, SINR, R ) IF( I.LT.M ) $ E( I ) = R F = COSR*D( I ) + SINR*E( I-1 ) E( I-1 ) = COSR*E( I-1 ) - SINR*D( I ) G = SINR*D( I-1 ) D( I-1 ) = COSR*D( I-1 ) CALL DLARTG( F, G, COSL, SINL, R ) D( I ) = R F = COSL*E( I-1 ) + SINL*D( I-1 ) D( I-1 ) = COSL*D( I-1 ) - SINL*E( I-1 ) IF( I.GT.LL+1 ) THEN G = SINL*E( I-2 ) E( I-2 ) = COSL*E( I-2 ) END IF WORK( I-LL ) = COSR WORK( I-LL+NM1 ) = -SINR WORK( I-LL+NM12 ) = COSL WORK( I-LL+NM13 ) = -SINL 150 CONTINUE E( LL ) = F * * Test convergence * IF( ABS( E( LL ) ).LE.THRESH ) $ E( LL ) = ZERO * * Update singular vectors if desired * IF( NCVT.GT.0 ) $ CALL DLASR( 'L', 'V', 'B', M-LL+1, NCVT, WORK( NM12+1 ), $ WORK( NM13+1 ), VT( LL, 1 ), LDVT ) IF( NRU.GT.0 ) $ CALL DLASR( 'R', 'V', 'B', NRU, M-LL+1, WORK( 1 ), $ WORK( N ), U( 1, LL ), LDU ) IF( NCC.GT.0 ) $ CALL DLASR( 'L', 'V', 'B', M-LL+1, NCC, WORK( 1 ), $ WORK( N ), C( LL, 1 ), LDC ) END IF END IF * * QR iteration finished, go back and check convergence * GO TO 60 * * All singular values converged, so make them positive * 160 CONTINUE DO 170 I = 1, N IF( D( I ).LT.ZERO ) THEN D( I ) = -D( I ) * * Change sign of singular vectors, if desired * IF( NCVT.GT.0 ) $ CALL DSCAL( NCVT, NEGONE, VT( I, 1 ), LDVT ) END IF 170 CONTINUE * * Sort the singular values into decreasing order (insertion sort on * singular values, but only one transposition per singular vector) * DO 190 I = 1, N - 1 * * Scan for smallest D(I) * ISUB = 1 SMIN = D( 1 ) DO 180 J = 2, N + 1 - I IF( D( J ).LE.SMIN ) THEN ISUB = J SMIN = D( J ) END IF 180 CONTINUE IF( ISUB.NE.N+1-I ) THEN * * Swap singular values and vectors * D( ISUB ) = D( N+1-I ) D( N+1-I ) = SMIN IF( NCVT.GT.0 ) $ CALL DSWAP( NCVT, VT( ISUB, 1 ), LDVT, VT( N+1-I, 1 ), $ LDVT ) IF( NRU.GT.0 ) $ CALL DSWAP( NRU, U( 1, ISUB ), 1, U( 1, N+1-I ), 1 ) IF( NCC.GT.0 ) $ CALL DSWAP( NCC, C( ISUB, 1 ), LDC, C( N+1-I, 1 ), LDC ) END IF 190 CONTINUE GO TO 220 * * Maximum number of iterations exceeded, failure to converge * 200 CONTINUE INFO = 0 DO 210 I = 1, N - 1 IF( E( I ).NE.ZERO ) $ INFO = INFO + 1 210 CONTINUE 220 CONTINUE RETURN * * End of DBDSQR * END SUBROUTINE DGEBAK( JOB, SIDE, N, ILO, IHI, SCALE, M, V, LDV, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER JOB, SIDE INTEGER IHI, ILO, INFO, LDV, M, N * .. * .. Array Arguments .. DOUBLE PRECISION SCALE( * ), V( LDV, * ) * .. * * Purpose * ======= * * DGEBAK forms the right or left eigenvectors of a real general matrix * by backward transformation on the computed eigenvectors of the * balanced matrix output by DGEBAL. * * Arguments * ========= * * JOB (input) CHARACTER*1 * Specifies the type of backward transformation required: * = 'N', do nothing, return immediately; * = 'P', do backward transformation for permutation only; * = 'S', do backward transformation for scaling only; * = 'B', do backward transformations for both permutation and * scaling. * JOB must be the same as the argument JOB supplied to DGEBAL. * * SIDE (input) CHARACTER*1 * = 'R': V contains right eigenvectors; * = 'L': V contains left eigenvectors. * * N (input) INTEGER * The number of rows of the matrix V. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * The integers ILO and IHI determined by DGEBAL. * 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. * * SCALE (input) DOUBLE PRECISION array, dimension (N) * Details of the permutation and scaling factors, as returned * by DGEBAL. * * M (input) INTEGER * The number of columns of the matrix V. M >= 0. * * V (input/output) DOUBLE PRECISION array, dimension (LDV,M) * On entry, the matrix of right or left eigenvectors to be * transformed, as returned by DHSEIN or DTREVC. * On exit, V is overwritten by the transformed eigenvectors. * * LDV (input) INTEGER * The leading dimension of the array V. LDV >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LEFTV, RIGHTV INTEGER I, II, K DOUBLE PRECISION S * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DSCAL, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Decode and Test the input parameters * RIGHTV = LSAME( SIDE, 'R' ) LEFTV = LSAME( SIDE, 'L' ) * INFO = 0 IF( .NOT.LSAME( JOB, 'N' ) .AND. .NOT.LSAME( JOB, 'P' ) .AND. $ .NOT.LSAME( JOB, 'S' ) .AND. .NOT.LSAME( JOB, 'B' ) ) THEN INFO = -1 ELSE IF( .NOT.RIGHTV .AND. .NOT.LEFTV ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( ILO.LT.1 .OR. ILO.GT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( IHI.LT.MIN( ILO, N ) .OR. IHI.GT.N ) THEN INFO = -5 ELSE IF( M.LT.0 ) THEN INFO = -7 ELSE IF( LDV.LT.MAX( 1, N ) ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEBAK', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN IF( M.EQ.0 ) $ RETURN IF( LSAME( JOB, 'N' ) ) $ RETURN * IF( ILO.EQ.IHI ) $ GO TO 30 * * Backward balance * IF( LSAME( JOB, 'S' ) .OR. LSAME( JOB, 'B' ) ) THEN * IF( RIGHTV ) THEN DO 10 I = ILO, IHI S = SCALE( I ) CALL DSCAL( M, S, V( I, 1 ), LDV ) 10 CONTINUE END IF * IF( LEFTV ) THEN DO 20 I = ILO, IHI S = ONE / SCALE( I ) CALL DSCAL( M, S, V( I, 1 ), LDV ) 20 CONTINUE END IF * END IF * * Backward permutation * * For I = ILO-1 step -1 until 1, * IHI+1 step 1 until N do -- * 30 CONTINUE IF( LSAME( JOB, 'P' ) .OR. LSAME( JOB, 'B' ) ) THEN IF( RIGHTV ) THEN DO 40 II = 1, N I = II IF( I.GE.ILO .AND. I.LE.IHI ) $ GO TO 40 IF( I.LT.ILO ) $ I = ILO - II K = SCALE( I ) IF( K.EQ.I ) $ GO TO 40 CALL DSWAP( M, V( I, 1 ), LDV, V( K, 1 ), LDV ) 40 CONTINUE END IF * IF( LEFTV ) THEN DO 50 II = 1, N I = II IF( I.GE.ILO .AND. I.LE.IHI ) $ GO TO 50 IF( I.LT.ILO ) $ I = ILO - II K = SCALE( I ) IF( K.EQ.I ) $ GO TO 50 CALL DSWAP( M, V( I, 1 ), LDV, V( K, 1 ), LDV ) 50 CONTINUE END IF END IF * RETURN * * End of DGEBAK * END SUBROUTINE DGEBAL( JOB, N, A, LDA, ILO, IHI, SCALE, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOB INTEGER IHI, ILO, INFO, LDA, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), SCALE( * ) * .. * * Purpose * ======= * * DGEBAL balances a general real matrix A. This involves, first, * permuting A by a similarity transformation to isolate eigenvalues * in the first 1 to ILO-1 and last IHI+1 to N elements on the * diagonal; and second, applying a diagonal similarity transformation * to rows and columns ILO to IHI to make the rows and columns as * close in norm as possible. Both steps are optional. * * Balancing may reduce the 1-norm of the matrix, and improve the * accuracy of the computed eigenvalues and/or eigenvectors. * * Arguments * ========= * * JOB (input) CHARACTER*1 * Specifies the operations to be performed on A: * = 'N': none: simply set ILO = 1, IHI = N, SCALE(I) = 1.0 * for i = 1,...,N; * = 'P': permute only; * = 'S': scale only; * = 'B': both permute and scale. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the input matrix A. * On exit, A is overwritten by the balanced matrix. * If JOB = 'N', A is not referenced. * See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * ILO (output) INTEGER * IHI (output) INTEGER * ILO and IHI are set to integers such that on exit * A(i,j) = 0 if i > j and j = 1,...,ILO-1 or I = IHI+1,...,N. * If JOB = 'N' or 'S', ILO = 1 and IHI = N. * * SCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied to * A. If P(j) is the index of the row and column interchanged * with row and column j and D(j) is the scaling factor * applied to row and column j, then * SCALE(j) = P(j) for j = 1,...,ILO-1 * = D(j) for j = ILO,...,IHI * = P(j) for j = IHI+1,...,N. * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * The permutations consist of row and column interchanges which put * the matrix in the form * * ( T1 X Y ) * P A P = ( 0 B Z ) * ( 0 0 T2 ) * * where T1 and T2 are upper triangular matrices whose eigenvalues lie * along the diagonal. The column indices ILO and IHI mark the starting * and ending columns of the submatrix B. Balancing consists of applying * a diagonal similarity transformation inv(D) * B * D to make the * 1-norms of each row of B and its corresponding column nearly equal. * The output matrix is * * ( T1 X*D Y ) * ( 0 inv(D)*B*D inv(D)*Z ). * ( 0 0 T2 ) * * Information about the permutations P and the diagonal matrix D is * returned in the vector SCALE. * * This subroutine is based on the EISPACK routine BALANC. * * Modified by Tzu-Yi Chen, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) DOUBLE PRECISION SCLFAC PARAMETER ( SCLFAC = 0.8D+1 ) DOUBLE PRECISION FACTOR PARAMETER ( FACTOR = 0.95D+0 ) * .. * .. Local Scalars .. LOGICAL NOCONV INTEGER I, ICA, IEXC, IRA, J, K, L, M DOUBLE PRECISION C, CA, F, G, R, RA, S, SFMAX1, SFMAX2, SFMIN1, $ SFMIN2 * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX DOUBLE PRECISION DLAMCH EXTERNAL LSAME, IDAMAX, DLAMCH * .. * .. External Subroutines .. EXTERNAL DSCAL, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 IF( .NOT.LSAME( JOB, 'N' ) .AND. .NOT.LSAME( JOB, 'P' ) .AND. $ .NOT.LSAME( JOB, 'S' ) .AND. .NOT.LSAME( JOB, 'B' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEBAL', -INFO ) RETURN END IF * K = 1 L = N * IF( N.EQ.0 ) $ GO TO 210 * IF( LSAME( JOB, 'N' ) ) THEN DO 10 I = 1, N SCALE( I ) = ONE 10 CONTINUE GO TO 210 END IF * IF( LSAME( JOB, 'S' ) ) $ GO TO 120 * * Permutation to isolate eigenvalues if possible * GO TO 50 * * Row and column exchange. * 20 CONTINUE SCALE( M ) = J IF( J.EQ.M ) $ GO TO 30 * CALL DSWAP( L, A( 1, J ), 1, A( 1, M ), 1 ) CALL DSWAP( N-K+1, A( J, K ), LDA, A( M, K ), LDA ) * 30 CONTINUE GO TO ( 40, 80 )IEXC * * Search for rows isolating an eigenvalue and push them down. * 40 CONTINUE IF( L.EQ.1 ) $ GO TO 210 L = L - 1 * 50 CONTINUE DO 70 J = L, 1, -1 * DO 60 I = 1, L IF( I.EQ.J ) $ GO TO 60 IF( A( J, I ).NE.ZERO ) $ GO TO 70 60 CONTINUE * M = L IEXC = 1 GO TO 20 70 CONTINUE * GO TO 90 * * Search for columns isolating an eigenvalue and push them left. * 80 CONTINUE K = K + 1 * 90 CONTINUE DO 110 J = K, L * DO 100 I = K, L IF( I.EQ.J ) $ GO TO 100 IF( A( I, J ).NE.ZERO ) $ GO TO 110 100 CONTINUE * M = K IEXC = 2 GO TO 20 110 CONTINUE * 120 CONTINUE DO 130 I = K, L SCALE( I ) = ONE 130 CONTINUE * IF( LSAME( JOB, 'P' ) ) $ GO TO 210 * * Balance the submatrix in rows K to L. * * Iterative loop for norm reduction * SFMIN1 = DLAMCH( 'S' ) / DLAMCH( 'P' ) SFMAX1 = ONE / SFMIN1 SFMIN2 = SFMIN1*SCLFAC SFMAX2 = ONE / SFMIN2 140 CONTINUE NOCONV = .FALSE. * DO 200 I = K, L C = ZERO R = ZERO * DO 150 J = K, L IF( J.EQ.I ) $ GO TO 150 C = C + ABS( A( J, I ) ) R = R + ABS( A( I, J ) ) 150 CONTINUE ICA = IDAMAX( L, A( 1, I ), 1 ) CA = ABS( A( ICA, I ) ) IRA = IDAMAX( N-K+1, A( I, K ), LDA ) RA = ABS( A( I, IRA+K-1 ) ) * * Guard against zero C or R due to underflow. * IF( C.EQ.ZERO .OR. R.EQ.ZERO ) $ GO TO 200 G = R / SCLFAC F = ONE S = C + R 160 CONTINUE IF( C.GE.G .OR. MAX( F, C, CA ).GE.SFMAX2 .OR. $ MIN( R, G, RA ).LE.SFMIN2 )GO TO 170 F = F*SCLFAC C = C*SCLFAC CA = CA*SCLFAC R = R / SCLFAC G = G / SCLFAC RA = RA / SCLFAC GO TO 160 * 170 CONTINUE G = C / SCLFAC 180 CONTINUE IF( G.LT.R .OR. MAX( R, RA ).GE.SFMAX2 .OR. $ MIN( F, C, G, CA ).LE.SFMIN2 )GO TO 190 F = F / SCLFAC C = C / SCLFAC G = G / SCLFAC CA = CA / SCLFAC R = R*SCLFAC RA = RA*SCLFAC GO TO 180 * * Now balance. * 190 CONTINUE IF( ( C+R ).GE.FACTOR*S ) $ GO TO 200 IF( F.LT.ONE .AND. SCALE( I ).LT.ONE ) THEN IF( F*SCALE( I ).LE.SFMIN1 ) $ GO TO 200 END IF IF( F.GT.ONE .AND. SCALE( I ).GT.ONE ) THEN IF( SCALE( I ).GE.SFMAX1 / F ) $ GO TO 200 END IF G = ONE / F SCALE( I ) = SCALE( I )*F NOCONV = .TRUE. * CALL DSCAL( N-K+1, G, A( I, K ), LDA ) CALL DSCAL( L, F, A( 1, I ), 1 ) * 200 CONTINUE * IF( NOCONV ) $ GO TO 140 * 210 CONTINUE ILO = K IHI = L * RETURN * * End of DGEBAL * END SUBROUTINE DGEBD2( M, N, A, LDA, D, E, TAUQ, TAUP, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER INFO, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAUP( * ), $ TAUQ( * ), WORK( * ) * .. * * Purpose * ======= * * DGEBD2 reduces a real general m by n matrix A to upper or lower * bidiagonal form B by an orthogonal transformation: Q' * A * P = B. * * If m >= n, B is upper bidiagonal; if m < n, B is lower bidiagonal. * * Arguments * ========= * * M (input) INTEGER * The number of rows in the matrix A. M >= 0. * * N (input) INTEGER * The number of columns in the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the m by n general matrix to be reduced. * On exit, * if m >= n, the diagonal and the first superdiagonal are * overwritten with the upper bidiagonal matrix B; the * elements below the diagonal, with the array TAUQ, represent * the orthogonal matrix Q as a product of elementary * reflectors, and the elements above the first superdiagonal, * with the array TAUP, represent the orthogonal matrix P as * a product of elementary reflectors; * if m < n, the diagonal and the first subdiagonal are * overwritten with the lower bidiagonal matrix B; the * elements below the first subdiagonal, with the array TAUQ, * represent the orthogonal matrix Q as a product of * elementary reflectors, and the elements above the diagonal, * with the array TAUP, represent the orthogonal matrix P as * a product of elementary reflectors. * See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * D (output) DOUBLE PRECISION array, dimension (min(M,N)) * The diagonal elements of the bidiagonal matrix B: * D(i) = A(i,i). * * E (output) DOUBLE PRECISION array, dimension (min(M,N)-1) * The off-diagonal elements of the bidiagonal matrix B: * if m >= n, E(i) = A(i,i+1) for i = 1,2,...,n-1; * if m < n, E(i) = A(i+1,i) for i = 1,2,...,m-1. * * TAUQ (output) DOUBLE PRECISION array dimension (min(M,N)) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix Q. See Further Details. * * TAUP (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix P. See Further Details. * * WORK (workspace) DOUBLE PRECISION array, dimension (max(M,N)) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * The matrices Q and P are represented as products of elementary * reflectors: * * If m >= n, * * Q = H(1) H(2) . . . H(n) and P = G(1) G(2) . . . G(n-1) * * Each H(i) and G(i) has the form: * * H(i) = I - tauq * v * v' and G(i) = I - taup * u * u' * * where tauq and taup are real scalars, and v and u are real vectors; * v(1:i-1) = 0, v(i) = 1, and v(i+1:m) is stored on exit in A(i+1:m,i); * u(1:i) = 0, u(i+1) = 1, and u(i+2:n) is stored on exit in A(i,i+2:n); * tauq is stored in TAUQ(i) and taup in TAUP(i). * * If m < n, * * Q = H(1) H(2) . . . H(m-1) and P = G(1) G(2) . . . G(m) * * Each H(i) and G(i) has the form: * * H(i) = I - tauq * v * v' and G(i) = I - taup * u * u' * * where tauq and taup are real scalars, and v and u are real vectors; * v(1:i) = 0, v(i+1) = 1, and v(i+2:m) is stored on exit in A(i+2:m,i); * u(1:i-1) = 0, u(i) = 1, and u(i+1:n) is stored on exit in A(i,i+1:n); * tauq is stored in TAUQ(i) and taup in TAUP(i). * * The contents of A on exit are illustrated by the following examples: * * m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n): * * ( d e u1 u1 u1 ) ( d u1 u1 u1 u1 u1 ) * ( v1 d e u2 u2 ) ( e d u2 u2 u2 u2 ) * ( v1 v2 d e u3 ) ( v1 e d u3 u3 u3 ) * ( v1 v2 v3 d e ) ( v1 v2 e d u4 u4 ) * ( v1 v2 v3 v4 d ) ( v1 v2 v3 e d u5 ) * ( v1 v2 v3 v4 v5 ) * * where d and e denote diagonal and off-diagonal elements of B, vi * denotes an element of the vector defining H(i), and ui an element of * the vector defining G(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I * .. * .. External Subroutines .. EXTERNAL DLARF, DLARFG, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 END IF IF( INFO.LT.0 ) THEN CALL XERBLA( 'DGEBD2', -INFO ) RETURN END IF * IF( M.GE.N ) THEN * * Reduce to upper bidiagonal form * DO 10 I = 1, N * * Generate elementary reflector H(i) to annihilate A(i+1:m,i) * CALL DLARFG( M-I+1, A( I, I ), A( MIN( I+1, M ), I ), 1, $ TAUQ( I ) ) D( I ) = A( I, I ) A( I, I ) = ONE * * Apply H(i) to A(i:m,i+1:n) from the left * CALL DLARF( 'Left', M-I+1, N-I, A( I, I ), 1, TAUQ( I ), $ A( I, I+1 ), LDA, WORK ) A( I, I ) = D( I ) * IF( I.LT.N ) THEN * * Generate elementary reflector G(i) to annihilate * A(i,i+2:n) * CALL DLARFG( N-I, A( I, I+1 ), A( I, MIN( I+2, N ) ), $ LDA, TAUP( I ) ) E( I ) = A( I, I+1 ) A( I, I+1 ) = ONE * * Apply G(i) to A(i+1:m,i+1:n) from the right * CALL DLARF( 'Right', M-I, N-I, A( I, I+1 ), LDA, $ TAUP( I ), A( I+1, I+1 ), LDA, WORK ) A( I, I+1 ) = E( I ) ELSE TAUP( I ) = ZERO END IF 10 CONTINUE ELSE * * Reduce to lower bidiagonal form * DO 20 I = 1, M * * Generate elementary reflector G(i) to annihilate A(i,i+1:n) * CALL DLARFG( N-I+1, A( I, I ), A( I, MIN( I+1, N ) ), LDA, $ TAUP( I ) ) D( I ) = A( I, I ) A( I, I ) = ONE * * Apply G(i) to A(i+1:m,i:n) from the right * CALL DLARF( 'Right', M-I, N-I+1, A( I, I ), LDA, TAUP( I ), $ A( MIN( I+1, M ), I ), LDA, WORK ) A( I, I ) = D( I ) * IF( I.LT.M ) THEN * * Generate elementary reflector H(i) to annihilate * A(i+2:m,i) * CALL DLARFG( M-I, A( I+1, I ), A( MIN( I+2, M ), I ), 1, $ TAUQ( I ) ) E( I ) = A( I+1, I ) A( I+1, I ) = ONE * * Apply H(i) to A(i+1:m,i+1:n) from the left * CALL DLARF( 'Left', M-I, N-I, A( I+1, I ), 1, TAUQ( I ), $ A( I+1, I+1 ), LDA, WORK ) A( I+1, I ) = E( I ) ELSE TAUQ( I ) = ZERO END IF 20 CONTINUE END IF RETURN * * End of DGEBD2 * END SUBROUTINE DGEBRD( M, N, A, LDA, D, E, TAUQ, TAUP, WORK, LWORK, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAUP( * ), $ TAUQ( * ), WORK( * ) * .. * * Purpose * ======= * * DGEBRD reduces a general real M-by-N matrix A to upper or lower * bidiagonal form B by an orthogonal transformation: Q**T * A * P = B. * * If m >= n, B is upper bidiagonal; if m < n, B is lower bidiagonal. * * Arguments * ========= * * M (input) INTEGER * The number of rows in the matrix A. M >= 0. * * N (input) INTEGER * The number of columns in the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N general matrix to be reduced. * On exit, * if m >= n, the diagonal and the first superdiagonal are * overwritten with the upper bidiagonal matrix B; the * elements below the diagonal, with the array TAUQ, represent * the orthogonal matrix Q as a product of elementary * reflectors, and the elements above the first superdiagonal, * with the array TAUP, represent the orthogonal matrix P as * a product of elementary reflectors; * if m < n, the diagonal and the first subdiagonal are * overwritten with the lower bidiagonal matrix B; the * elements below the first subdiagonal, with the array TAUQ, * represent the orthogonal matrix Q as a product of * elementary reflectors, and the elements above the diagonal, * with the array TAUP, represent the orthogonal matrix P as * a product of elementary reflectors. * See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * D (output) DOUBLE PRECISION array, dimension (min(M,N)) * The diagonal elements of the bidiagonal matrix B: * D(i) = A(i,i). * * E (output) DOUBLE PRECISION array, dimension (min(M,N)-1) * The off-diagonal elements of the bidiagonal matrix B: * if m >= n, E(i) = A(i,i+1) for i = 1,2,...,n-1; * if m < n, E(i) = A(i+1,i) for i = 1,2,...,m-1. * * TAUQ (output) DOUBLE PRECISION array dimension (min(M,N)) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix Q. See Further Details. * * TAUP (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix P. See Further Details. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,M,N). * For optimum performance LWORK >= (M+N)*NB, where NB * is the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * The matrices Q and P are represented as products of elementary * reflectors: * * If m >= n, * * Q = H(1) H(2) . . . H(n) and P = G(1) G(2) . . . G(n-1) * * Each H(i) and G(i) has the form: * * H(i) = I - tauq * v * v' and G(i) = I - taup * u * u' * * where tauq and taup are real scalars, and v and u are real vectors; * v(1:i-1) = 0, v(i) = 1, and v(i+1:m) is stored on exit in A(i+1:m,i); * u(1:i) = 0, u(i+1) = 1, and u(i+2:n) is stored on exit in A(i,i+2:n); * tauq is stored in TAUQ(i) and taup in TAUP(i). * * If m < n, * * Q = H(1) H(2) . . . H(m-1) and P = G(1) G(2) . . . G(m) * * Each H(i) and G(i) has the form: * * H(i) = I - tauq * v * v' and G(i) = I - taup * u * u' * * where tauq and taup are real scalars, and v and u are real vectors; * v(1:i) = 0, v(i+1) = 1, and v(i+2:m) is stored on exit in A(i+2:m,i); * u(1:i-1) = 0, u(i) = 1, and u(i+1:n) is stored on exit in A(i,i+1:n); * tauq is stored in TAUQ(i) and taup in TAUP(i). * * The contents of A on exit are illustrated by the following examples: * * m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n): * * ( d e u1 u1 u1 ) ( d u1 u1 u1 u1 u1 ) * ( v1 d e u2 u2 ) ( e d u2 u2 u2 u2 ) * ( v1 v2 d e u3 ) ( v1 e d u3 u3 u3 ) * ( v1 v2 v3 d e ) ( v1 v2 e d u4 u4 ) * ( v1 v2 v3 v4 d ) ( v1 v2 v3 e d u5 ) * ( v1 v2 v3 v4 v5 ) * * where d and e denote diagonal and off-diagonal elements of B, vi * denotes an element of the vector defining H(i), and ui an element of * the vector defining G(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IINFO, J, LDWRKX, LDWRKY, LWKOPT, MINMN, NB, $ NBMIN, NX DOUBLE PRECISION WS * .. * .. External Subroutines .. EXTERNAL DGEBD2, DGEMM, DLABRD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC DBLE, MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 NB = MAX( 1, ILAENV( 1, 'DGEBRD', ' ', M, N, -1, -1 ) ) LWKOPT = ( M+N )*NB WORK( 1 ) = DBLE( LWKOPT ) LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 ELSE IF( LWORK.LT.MAX( 1, M, N ) .AND. .NOT.LQUERY ) THEN INFO = -10 END IF IF( INFO.LT.0 ) THEN CALL XERBLA( 'DGEBRD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * MINMN = MIN( M, N ) IF( MINMN.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * WS = MAX( M, N ) LDWRKX = M LDWRKY = N * IF( NB.GT.1 .AND. NB.LT.MINMN ) THEN * * Set the crossover point NX. * NX = MAX( NB, ILAENV( 3, 'DGEBRD', ' ', M, N, -1, -1 ) ) * * Determine when to switch from blocked to unblocked code. * IF( NX.LT.MINMN ) THEN WS = ( M+N )*NB IF( LWORK.LT.WS ) THEN * * Not enough work space for the optimal NB, consider using * a smaller block size. * NBMIN = ILAENV( 2, 'DGEBRD', ' ', M, N, -1, -1 ) IF( LWORK.GE.( M+N )*NBMIN ) THEN NB = LWORK / ( M+N ) ELSE NB = 1 NX = MINMN END IF END IF END IF ELSE NX = MINMN END IF * DO 30 I = 1, MINMN - NX, NB * * Reduce rows and columns i:i+nb-1 to bidiagonal form and return * the matrices X and Y which are needed to update the unreduced * part of the matrix * CALL DLABRD( M-I+1, N-I+1, NB, A( I, I ), LDA, D( I ), E( I ), $ TAUQ( I ), TAUP( I ), WORK, LDWRKX, $ WORK( LDWRKX*NB+1 ), LDWRKY ) * * Update the trailing submatrix A(i+nb:m,i+nb:n), using an update * of the form A := A - V*Y' - X*U' * CALL DGEMM( 'No transpose', 'Transpose', M-I-NB+1, N-I-NB+1, $ NB, -ONE, A( I+NB, I ), LDA, $ WORK( LDWRKX*NB+NB+1 ), LDWRKY, ONE, $ A( I+NB, I+NB ), LDA ) CALL DGEMM( 'No transpose', 'No transpose', M-I-NB+1, N-I-NB+1, $ NB, -ONE, WORK( NB+1 ), LDWRKX, A( I, I+NB ), LDA, $ ONE, A( I+NB, I+NB ), LDA ) * * Copy diagonal and off-diagonal elements of B back into A * IF( M.GE.N ) THEN DO 10 J = I, I + NB - 1 A( J, J ) = D( J ) A( J, J+1 ) = E( J ) 10 CONTINUE ELSE DO 20 J = I, I + NB - 1 A( J, J ) = D( J ) A( J+1, J ) = E( J ) 20 CONTINUE END IF 30 CONTINUE * * Use unblocked code to reduce the remainder of the matrix * CALL DGEBD2( M-I+1, N-I+1, A( I, I ), LDA, D( I ), E( I ), $ TAUQ( I ), TAUP( I ), WORK, IINFO ) WORK( 1 ) = WS RETURN * * End of DGEBRD * END SUBROUTINE DGECON( NORM, N, A, LDA, ANORM, RCOND, WORK, IWORK, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER NORM INTEGER INFO, LDA, N DOUBLE PRECISION ANORM, RCOND * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), WORK( * ) * .. * * Purpose * ======= * * DGECON estimates the reciprocal of the condition number of a general * real matrix A, in either the 1-norm or the infinity-norm, using * the LU factorization computed by DGETRF. * * An estimate is obtained for norm(inv(A)), and the reciprocal of the * condition number is computed as * RCOND = 1 / ( norm(A) * norm(inv(A)) ). * * Arguments * ========= * * NORM (input) CHARACTER*1 * Specifies whether the 1-norm condition number or the * infinity-norm condition number is required: * = '1' or 'O': 1-norm; * = 'I': Infinity-norm. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The factors L and U from the factorization A = P*L*U * as computed by DGETRF. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * ANORM (input) DOUBLE PRECISION * If NORM = '1' or 'O', the 1-norm of the original matrix A. * If NORM = 'I', the infinity-norm of the original matrix A. * * RCOND (output) DOUBLE PRECISION * The reciprocal of the condition number of the matrix A, * computed as RCOND = 1/(norm(A) * norm(inv(A))). * * WORK (workspace) DOUBLE PRECISION array, dimension (4*N) * * IWORK (workspace) INTEGER array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL ONENRM CHARACTER NORMIN INTEGER IX, KASE, KASE1 DOUBLE PRECISION AINVNM, SCALE, SL, SMLNUM, SU * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX DOUBLE PRECISION DLAMCH EXTERNAL LSAME, IDAMAX, DLAMCH * .. * .. External Subroutines .. EXTERNAL DLACON, DLATRS, DRSCL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 ONENRM = NORM.EQ.'1' .OR. LSAME( NORM, 'O' ) IF( .NOT.ONENRM .AND. .NOT.LSAME( NORM, 'I' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( ANORM.LT.ZERO ) THEN INFO = -5 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGECON', -INFO ) RETURN END IF * * Quick return if possible * RCOND = ZERO IF( N.EQ.0 ) THEN RCOND = ONE RETURN ELSE IF( ANORM.EQ.ZERO ) THEN RETURN END IF * SMLNUM = DLAMCH( 'Safe minimum' ) * * Estimate the norm of inv(A). * AINVNM = ZERO NORMIN = 'N' IF( ONENRM ) THEN KASE1 = 1 ELSE KASE1 = 2 END IF KASE = 0 10 CONTINUE CALL DLACON( N, WORK( N+1 ), WORK, IWORK, AINVNM, KASE ) IF( KASE.NE.0 ) THEN IF( KASE.EQ.KASE1 ) THEN * * Multiply by inv(L). * CALL DLATRS( 'Lower', 'No transpose', 'Unit', NORMIN, N, A, $ LDA, WORK, SL, WORK( 2*N+1 ), INFO ) * * Multiply by inv(U). * CALL DLATRS( 'Upper', 'No transpose', 'Non-unit', NORMIN, N, $ A, LDA, WORK, SU, WORK( 3*N+1 ), INFO ) ELSE * * Multiply by inv(U'). * CALL DLATRS( 'Upper', 'Transpose', 'Non-unit', NORMIN, N, A, $ LDA, WORK, SU, WORK( 3*N+1 ), INFO ) * * Multiply by inv(L'). * CALL DLATRS( 'Lower', 'Transpose', 'Unit', NORMIN, N, A, $ LDA, WORK, SL, WORK( 2*N+1 ), INFO ) END IF * * Divide X by 1/(SL*SU) if doing so will not cause overflow. * SCALE = SL*SU NORMIN = 'Y' IF( SCALE.NE.ONE ) THEN IX = IDAMAX( N, WORK, 1 ) IF( SCALE.LT.ABS( WORK( IX ) )*SMLNUM .OR. SCALE.EQ.ZERO ) $ GO TO 20 CALL DRSCL( N, SCALE, WORK, 1 ) END IF GO TO 10 END IF * * Compute the estimate of the reciprocal condition number. * IF( AINVNM.NE.ZERO ) $ RCOND = ( ONE / AINVNM ) / ANORM * 20 CONTINUE RETURN * * End of DGECON * END SUBROUTINE DGEES( JOBVS, SORT, SELECT, N, A, LDA, SDIM, WR, WI, $ VS, LDVS, WORK, LWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVS, SORT INTEGER INFO, LDA, LDVS, LWORK, N, SDIM * .. * .. Array Arguments .. LOGICAL BWORK( * ) DOUBLE PRECISION A( LDA, * ), VS( LDVS, * ), WI( * ), WORK( * ), $ WR( * ) * .. * .. Function Arguments .. LOGICAL SELECT EXTERNAL SELECT * .. * * Purpose * ======= * * DGEES computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues, the real Schur form T, and, optionally, the matrix of * Schur vectors Z. This gives the Schur factorization A = Z*T*(Z**T). * * Optionally, it also orders the eigenvalues on the diagonal of the * real Schur form so that selected eigenvalues are at the top left. * The leading columns of Z then form an orthonormal basis for the * invariant subspace corresponding to the selected eigenvalues. * * A matrix is in real Schur form if it is upper quasi-triangular with * 1-by-1 and 2-by-2 blocks. 2-by-2 blocks will be standardized in the * form * [ a b ] * [ c a ] * * where b*c < 0. The eigenvalues of such a block are a +- sqrt(bc). * * Arguments * ========= * * JOBVS (input) CHARACTER*1 * = 'N': Schur vectors are not computed; * = 'V': Schur vectors are computed. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see SELECT). * * SELECT (input) LOGICAL FUNCTION of two DOUBLE PRECISION arguments * SELECT must be declared EXTERNAL in the calling subroutine. * If SORT = 'S', SELECT is used to select eigenvalues to sort * to the top left of the Schur form. * If SORT = 'N', SELECT is not referenced. * An eigenvalue WR(j)+sqrt(-1)*WI(j) is selected if * SELECT(WR(j),WI(j)) is true; i.e., if either one of a complex * conjugate pair of eigenvalues is selected, then both complex * eigenvalues are selected. * Note that a selected complex eigenvalue may no longer * satisfy SELECT(WR(j),WI(j)) = .TRUE. after ordering, since * ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned); in this * case INFO is set to N+2 (see INFO below). * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten by its real Schur form T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which SELECT is true. (Complex conjugate * pairs for which SELECT is true for either * eigenvalue count as 2.) * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues in the same order * that they appear on the diagonal of the output Schur form T. * Complex conjugate pairs of eigenvalues will appear * consecutively with the eigenvalue having the positive * imaginary part first. * * VS (output) DOUBLE PRECISION array, dimension (LDVS,N) * If JOBVS = 'V', VS contains the orthogonal matrix Z of Schur * vectors. * If JOBVS = 'N', VS is not referenced. * * LDVS (input) INTEGER * The leading dimension of the array VS. LDVS >= 1; if * JOBVS = 'V', LDVS >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) contains the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N). * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, and i is * <= N: the QR algorithm failed to compute all the * eigenvalues; elements 1:ILO-1 and i+1:N of WR and WI * contain those eigenvalues which have converged; if * JOBVS = 'V', VS contains the matrix which reduces A * to its partially converged Schur form. * = N+1: the eigenvalues could not be reordered because some * eigenvalues were too close to separate (the problem * is very ill-conditioned); * = N+2: after reordering, roundoff changed values of some * complex eigenvalues so that leading eigenvalues in * the Schur form no longer satisfy SELECT=.TRUE. This * could also be caused by underflow due to scaling. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL CURSL, LASTSL, LQUERY, LST2SL, SCALEA, WANTST, $ WANTVS INTEGER HSWORK, I, I1, I2, IBAL, ICOND, IERR, IEVAL, $ IHI, ILO, INXT, IP, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK DOUBLE PRECISION ANRM, BIGNUM, CSCALE, EPS, S, SEP, SMLNUM * .. * .. Local Arrays .. INTEGER IDUM( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, $ DLASCL, DORGHR, DSWAP, DTRSEN, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVS = LSAME( JOBVS, 'V' ) WANTST = LSAME( SORT, 'S' ) IF( ( .NOT.WANTVS ) .AND. ( .NOT.LSAME( JOBVS, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDVS.LT.1 .OR. ( WANTVS .AND. LDVS.LT.N ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 3*N ) IF( .NOT.WANTVS ) THEN MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) ELSE MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'EN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEES ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Permute the matrix to make it more nearly triangular * (Workspace: need N) * IBAL = 1 CALL DGEBAL( 'P', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (Workspace: need 3*N, prefer 2*N+N*NB) * ITAU = N + IBAL IWRK = N + ITAU CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVS ) THEN * * Copy Householder vectors to VS * CALL DLACPY( 'L', N, N, A, LDA, VS, LDVS ) * * Generate orthogonal matrix in VS * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VS, LDVS, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) END IF * SDIM = 0 * * Perform QR iteration, accumulating Schur vectors in VS if desired * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', JOBVS, N, ILO, IHI, A, LDA, WR, WI, VS, LDVS, $ WORK( IWRK ), LWORK-IWRK+1, IEVAL ) IF( IEVAL.GT.0 ) $ INFO = IEVAL * * Sort eigenvalues if desired * IF( WANTST .AND. INFO.EQ.0 ) THEN IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WR, N, IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WI, N, IERR ) END IF DO 10 I = 1, N BWORK( I ) = SELECT( WR( I ), WI( I ) ) 10 CONTINUE * * Reorder eigenvalues and transform Schur vectors * (Workspace: none needed) * CALL DTRSEN( 'N', JOBVS, BWORK, N, A, LDA, VS, LDVS, WR, WI, $ SDIM, S, SEP, WORK( IWRK ), LWORK-IWRK+1, IDUM, 1, $ ICOND ) IF( ICOND.GT.0 ) $ INFO = N + ICOND END IF * IF( WANTVS ) THEN * * Undo balancing * (Workspace: need N) * CALL DGEBAK( 'P', 'R', N, ILO, IHI, WORK( IBAL ), N, VS, LDVS, $ IERR ) END IF * IF( SCALEA ) THEN * * Undo scaling for the Schur form of A * CALL DLASCL( 'H', 0, 0, CSCALE, ANRM, N, N, A, LDA, IERR ) CALL DCOPY( N, A, LDA+1, WR, 1 ) IF( CSCALE.EQ.SMLNUM ) THEN * * If scaling back towards underflow, adjust WI if an * offdiagonal element of a 2-by-2 block in the Schur form * underflows. * IF( IEVAL.GT.0 ) THEN I1 = IEVAL + 1 I2 = IHI - 1 CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, $ MAX( ILO-1, 1 ), IERR ) ELSE IF( WANTST ) THEN I1 = 1 I2 = N - 1 ELSE I1 = ILO I2 = IHI - 1 END IF INXT = I1 - 1 DO 20 I = I1, I2 IF( I.LT.INXT ) $ GO TO 20 IF( WI( I ).EQ.ZERO ) THEN INXT = I + 1 ELSE IF( A( I+1, I ).EQ.ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO ELSE IF( A( I+1, I ).NE.ZERO .AND. A( I, I+1 ).EQ. $ ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO IF( I.GT.1 ) $ CALL DSWAP( I-1, A( 1, I ), 1, A( 1, I+1 ), 1 ) IF( N.GT.I+1 ) $ CALL DSWAP( N-I-1, A( I, I+2 ), LDA, $ A( I+1, I+2 ), LDA ) CALL DSWAP( N, VS( 1, I ), 1, VS( 1, I+1 ), 1 ) A( I, I+1 ) = A( I+1, I ) A( I+1, I ) = ZERO END IF INXT = I + 2 END IF 20 CONTINUE END IF * * Undo scaling for the imaginary part of the eigenvalues * CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-IEVAL, 1, $ WI( IEVAL+1 ), MAX( N-IEVAL, 1 ), IERR ) END IF * IF( WANTST .AND. INFO.EQ.0 ) THEN * * Check if reordering successful * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 30 I = 1, N CURSL = SELECT( WR( I ), WI( I ) ) IF( WI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 30 CONTINUE END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEES * END SUBROUTINE DGEESX( JOBVS, SORT, SELECT, SENSE, N, A, LDA, SDIM, $ WR, WI, VS, LDVS, RCONDE, RCONDV, WORK, LWORK, $ IWORK, LIWORK, BWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVS, SENSE, SORT INTEGER INFO, LDA, LDVS, LIWORK, LWORK, N, SDIM DOUBLE PRECISION RCONDE, RCONDV * .. * .. Array Arguments .. LOGICAL BWORK( * ) INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), VS( LDVS, * ), WI( * ), WORK( * ), $ WR( * ) * .. * .. Function Arguments .. LOGICAL SELECT EXTERNAL SELECT * .. * * Purpose * ======= * * DGEESX computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues, the real Schur form T, and, optionally, the matrix of * Schur vectors Z. This gives the Schur factorization A = Z*T*(Z**T). * * Optionally, it also orders the eigenvalues on the diagonal of the * real Schur form so that selected eigenvalues are at the top left; * computes a reciprocal condition number for the average of the * selected eigenvalues (RCONDE); and computes a reciprocal condition * number for the right invariant subspace corresponding to the * selected eigenvalues (RCONDV). The leading columns of Z form an * orthonormal basis for this invariant subspace. * * For further explanation of the reciprocal condition numbers RCONDE * and RCONDV, see Section 4.10 of the LAPACK Users' Guide (where * these quantities are called s and sep respectively). * * A real matrix is in real Schur form if it is upper quasi-triangular * with 1-by-1 and 2-by-2 blocks. 2-by-2 blocks will be standardized in * the form * [ a b ] * [ c a ] * * where b*c < 0. The eigenvalues of such a block are a +- sqrt(bc). * * Arguments * ========= * * JOBVS (input) CHARACTER*1 * = 'N': Schur vectors are not computed; * = 'V': Schur vectors are computed. * * SORT (input) CHARACTER*1 * Specifies whether or not to order the eigenvalues on the * diagonal of the Schur form. * = 'N': Eigenvalues are not ordered; * = 'S': Eigenvalues are ordered (see SELECT). * * SELECT (input) LOGICAL FUNCTION of two DOUBLE PRECISION arguments * SELECT must be declared EXTERNAL in the calling subroutine. * If SORT = 'S', SELECT is used to select eigenvalues to sort * to the top left of the Schur form. * If SORT = 'N', SELECT is not referenced. * An eigenvalue WR(j)+sqrt(-1)*WI(j) is selected if * SELECT(WR(j),WI(j)) is true; i.e., if either one of a * complex conjugate pair of eigenvalues is selected, then both * are. Note that a selected complex eigenvalue may no longer * satisfy SELECT(WR(j),WI(j)) = .TRUE. after ordering, since * ordering may change the value of complex eigenvalues * (especially if the eigenvalue is ill-conditioned); in this * case INFO may be set to N+3 (see INFO below). * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': None are computed; * = 'E': Computed for average of selected eigenvalues only; * = 'V': Computed for selected right invariant subspace only; * = 'B': Computed for both. * If SENSE = 'E', 'V' or 'B', SORT must equal 'S'. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the N-by-N matrix A. * On exit, A is overwritten by its real Schur form T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * SDIM (output) INTEGER * If SORT = 'N', SDIM = 0. * If SORT = 'S', SDIM = number of eigenvalues (after sorting) * for which SELECT is true. (Complex conjugate * pairs for which SELECT is true for either * eigenvalue count as 2.) * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, respectively, * of the computed eigenvalues, in the same order that they * appear on the diagonal of the output Schur form T. Complex * conjugate pairs of eigenvalues appear consecutively with the * eigenvalue having the positive imaginary part first. * * VS (output) DOUBLE PRECISION array, dimension (LDVS,N) * If JOBVS = 'V', VS contains the orthogonal matrix Z of Schur * vectors. * If JOBVS = 'N', VS is not referenced. * * LDVS (input) INTEGER * The leading dimension of the array VS. LDVS >= 1, and if * JOBVS = 'V', LDVS >= N. * * RCONDE (output) DOUBLE PRECISION * If SENSE = 'E' or 'B', RCONDE contains the reciprocal * condition number for the average of the selected eigenvalues. * Not referenced if SENSE = 'N' or 'V'. * * RCONDV (output) DOUBLE PRECISION * If SENSE = 'V' or 'B', RCONDV contains the reciprocal * condition number for the selected right invariant subspace. * Not referenced if SENSE = 'N' or 'E'. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N). * Also, if SENSE = 'E' or 'V' or 'B', * LWORK >= N+2*SDIM*(N-SDIM), where SDIM is the number of * selected eigenvalues computed by this routine. Note that * N+2*SDIM*(N-SDIM) <= N+N*N/2. * For good performance, LWORK must generally be larger. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * Not referenced if SENSE = 'N' or 'E'. * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * LIWORK >= 1; if SENSE = 'V' or 'B', LIWORK >= SDIM*(N-SDIM). * * BWORK (workspace) LOGICAL array, dimension (N) * Not referenced if SORT = 'N'. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, and i is * <= N: the QR algorithm failed to compute all the * eigenvalues; elements 1:ILO-1 and i+1:N of WR and WI * contain those eigenvalues which have converged; if * JOBVS = 'V', VS contains the transformation which * reduces A to its partially converged Schur form. * = N+1: the eigenvalues could not be reordered because some * eigenvalues were too close to separate (the problem * is very ill-conditioned); * = N+2: after reordering, roundoff changed values of some * complex eigenvalues so that leading eigenvalues in * the Schur form no longer satisfy SELECT=.TRUE. This * could also be caused by underflow due to scaling. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL CURSL, LASTSL, LST2SL, SCALEA, WANTSB, WANTSE, $ WANTSN, WANTST, WANTSV, WANTVS INTEGER HSWORK, I, I1, I2, IBAL, ICOND, IERR, IEVAL, $ IHI, ILO, INXT, IP, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK DOUBLE PRECISION ANRM, BIGNUM, CSCALE, EPS, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, $ DLASCL, DORGHR, DSWAP, DTRSEN, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 WANTVS = LSAME( JOBVS, 'V' ) WANTST = LSAME( SORT, 'S' ) WANTSN = LSAME( SENSE, 'N' ) WANTSE = LSAME( SENSE, 'E' ) WANTSV = LSAME( SENSE, 'V' ) WANTSB = LSAME( SENSE, 'B' ) IF( ( .NOT.WANTVS ) .AND. ( .NOT.LSAME( JOBVS, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTST ) .AND. ( .NOT.LSAME( SORT, 'N' ) ) ) THEN INFO = -2 ELSE IF( .NOT.( WANTSN .OR. WANTSE .OR. WANTSV .OR. WANTSB ) .OR. $ ( .NOT.WANTST .AND. .NOT.WANTSN ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVS.LT.1 .OR. ( WANTVS .AND. LDVS.LT.N ) ) THEN INFO = -12 END IF * * Compute workspace * (Note: Comments in the code beginning "RWorkspace:" describe the * minimal amount of real workspace needed at that point in the * code, as well as the preferred amount for good performance. * IWorkspace refers to integer workspace. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case. * If SENSE = 'E', 'V' or 'B', then the amount of workspace needed * depends on SDIM, which is computed by the routine DTRSEN later * in the code.) * MINWRK = 1 IF( INFO.EQ.0 .AND. LWORK.GE.1 ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) MINWRK = MAX( 1, 3*N ) IF( .NOT.WANTVS ) THEN MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) ELSE MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SV', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SV', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+HSWORK, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK ) THEN INFO = -16 END IF IF( LIWORK.LT.1 ) THEN INFO = -18 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEESX', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN SDIM = 0 RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Permute the matrix to make it more nearly triangular * (RWorkspace: need N) * IBAL = 1 CALL DGEBAL( 'P', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (RWorkspace: need 3*N, prefer 2*N+N*NB) * ITAU = N + IBAL IWRK = N + ITAU CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVS ) THEN * * Copy Householder vectors to VS * CALL DLACPY( 'L', N, N, A, LDA, VS, LDVS ) * * Generate orthogonal matrix in VS * (RWorkspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VS, LDVS, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) END IF * SDIM = 0 * * Perform QR iteration, accumulating Schur vectors in VS if desired * (RWorkspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', JOBVS, N, ILO, IHI, A, LDA, WR, WI, VS, LDVS, $ WORK( IWRK ), LWORK-IWRK+1, IEVAL ) IF( IEVAL.GT.0 ) $ INFO = IEVAL * * Sort eigenvalues if desired * IF( WANTST .AND. INFO.EQ.0 ) THEN IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WR, N, IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, WI, N, IERR ) END IF DO 10 I = 1, N BWORK( I ) = SELECT( WR( I ), WI( I ) ) 10 CONTINUE * * Reorder eigenvalues, transform Schur vectors, and compute * reciprocal condition numbers * (RWorkspace: if SENSE is not 'N', need N+2*SDIM*(N-SDIM) * otherwise, need N ) * (IWorkspace: if SENSE is 'V' or 'B', need SDIM*(N-SDIM) * otherwise, need 0 ) * CALL DTRSEN( SENSE, JOBVS, BWORK, N, A, LDA, VS, LDVS, WR, WI, $ SDIM, RCONDE, RCONDV, WORK( IWRK ), LWORK-IWRK+1, $ IWORK, LIWORK, ICOND ) IF( .NOT.WANTSN ) $ MAXWRK = MAX( MAXWRK, N+2*SDIM*( N-SDIM ) ) IF( ICOND.EQ.-15 ) THEN * * Not enough real workspace * INFO = -16 ELSE IF( ICOND.EQ.-17 ) THEN * * Not enough integer workspace * INFO = -18 ELSE IF( ICOND.GT.0 ) THEN * * DTRSEN failed to reorder or to restore standard Schur form * INFO = ICOND + N END IF END IF * IF( WANTVS ) THEN * * Undo balancing * (RWorkspace: need N) * CALL DGEBAK( 'P', 'R', N, ILO, IHI, WORK( IBAL ), N, VS, LDVS, $ IERR ) END IF * IF( SCALEA ) THEN * * Undo scaling for the Schur form of A * CALL DLASCL( 'H', 0, 0, CSCALE, ANRM, N, N, A, LDA, IERR ) CALL DCOPY( N, A, LDA+1, WR, 1 ) IF( ( WANTSV .OR. WANTSB ) .AND. INFO.EQ.0 ) THEN DUM( 1 ) = RCONDV CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, 1, 1, DUM, 1, IERR ) RCONDV = DUM( 1 ) END IF IF( CSCALE.EQ.SMLNUM ) THEN * * If scaling back towards underflow, adjust WI if an * offdiagonal element of a 2-by-2 block in the Schur form * underflows. * IF( IEVAL.GT.0 ) THEN I1 = IEVAL + 1 I2 = IHI - 1 CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) ELSE IF( WANTST ) THEN I1 = 1 I2 = N - 1 ELSE I1 = ILO I2 = IHI - 1 END IF INXT = I1 - 1 DO 20 I = I1, I2 IF( I.LT.INXT ) $ GO TO 20 IF( WI( I ).EQ.ZERO ) THEN INXT = I + 1 ELSE IF( A( I+1, I ).EQ.ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO ELSE IF( A( I+1, I ).NE.ZERO .AND. A( I, I+1 ).EQ. $ ZERO ) THEN WI( I ) = ZERO WI( I+1 ) = ZERO IF( I.GT.1 ) $ CALL DSWAP( I-1, A( 1, I ), 1, A( 1, I+1 ), 1 ) IF( N.GT.I+1 ) $ CALL DSWAP( N-I-1, A( I, I+2 ), LDA, $ A( I+1, I+2 ), LDA ) CALL DSWAP( N, VS( 1, I ), 1, VS( 1, I+1 ), 1 ) A( I, I+1 ) = A( I+1, I ) A( I+1, I ) = ZERO END IF INXT = I + 2 END IF 20 CONTINUE END IF CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-IEVAL, 1, $ WI( IEVAL+1 ), MAX( N-IEVAL, 1 ), IERR ) END IF * IF( WANTST .AND. INFO.EQ.0 ) THEN * * Check if reordering successful * LASTSL = .TRUE. LST2SL = .TRUE. SDIM = 0 IP = 0 DO 30 I = 1, N CURSL = SELECT( WR( I ), WI( I ) ) IF( WI( I ).EQ.ZERO ) THEN IF( CURSL ) $ SDIM = SDIM + 1 IP = 0 IF( CURSL .AND. .NOT.LASTSL ) $ INFO = N + 2 ELSE IF( IP.EQ.1 ) THEN * * Last eigenvalue of conjugate pair * CURSL = CURSL .OR. LASTSL LASTSL = CURSL IF( CURSL ) $ SDIM = SDIM + 2 IP = -1 IF( CURSL .AND. .NOT.LST2SL ) $ INFO = N + 2 ELSE * * First eigenvalue of conjugate pair * IP = 1 END IF END IF LST2SL = LASTSL LASTSL = CURSL 30 CONTINUE END IF * WORK( 1 ) = MAXWRK IF( WANTSV .OR. WANTSB ) THEN IWORK( 1 ) = SDIM*( N-SDIM ) ELSE IWORK( 1 ) = 1 END IF * RETURN * * End of DGEESX * END SUBROUTINE DGEEV( JOBVL, JOBVR, N, A, LDA, WR, WI, VL, LDVL, VR, $ LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBVL, JOBVR INTEGER INFO, LDA, LDVL, LDVR, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) * .. * * Purpose * ======= * * DGEEV computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues and, optionally, the left and/or right eigenvectors. * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * Arguments * ========= * * JOBVL (input) CHARACTER*1 * = 'N': left eigenvectors of A are not computed; * = 'V': left eigenvectors of A are computed. * * JOBVR (input) CHARACTER*1 * = 'N': right eigenvectors of A are not computed; * = 'V': right eigenvectors of A are computed. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues. Complex * conjugate pairs of eigenvalues appear consecutively * with the eigenvalue having the positive imaginary part * first. * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order * as their eigenvalues. * If JOBVL = 'N', VL is not referenced. * If the j-th eigenvalue is real, then u(j) = VL(:,j), * the j-th column of VL. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and * u(j+1) = VL(:,j) - i*VL(:,j+1). * * LDVL (input) INTEGER * The leading dimension of the array VL. LDVL >= 1; if * JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order * as their eigenvalues. * If JOBVR = 'N', VR is not referenced. * If the j-th eigenvalue is real, then v(j) = VR(:,j), * the j-th column of VR. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and * v(j+1) = VR(:,j) - i*VR(:,j+1). * * LDVR (input) INTEGER * The leading dimension of the array VR. LDVR >= 1; if * JOBVR = 'V', LDVR >= N. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,3*N), and * if JOBVL = 'V' or JOBVR = 'V', LWORK >= 4*N. For good * performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the QR algorithm failed to compute all the * eigenvalues, and no eigenvectors have been computed; * elements i+1:N of WR and WI contain eigenvalues which * have converged. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, SCALEA, WANTVL, WANTVR CHARACTER SIDE INTEGER HSWORK, I, IBAL, IERR, IHI, ILO, ITAU, IWRK, K, $ MAXB, MAXWRK, MINWRK, NOUT DOUBLE PRECISION ANRM, BIGNUM, CS, CSCALE, EPS, R, SCL, SMLNUM, $ SN * .. * .. Local Arrays .. LOGICAL SELECT( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, DLARTG, $ DLASCL, DORGHR, DROT, DSCAL, DTREVC, XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX, ILAENV DOUBLE PRECISION DLAMCH, DLANGE, DLAPY2, DNRM2 EXTERNAL LSAME, IDAMAX, ILAENV, DLAMCH, DLANGE, DLAPY2, $ DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVL = LSAME( JOBVL, 'V' ) WANTVR = LSAME( JOBVR, 'V' ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.LSAME( JOBVL, 'N' ) ) ) THEN INFO = -1 ELSE IF( ( .NOT.WANTVR ) .AND. ( .NOT.LSAME( JOBVR, 'N' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LDVL.LT.1 .OR. ( WANTVL .AND. LDVL.LT.N ) ) THEN INFO = -9 ELSE IF( LDVR.LT.1 .OR. ( WANTVR .AND. LDVR.LT.N ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 ) THEN c IF( INFO.EQ.0 .AND. LWORK.GE.1 ) THEN MAXWRK = 2*N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.WANTVR ) ) THEN MINWRK = MAX( 1, 3*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'EN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+1, N+HSWORK ) ELSE MINWRK = MAX( 1, 4*N ) MAXWRK = MAX( MAXWRK, 2*N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SV', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SV', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, N+1, N+HSWORK ) MAXWRK = MAX( MAXWRK, 4*N ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEEV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Balance the matrix * (Workspace: need N) * IBAL = 1 CALL DGEBAL( 'B', N, A, LDA, ILO, IHI, WORK( IBAL ), IERR ) * * Reduce to upper Hessenberg form * (Workspace: need 3*N, prefer 2*N+N*NB) * ITAU = IBAL + N IWRK = ITAU + N CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVL ) THEN * * Want left eigenvectors * Copy Householder vectors to VL * SIDE = 'L' CALL DLACPY( 'L', N, N, A, LDA, VL, LDVL ) * * Generate orthogonal matrix in VL * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VL, LDVL, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VL * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VL, LDVL, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * IF( WANTVR ) THEN * * Want left and right eigenvectors * Copy Schur vectors to VR * SIDE = 'B' CALL DLACPY( 'F', N, N, VL, LDVL, VR, LDVR ) END IF * ELSE IF( WANTVR ) THEN * * Want right eigenvectors * Copy Householder vectors to VR * SIDE = 'R' CALL DLACPY( 'L', N, N, A, LDA, VR, LDVR ) * * Generate orthogonal matrix in VR * (Workspace: need 3*N-1, prefer 2*N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VR, LDVR, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VR * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * ELSE * * Compute eigenvalues only * (Workspace: need N+1, prefer N+HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'E', 'N', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) END IF * * If INFO > 0 from DHSEQR, then quit * IF( INFO.GT.0 ) $ GO TO 50 * IF( WANTVL .OR. WANTVR ) THEN * * Compute left and/or right eigenvectors * (Workspace: need 4*N) * CALL DTREVC( SIDE, 'B', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ N, NOUT, WORK( IWRK ), IERR ) END IF * IF( WANTVL ) THEN * * Undo balancing of left eigenvectors * (Workspace: need N) * CALL DGEBAK( 'B', 'L', N, ILO, IHI, WORK( IBAL ), N, VL, LDVL, $ IERR ) * * Normalize left eigenvectors and make largest component real * DO 20 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VL( 1, I ), 1 ), $ DNRM2( N, VL( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I+1 ), 1 ) DO 10 K = 1, N WORK( IWRK+K-1 ) = VL( K, I )**2 + VL( K, I+1 )**2 10 CONTINUE K = IDAMAX( N, WORK( IWRK ), 1 ) CALL DLARTG( VL( K, I ), VL( K, I+1 ), CS, SN, R ) CALL DROT( N, VL( 1, I ), 1, VL( 1, I+1 ), 1, CS, SN ) VL( K, I+1 ) = ZERO END IF 20 CONTINUE END IF * IF( WANTVR ) THEN * * Undo balancing of right eigenvectors * (Workspace: need N) * CALL DGEBAK( 'B', 'R', N, ILO, IHI, WORK( IBAL ), N, VR, LDVR, $ IERR ) * * Normalize right eigenvectors and make largest component real * DO 40 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VR( 1, I ), 1 ), $ DNRM2( N, VR( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I+1 ), 1 ) DO 30 K = 1, N WORK( IWRK+K-1 ) = VR( K, I )**2 + VR( K, I+1 )**2 30 CONTINUE K = IDAMAX( N, WORK( IWRK ), 1 ) CALL DLARTG( VR( K, I ), VR( K, I+1 ), CS, SN, R ) CALL DROT( N, VR( 1, I ), 1, VR( 1, I+1 ), 1, CS, SN ) VR( K, I+1 ) = ZERO END IF 40 CONTINUE END IF * * Undo scaling if necessary * 50 CONTINUE IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WR( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WI( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) IF( INFO.GT.0 ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) END IF END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEEV * END SUBROUTINE DGEEVX( BALANC, JOBVL, JOBVR, SENSE, N, A, LDA, WR, WI, $ VL, LDVL, VR, LDVR, ILO, IHI, SCALE, ABNRM, $ RCONDE, RCONDV, WORK, LWORK, IWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER BALANC, JOBVL, JOBVR, SENSE INTEGER IHI, ILO, INFO, LDA, LDVL, LDVR, LWORK, N DOUBLE PRECISION ABNRM * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), RCONDE( * ), RCONDV( * ), $ SCALE( * ), VL( LDVL, * ), VR( LDVR, * ), $ WI( * ), WORK( * ), WR( * ) * .. * * Purpose * ======= * * DGEEVX computes for an N-by-N real nonsymmetric matrix A, the * eigenvalues and, optionally, the left and/or right eigenvectors. * * Optionally also, it computes a balancing transformation to improve * the conditioning of the eigenvalues and eigenvectors (ILO, IHI, * SCALE, and ABNRM), reciprocal condition numbers for the eigenvalues * (RCONDE), and reciprocal condition numbers for the right * eigenvectors (RCONDV). * * The right eigenvector v(j) of A satisfies * A * v(j) = lambda(j) * v(j) * where lambda(j) is its eigenvalue. * The left eigenvector u(j) of A satisfies * u(j)**H * A = lambda(j) * u(j)**H * where u(j)**H denotes the conjugate transpose of u(j). * * The computed eigenvectors are normalized to have Euclidean norm * equal to 1 and largest component real. * * Balancing a matrix means permuting the rows and columns to make it * more nearly upper triangular, and applying a diagonal similarity * transformation D * A * D**(-1), where D is a diagonal matrix, to * make its rows and columns closer in norm and the condition numbers * of its eigenvalues and eigenvectors smaller. The computed * reciprocal condition numbers correspond to the balanced matrix. * Permuting rows and columns will not change the condition numbers * (in exact arithmetic) but diagonal scaling will. For further * explanation of balancing, see section 4.10.2 of the LAPACK * Users' Guide. * * Arguments * ========= * * BALANC (input) CHARACTER*1 * Indicates how the input matrix should be diagonally scaled * and/or permuted to improve the conditioning of its * eigenvalues. * = 'N': Do not diagonally scale or permute; * = 'P': Perform permutations to make the matrix more nearly * upper triangular. Do not diagonally scale; * = 'S': Diagonally scale the matrix, i.e. replace A by * D*A*D**(-1), where D is a diagonal matrix chosen * to make the rows and columns of A more equal in * norm. Do not permute; * = 'B': Both diagonally scale and permute A. * * Computed reciprocal condition numbers will be for the matrix * after balancing and/or permuting. Permuting does not change * condition numbers (in exact arithmetic), but balancing does. * * JOBVL (input) CHARACTER*1 * = 'N': left eigenvectors of A are not computed; * = 'V': left eigenvectors of A are computed. * If SENSE = 'E' or 'B', JOBVL must = 'V'. * * JOBVR (input) CHARACTER*1 * = 'N': right eigenvectors of A are not computed; * = 'V': right eigenvectors of A are computed. * If SENSE = 'E' or 'B', JOBVR must = 'V'. * * SENSE (input) CHARACTER*1 * Determines which reciprocal condition numbers are computed. * = 'N': None are computed; * = 'E': Computed for eigenvalues only; * = 'V': Computed for right eigenvectors only; * = 'B': Computed for eigenvalues and right eigenvectors. * * If SENSE = 'E' or 'B', both left and right eigenvectors * must also be computed (JOBVL = 'V' and JOBVR = 'V'). * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N matrix A. * On exit, A has been overwritten. If JOBVL = 'V' or * JOBVR = 'V', A contains the real Schur form of the balanced * version of the input matrix A. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * WR and WI contain the real and imaginary parts, * respectively, of the computed eigenvalues. Complex * conjugate pairs of eigenvalues will appear consecutively * with the eigenvalue having the positive imaginary part * first. * * VL (output) DOUBLE PRECISION array, dimension (LDVL,N) * If JOBVL = 'V', the left eigenvectors u(j) are stored one * after another in the columns of VL, in the same order * as their eigenvalues. * If JOBVL = 'N', VL is not referenced. * If the j-th eigenvalue is real, then u(j) = VL(:,j), * the j-th column of VL. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and * u(j+1) = VL(:,j) - i*VL(:,j+1). * * LDVL (input) INTEGER * The leading dimension of the array VL. LDVL >= 1; if * JOBVL = 'V', LDVL >= N. * * VR (output) DOUBLE PRECISION array, dimension (LDVR,N) * If JOBVR = 'V', the right eigenvectors v(j) are stored one * after another in the columns of VR, in the same order * as their eigenvalues. * If JOBVR = 'N', VR is not referenced. * If the j-th eigenvalue is real, then v(j) = VR(:,j), * the j-th column of VR. * If the j-th and (j+1)-st eigenvalues form a complex * conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and * v(j+1) = VR(:,j) - i*VR(:,j+1). * * LDVR (input) INTEGER * The leading dimension of the array VR. LDVR >= 1, and if * JOBVR = 'V', LDVR >= N. * * ILO,IHI (output) INTEGER * ILO and IHI are integer values determined when A was * balanced. The balanced A(i,j) = 0 if I > J and * J = 1,...,ILO-1 or I = IHI+1,...,N. * * SCALE (output) DOUBLE PRECISION array, dimension (N) * Details of the permutations and scaling factors applied * when balancing A. If P(j) is the index of the row and column * interchanged with row and column j, and D(j) is the scaling * factor applied to row and column j, then * SCALE(J) = P(J), for J = 1,...,ILO-1 * = D(J), for J = ILO,...,IHI * = P(J) for J = IHI+1,...,N. * The order in which the interchanges are made is N to IHI+1, * then 1 to ILO-1. * * ABNRM (output) DOUBLE PRECISION * The one-norm of the balanced matrix (the maximum * of the sum of absolute values of elements of any column). * * RCONDE (output) DOUBLE PRECISION array, dimension (N) * RCONDE(j) is the reciprocal condition number of the j-th * eigenvalue. * * RCONDV (output) DOUBLE PRECISION array, dimension (N) * RCONDV(j) is the reciprocal condition number of the j-th * right eigenvector. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. If SENSE = 'N' or 'E', * LWORK >= max(1,2*N), and if JOBVL = 'V' or JOBVR = 'V', * LWORK >= 3*N. If SENSE = 'V' or 'B', LWORK >= N*(N+6). * For good performance, LWORK must generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (2*N-2) * If SENSE = 'N' or 'E', not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = i, the QR algorithm failed to compute all the * eigenvalues, and no eigenvectors or condition numbers * have been computed; elements 1:ILO-1 and i+1:N of WR * and WI contain eigenvalues which have converged. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, SCALEA, WANTVL, WANTVR, WNTSNB, WNTSNE, $ WNTSNN, WNTSNV CHARACTER JOB, SIDE INTEGER HSWORK, I, ICOND, IERR, ITAU, IWRK, K, MAXB, $ MAXWRK, MINWRK, NOUT DOUBLE PRECISION ANRM, BIGNUM, CS, CSCALE, EPS, R, SCL, SMLNUM, $ SN * .. * .. Local Arrays .. LOGICAL SELECT( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DGEBAK, DGEBAL, DGEHRD, DHSEQR, DLACPY, DLARTG, $ DLASCL, DORGHR, DROT, DSCAL, DTREVC, DTRSNA, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX, ILAENV DOUBLE PRECISION DLAMCH, DLANGE, DLAPY2, DNRM2 EXTERNAL LSAME, IDAMAX, ILAENV, DLAMCH, DLANGE, DLAPY2, $ DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) WANTVL = LSAME( JOBVL, 'V' ) WANTVR = LSAME( JOBVR, 'V' ) WNTSNN = LSAME( SENSE, 'N' ) WNTSNE = LSAME( SENSE, 'E' ) WNTSNV = LSAME( SENSE, 'V' ) WNTSNB = LSAME( SENSE, 'B' ) IF( .NOT.( LSAME( BALANC, 'N' ) .OR. LSAME( BALANC, $ 'S' ) .OR. LSAME( BALANC, 'P' ) .OR. LSAME( BALANC, 'B' ) ) ) $ THEN INFO = -1 ELSE IF( ( .NOT.WANTVL ) .AND. ( .NOT.LSAME( JOBVL, 'N' ) ) ) THEN INFO = -2 ELSE IF( ( .NOT.WANTVR ) .AND. ( .NOT.LSAME( JOBVR, 'N' ) ) ) THEN INFO = -3 ELSE IF( .NOT.( WNTSNN .OR. WNTSNE .OR. WNTSNB .OR. WNTSNV ) .OR. $ ( ( WNTSNE .OR. WNTSNB ) .AND. .NOT.( WANTVL .AND. $ WANTVR ) ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDVL.LT.1 .OR. ( WANTVL .AND. LDVL.LT.N ) ) THEN INFO = -11 ELSE IF( LDVR.LT.1 .OR. ( WANTVR .AND. LDVR.LT.N ) ) THEN INFO = -13 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV. * HSWORK refers to the workspace preferred by DHSEQR, as * calculated below. HSWORK is computed assuming ILO=1 and IHI=N, * the worst case.) * MINWRK = 1 IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) ) THEN MAXWRK = N + N*ILAENV( 1, 'DGEHRD', ' ', N, 1, N, 0 ) IF( ( .NOT.WANTVL ) .AND. ( .NOT.WANTVR ) ) THEN MINWRK = MAX( 1, 2*N ) IF( .NOT.WNTSNN ) $ MINWRK = MAX( MINWRK, N*N+6*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) IF( WNTSNN ) THEN K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, $ 1, N, -1 ) ) ) ELSE K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'SN', N, $ 1, N, -1 ) ) ) END IF HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, 1, HSWORK ) IF( .NOT.WNTSNN ) $ MAXWRK = MAX( MAXWRK, N*N+6*N ) ELSE MINWRK = MAX( 1, 3*N ) IF( ( .NOT.WNTSNN ) .AND. ( .NOT.WNTSNE ) ) $ MINWRK = MAX( MINWRK, N*N+6*N ) MAXB = MAX( ILAENV( 8, 'DHSEQR', 'SN', N, 1, N, -1 ), 2 ) K = MIN( MAXB, N, MAX( 2, ILAENV( 4, 'DHSEQR', 'EN', N, 1, $ N, -1 ) ) ) HSWORK = MAX( K*( K+2 ), 2*N ) MAXWRK = MAX( MAXWRK, 1, HSWORK ) MAXWRK = MAX( MAXWRK, N+( N-1 )* $ ILAENV( 1, 'DORGHR', ' ', N, 1, N, -1 ) ) IF( ( .NOT.WNTSNN ) .AND. ( .NOT.WNTSNE ) ) $ MAXWRK = MAX( MAXWRK, N*N+6*N ) MAXWRK = MAX( MAXWRK, 3*N, 1 ) END IF WORK( 1 ) = MAXWRK END IF IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -21 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEEVX', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SQRT( SMLNUM ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ICOND = 0 ANRM = DLANGE( 'M', N, N, A, LDA, DUM ) SCALEA = .FALSE. IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN SCALEA = .TRUE. CSCALE = SMLNUM ELSE IF( ANRM.GT.BIGNUM ) THEN SCALEA = .TRUE. CSCALE = BIGNUM END IF IF( SCALEA ) $ CALL DLASCL( 'G', 0, 0, ANRM, CSCALE, N, N, A, LDA, IERR ) * * Balance the matrix and compute ABNRM * CALL DGEBAL( BALANC, N, A, LDA, ILO, IHI, SCALE, IERR ) ABNRM = DLANGE( '1', N, N, A, LDA, DUM ) IF( SCALEA ) THEN DUM( 1 ) = ABNRM CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, 1, 1, DUM, 1, IERR ) ABNRM = DUM( 1 ) END IF * * Reduce to upper Hessenberg form * (Workspace: need 2*N, prefer N+N*NB) * ITAU = 1 IWRK = ITAU + N CALL DGEHRD( N, ILO, IHI, A, LDA, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * IF( WANTVL ) THEN * * Want left eigenvectors * Copy Householder vectors to VL * SIDE = 'L' CALL DLACPY( 'L', N, N, A, LDA, VL, LDVL ) * * Generate orthogonal matrix in VL * (Workspace: need 2*N-1, prefer N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VL, LDVL, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VL * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VL, LDVL, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * IF( WANTVR ) THEN * * Want left and right eigenvectors * Copy Schur vectors to VR * SIDE = 'B' CALL DLACPY( 'F', N, N, VL, LDVL, VR, LDVR ) END IF * ELSE IF( WANTVR ) THEN * * Want right eigenvectors * Copy Householder vectors to VR * SIDE = 'R' CALL DLACPY( 'L', N, N, A, LDA, VR, LDVR ) * * Generate orthogonal matrix in VR * (Workspace: need 2*N-1, prefer N+(N-1)*NB) * CALL DORGHR( N, ILO, IHI, VR, LDVR, WORK( ITAU ), WORK( IWRK ), $ LWORK-IWRK+1, IERR ) * * Perform QR iteration, accumulating Schur vectors in VR * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( 'S', 'V', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) * ELSE * * Compute eigenvalues only * If condition numbers desired, compute Schur form * IF( WNTSNN ) THEN JOB = 'E' ELSE JOB = 'S' END IF * * (Workspace: need 1, prefer HSWORK (see comments) ) * IWRK = ITAU CALL DHSEQR( JOB, 'N', N, ILO, IHI, A, LDA, WR, WI, VR, LDVR, $ WORK( IWRK ), LWORK-IWRK+1, INFO ) END IF * * If INFO > 0 from DHSEQR, then quit * IF( INFO.GT.0 ) $ GO TO 50 * IF( WANTVL .OR. WANTVR ) THEN * * Compute left and/or right eigenvectors * (Workspace: need 3*N) * CALL DTREVC( SIDE, 'B', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ N, NOUT, WORK( IWRK ), IERR ) END IF * * Compute condition numbers if desired * (Workspace: need N*N+6*N unless SENSE = 'E') * IF( .NOT.WNTSNN ) THEN CALL DTRSNA( SENSE, 'A', SELECT, N, A, LDA, VL, LDVL, VR, LDVR, $ RCONDE, RCONDV, N, NOUT, WORK( IWRK ), N, IWORK, $ ICOND ) END IF * IF( WANTVL ) THEN * * Undo balancing of left eigenvectors * CALL DGEBAK( BALANC, 'L', N, ILO, IHI, SCALE, N, VL, LDVL, $ IERR ) * * Normalize left eigenvectors and make largest component real * DO 20 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VL( 1, I ), 1 ), $ DNRM2( N, VL( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VL( 1, I ), 1 ) CALL DSCAL( N, SCL, VL( 1, I+1 ), 1 ) DO 10 K = 1, N WORK( K ) = VL( K, I )**2 + VL( K, I+1 )**2 10 CONTINUE K = IDAMAX( N, WORK, 1 ) CALL DLARTG( VL( K, I ), VL( K, I+1 ), CS, SN, R ) CALL DROT( N, VL( 1, I ), 1, VL( 1, I+1 ), 1, CS, SN ) VL( K, I+1 ) = ZERO END IF 20 CONTINUE END IF * IF( WANTVR ) THEN * * Undo balancing of right eigenvectors * CALL DGEBAK( BALANC, 'R', N, ILO, IHI, SCALE, N, VR, LDVR, $ IERR ) * * Normalize right eigenvectors and make largest component real * DO 40 I = 1, N IF( WI( I ).EQ.ZERO ) THEN SCL = ONE / DNRM2( N, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) ELSE IF( WI( I ).GT.ZERO ) THEN SCL = ONE / DLAPY2( DNRM2( N, VR( 1, I ), 1 ), $ DNRM2( N, VR( 1, I+1 ), 1 ) ) CALL DSCAL( N, SCL, VR( 1, I ), 1 ) CALL DSCAL( N, SCL, VR( 1, I+1 ), 1 ) DO 30 K = 1, N WORK( K ) = VR( K, I )**2 + VR( K, I+1 )**2 30 CONTINUE K = IDAMAX( N, WORK, 1 ) CALL DLARTG( VR( K, I ), VR( K, I+1 ), CS, SN, R ) CALL DROT( N, VR( 1, I ), 1, VR( 1, I+1 ), 1, CS, SN ) VR( K, I+1 ) = ZERO END IF 40 CONTINUE END IF * * Undo scaling if necessary * 50 CONTINUE IF( SCALEA ) THEN CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WR( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N-INFO, 1, WI( INFO+1 ), $ MAX( N-INFO, 1 ), IERR ) IF( INFO.EQ.0 ) THEN IF( ( WNTSNV .OR. WNTSNB ) .AND. ICOND.EQ.0 ) $ CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, N, 1, RCONDV, N, $ IERR ) ELSE CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WR, N, $ IERR ) CALL DLASCL( 'G', 0, 0, CSCALE, ANRM, ILO-1, 1, WI, N, $ IERR ) END IF END IF * WORK( 1 ) = MAXWRK RETURN * * End of DGEEVX * END SUBROUTINE DGEHD2( N, ILO, IHI, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. INTEGER IHI, ILO, INFO, LDA, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGEHD2 reduces a real general matrix A to upper Hessenberg form H by * an orthogonal similarity transformation: Q' * A * Q = H . * * Arguments * ========= * * N (input) INTEGER * The order of the matrix A. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * It is assumed that A is already upper triangular in rows * and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally * set by a previous call to DGEBAL; otherwise they should be * set to 1 and N respectively. See Further Details. * 1 <= ILO <= IHI <= max(1,N). * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the n by n general matrix to be reduced. * On exit, the upper triangle and the first subdiagonal of A * are overwritten with the upper Hessenberg matrix H, and the * elements below the first subdiagonal, with the array TAU, * represent the orthogonal matrix Q as a product of elementary * reflectors. See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * TAU (output) DOUBLE PRECISION array, dimension (N-1) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * The matrix Q is represented as a product of (ihi-ilo) elementary * reflectors * * Q = H(ilo) H(ilo+1) . . . H(ihi-1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on * exit in A(i+2:ihi,i), and tau in TAU(i). * * The contents of A are illustrated by the following example, with * n = 7, ilo = 2 and ihi = 6: * * on entry, on exit, * * ( a a a a a a a ) ( a a h h h h a ) * ( a a a a a a ) ( a h h h h a ) * ( a a a a a a ) ( h h h h h h ) * ( a a a a a a ) ( v2 h h h h h ) * ( a a a a a a ) ( v2 v3 h h h h ) * ( a a a a a a ) ( v2 v3 v4 h h h ) * ( a ) ( a ) * * where a denotes an element of the original matrix A, h denotes a * modified element of the upper Hessenberg matrix H, and vi denotes an * element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I DOUBLE PRECISION AII * .. * .. External Subroutines .. EXTERNAL DLARF, DLARFG, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 IF( N.LT.0 ) THEN INFO = -1 ELSE IF( ILO.LT.1 .OR. ILO.GT.MAX( 1, N ) ) THEN INFO = -2 ELSE IF( IHI.LT.MIN( ILO, N ) .OR. IHI.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEHD2', -INFO ) RETURN END IF * DO 10 I = ILO, IHI - 1 * * Compute elementary reflector H(i) to annihilate A(i+2:ihi,i) * CALL DLARFG( IHI-I, A( I+1, I ), A( MIN( I+2, N ), I ), 1, $ TAU( I ) ) AII = A( I+1, I ) A( I+1, I ) = ONE * * Apply H(i) to A(1:ihi,i+1:ihi) from the right * CALL DLARF( 'Right', IHI, IHI-I, A( I+1, I ), 1, TAU( I ), $ A( 1, I+1 ), LDA, WORK ) * * Apply H(i) to A(i+1:ihi,i+1:n) from the left * CALL DLARF( 'Left', IHI-I, N-I, A( I+1, I ), 1, TAU( I ), $ A( I+1, I+1 ), LDA, WORK ) * A( I+1, I ) = AII 10 CONTINUE * RETURN * * End of DGEHD2 * END SUBROUTINE DGEHRD( N, ILO, IHI, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IHI, ILO, INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGEHRD reduces a real general matrix A to upper Hessenberg form H by * an orthogonal similarity transformation: Q' * A * Q = H . * * Arguments * ========= * * N (input) INTEGER * The order of the matrix A. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * It is assumed that A is already upper triangular in rows * and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally * set by a previous call to DGEBAL; otherwise they should be * set to 1 and N respectively. See Further Details. * 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the N-by-N general matrix to be reduced. * On exit, the upper triangle and the first subdiagonal of A * are overwritten with the upper Hessenberg matrix H, and the * elements below the first subdiagonal, with the array TAU, * represent the orthogonal matrix Q as a product of elementary * reflectors. See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * TAU (output) DOUBLE PRECISION array, dimension (N-1) * The scalar factors of the elementary reflectors (see Further * Details). Elements 1:ILO-1 and IHI:N-1 of TAU are set to * zero. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,N). * For optimum performance LWORK >= N*NB, where NB is the * optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * The matrix Q is represented as a product of (ihi-ilo) elementary * reflectors * * Q = H(ilo) H(ilo+1) . . . H(ihi-1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on * exit in A(i+2:ihi,i), and tau in TAU(i). * * The contents of A are illustrated by the following example, with * n = 7, ilo = 2 and ihi = 6: * * on entry, on exit, * * ( a a a a a a a ) ( a a h h h h a ) * ( a a a a a a ) ( a h h h h a ) * ( a a a a a a ) ( h h h h h h ) * ( a a a a a a ) ( v2 h h h h h ) * ( a a a a a a ) ( v2 v3 h h h h ) * ( a a a a a a ) ( v2 v3 v4 h h h ) * ( a ) ( a ) * * where a denotes an element of the original matrix A, h denotes a * modified element of the upper Hessenberg matrix H, and vi denotes an * element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. INTEGER NBMAX, LDT PARAMETER ( NBMAX = 64, LDT = NBMAX+1 ) DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, LDWORK, LWKOPT, NB, NBMIN, $ NH, NX DOUBLE PRECISION EI * .. * .. Local Arrays .. DOUBLE PRECISION T( LDT, NBMAX ) * .. * .. External Subroutines .. EXTERNAL DGEHD2, DGEMM, DLAHRD, DLARFB, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 NB = MIN( NBMAX, ILAENV( 1, 'DGEHRD', ' ', N, ILO, IHI, -1 ) ) LWKOPT = N*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( N.LT.0 ) THEN INFO = -1 ELSE IF( ILO.LT.1 .OR. ILO.GT.MAX( 1, N ) ) THEN INFO = -2 ELSE IF( IHI.LT.MIN( ILO, N ) .OR. IHI.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, N ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEHRD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Set elements 1:ILO-1 and IHI:N-1 of TAU to zero * DO 10 I = 1, ILO - 1 TAU( I ) = ZERO 10 CONTINUE DO 20 I = MAX( 1, IHI ), N - 1 TAU( I ) = ZERO 20 CONTINUE * * Quick return if possible * NH = IHI - ILO + 1 IF( NH.LE.1 ) THEN WORK( 1 ) = 1 RETURN END IF * * Determine the block size. * NB = MIN( NBMAX, ILAENV( 1, 'DGEHRD', ' ', N, ILO, IHI, -1 ) ) NBMIN = 2 IWS = 1 IF( NB.GT.1 .AND. NB.LT.NH ) THEN * * Determine when to cross over from blocked to unblocked code * (last block is always handled by unblocked code). * NX = MAX( NB, ILAENV( 3, 'DGEHRD', ' ', N, ILO, IHI, -1 ) ) IF( NX.LT.NH ) THEN * * Determine if workspace is large enough for blocked code. * IWS = N*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: determine the * minimum value of NB, and reduce NB or force use of * unblocked code. * NBMIN = MAX( 2, ILAENV( 2, 'DGEHRD', ' ', N, ILO, IHI, $ -1 ) ) IF( LWORK.GE.N*NBMIN ) THEN NB = LWORK / N ELSE NB = 1 END IF END IF END IF END IF LDWORK = N * IF( NB.LT.NBMIN .OR. NB.GE.NH ) THEN * * Use unblocked code below * I = ILO * ELSE * * Use blocked code * DO 30 I = ILO, IHI - 1 - NX, NB IB = MIN( NB, IHI-I ) * * Reduce columns i:i+ib-1 to Hessenberg form, returning the * matrices V and T of the block reflector H = I - V*T*V' * which performs the reduction, and also the matrix Y = A*V*T * CALL DLAHRD( IHI, I, IB, A( 1, I ), LDA, TAU( I ), T, LDT, $ WORK, LDWORK ) * * Apply the block reflector H to A(1:ihi,i+ib:ihi) from the * right, computing A := A - Y * V'. V(i+ib,ib-1) must be set * to 1. * EI = A( I+IB, I+IB-1 ) A( I+IB, I+IB-1 ) = ONE CALL DGEMM( 'No transpose', 'Transpose', IHI, IHI-I-IB+1, $ IB, -ONE, WORK, LDWORK, A( I+IB, I ), LDA, ONE, $ A( 1, I+IB ), LDA ) A( I+IB, I+IB-1 ) = EI * * Apply the block reflector H to A(i+1:ihi,i+ib:n) from the * left * CALL DLARFB( 'Left', 'Transpose', 'Forward', 'Columnwise', $ IHI-I, N-I-IB+1, IB, A( I+1, I ), LDA, T, LDT, $ A( I+1, I+IB ), LDA, WORK, LDWORK ) 30 CONTINUE END IF * * Use unblocked code to reduce the rest of the matrix * CALL DGEHD2( N, I, IHI, A, LDA, TAU, WORK, IINFO ) WORK( 1 ) = IWS * RETURN * * End of DGEHRD * END SUBROUTINE DGELQ2( M, N, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER INFO, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGELQ2 computes an LQ factorization of a real m by n matrix A: * A = L * Q. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the m by n matrix A. * On exit, the elements on and below the diagonal of the array * contain the m by min(m,n) lower trapezoidal matrix L (L is * lower triangular if m <= n); the elements above the diagonal, * with the array TAU, represent the orthogonal matrix Q as a * product of elementary reflectors (see Further Details). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace) DOUBLE PRECISION array, dimension (M) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The matrix Q is represented as a product of elementary reflectors * * Q = H(k) . . . H(2) H(1), where k = min(m,n). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i-1) = 0 and v(i) = 1; v(i+1:n) is stored on exit in A(i,i+1:n), * and tau in TAU(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I, K DOUBLE PRECISION AII * .. * .. External Subroutines .. EXTERNAL DLARF, DLARFG, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELQ2', -INFO ) RETURN END IF * K = MIN( M, N ) * DO 10 I = 1, K * * Generate elementary reflector H(i) to annihilate A(i,i+1:n) * CALL DLARFG( N-I+1, A( I, I ), A( I, MIN( I+1, N ) ), LDA, $ TAU( I ) ) IF( I.LT.M ) THEN * * Apply H(i) to A(i+1:m,i:n) from the right * AII = A( I, I ) A( I, I ) = ONE CALL DLARF( 'Right', M-I, N-I+1, A( I, I ), LDA, TAU( I ), $ A( I+1, I ), LDA, WORK ) A( I, I ) = AII END IF 10 CONTINUE RETURN * * End of DGELQ2 * END SUBROUTINE DGELQF( M, N, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGELQF computes an LQ factorization of a real M-by-N matrix A: * A = L * Q. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, the elements on and below the diagonal of the array * contain the m-by-min(m,n) lower trapezoidal matrix L (L is * lower triangular if m <= n); the elements above the diagonal, * with the array TAU, represent the orthogonal matrix Q as a * product of elementary reflectors (see Further Details). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,M). * For optimum performance LWORK >= M*NB, where NB is the * optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The matrix Q is represented as a product of elementary reflectors * * Q = H(k) . . . H(2) H(1), where k = min(m,n). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i-1) = 0 and v(i) = 1; v(i+1:n) is stored on exit in A(i,i+1:n), * and tau in TAU(i). * * ===================================================================== * * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, K, LDWORK, LWKOPT, NB, $ NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DGELQ2, DLARFB, DLARFT, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NB = ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) LWKOPT = M*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 ELSE IF( LWORK.LT.MAX( 1, M ) .AND. .NOT.LQUERY ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGELQF', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * K = MIN( M, N ) IF( K.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 NX = 0 IWS = M IF( NB.GT.1 .AND. NB.LT.K ) THEN * * Determine when to cross over from blocked to unblocked code. * NX = MAX( 0, ILAENV( 3, 'DGELQF', ' ', M, N, -1, -1 ) ) IF( NX.LT.K ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = M IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: reduce NB and * determine the minimum value of NB. * NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DGELQF', ' ', M, N, -1, $ -1 ) ) END IF END IF END IF * IF( NB.GE.NBMIN .AND. NB.LT.K .AND. NX.LT.K ) THEN * * Use blocked code initially * DO 10 I = 1, K - NX, NB IB = MIN( K-I+1, NB ) * * Compute the LQ factorization of the current block * A(i:i+ib-1,i:n) * CALL DGELQ2( IB, N-I+1, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) IF( I+IB.LE.M ) THEN * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Rowwise', N-I+1, IB, A( I, I ), $ LDA, TAU( I ), WORK, LDWORK ) * * Apply H to A(i+ib:m,i:n) from the right * CALL DLARFB( 'Right', 'No transpose', 'Forward', $ 'Rowwise', M-I-IB+1, N-I+1, IB, A( I, I ), $ LDA, WORK, LDWORK, A( I+IB, I ), LDA, $ WORK( IB+1 ), LDWORK ) END IF 10 CONTINUE ELSE I = 1 END IF * * Use unblocked code to factor the last or only block. * IF( I.LE.K ) $ CALL DGELQ2( M-I+1, N-I+1, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) * WORK( 1 ) = IWS RETURN * * End of DGELQF * END SUBROUTINE DGEQR2( M, N, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER INFO, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGEQR2 computes a QR factorization of a real m by n matrix A: * A = Q * R. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the m by n matrix A. * On exit, the elements on and above the diagonal of the array * contain the min(m,n) by n upper trapezoidal matrix R (R is * upper triangular if m >= n); the elements below the diagonal, * with the array TAU, represent the orthogonal matrix Q as a * product of elementary reflectors (see Further Details). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The matrix Q is represented as a product of elementary reflectors * * Q = H(1) H(2) . . . H(k), where k = min(m,n). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), * and tau in TAU(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I, K DOUBLE PRECISION AII * .. * .. External Subroutines .. EXTERNAL DLARF, DLARFG, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEQR2', -INFO ) RETURN END IF * K = MIN( M, N ) * DO 10 I = 1, K * * Generate elementary reflector H(i) to annihilate A(i+1:m,i) * CALL DLARFG( M-I+1, A( I, I ), A( MIN( I+1, M ), I ), 1, $ TAU( I ) ) IF( I.LT.N ) THEN * * Apply H(i) to A(i:m,i+1:n) from the left * AII = A( I, I ) A( I, I ) = ONE CALL DLARF( 'Left', M-I+1, N-I, A( I, I ), 1, TAU( I ), $ A( I, I+1 ), LDA, WORK ) A( I, I ) = AII END IF 10 CONTINUE RETURN * * End of DGEQR2 * END SUBROUTINE DGEQRF( M, N, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DGEQRF computes a QR factorization of a real M-by-N matrix A: * A = Q * R. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, the elements on and above the diagonal of the array * contain the min(M,N)-by-N upper trapezoidal matrix R (R is * upper triangular if m >= n); the elements below the diagonal, * with the array TAU, represent the orthogonal matrix Q as a * product of min(m,n) elementary reflectors (see Further * Details). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N). * For optimum performance LWORK >= N*NB, where NB is * the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The matrix Q is represented as a product of elementary reflectors * * Q = H(1) H(2) . . . H(k), where k = min(m,n). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), * and tau in TAU(i). * * ===================================================================== * * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, K, LDWORK, LWKOPT, NB, $ NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DGEQR2, DLARFB, DLARFT, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NB = ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) LWKOPT = N*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -4 ELSE IF( LWORK.LT.MAX( 1, N ) .AND. .NOT.LQUERY ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEQRF', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * K = MIN( M, N ) IF( K.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 NX = 0 IWS = N IF( NB.GT.1 .AND. NB.LT.K ) THEN * * Determine when to cross over from blocked to unblocked code. * NX = MAX( 0, ILAENV( 3, 'DGEQRF', ' ', M, N, -1, -1 ) ) IF( NX.LT.K ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = N IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: reduce NB and * determine the minimum value of NB. * NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DGEQRF', ' ', M, N, -1, $ -1 ) ) END IF END IF END IF * IF( NB.GE.NBMIN .AND. NB.LT.K .AND. NX.LT.K ) THEN * * Use blocked code initially * DO 10 I = 1, K - NX, NB IB = MIN( K-I+1, NB ) * * Compute the QR factorization of the current block * A(i:m,i:i+ib-1) * CALL DGEQR2( M-I+1, IB, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) IF( I+IB.LE.N ) THEN * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Columnwise', M-I+1, IB, $ A( I, I ), LDA, TAU( I ), WORK, LDWORK ) * * Apply H' to A(i:m,i+ib:n) from the left * CALL DLARFB( 'Left', 'Transpose', 'Forward', $ 'Columnwise', M-I+1, N-I-IB+1, IB, $ A( I, I ), LDA, WORK, LDWORK, A( I, I+IB ), $ LDA, WORK( IB+1 ), LDWORK ) END IF 10 CONTINUE ELSE I = 1 END IF * * Use unblocked code to factor the last or only block. * IF( I.LE.K ) $ CALL DGEQR2( M-I+1, N-I+1, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) * WORK( 1 ) = IWS RETURN * * End of DGEQRF * END SUBROUTINE DGESC2( N, A, LDA, RHS, IPIV, JPIV, SCALE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER LDA, N DOUBLE PRECISION SCALE * .. * .. Array Arguments .. INTEGER IPIV( * ), JPIV( * ) DOUBLE PRECISION A( LDA, * ), RHS( * ) * .. * * Purpose * ======= * * DGESC2 solves a system of linear equations * * A * X = scale* RHS * * with a general N-by-N matrix A using the LU factorization with * complete pivoting computed by DGETC2. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix A. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the LU part of the factorization of the n-by-n * matrix A computed by DGETC2: A = P * L * U * Q * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1, N). * * RHS (input/output) DOUBLE PRECISION array, dimension (N). * On entry, the right hand side vector b. * On exit, the solution vector X. * * IPIV (iput) INTEGER array, dimension (N). * The pivot indices; for 1 <= i <= N, row i of the * matrix has been interchanged with row IPIV(i). * * JPIV (iput) INTEGER array, dimension (N). * The pivot indices; for 1 <= j <= N, column j of the * matrix has been interchanged with column JPIV(j). * * SCALE (output) DOUBLE PRECISION * On exit, SCALE contains the scale factor. SCALE is chosen * 0 <= SCALE <= 1 to prevent owerflow in the solution. * * Further Details * =============== * * Based on contributions by * Bo Kagstrom and Peter Poromaa, Department of Computing Science, * Umea University, S-901 87 Umea, Sweden. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, TWO PARAMETER ( ONE = 1.0D+0, TWO = 2.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J DOUBLE PRECISION BIGNUM, EPS, SMLNUM, TEMP * .. * .. External Subroutines .. EXTERNAL DLASWP, DSCAL * .. * .. External Functions .. INTEGER IDAMAX DOUBLE PRECISION DLAMCH EXTERNAL IDAMAX, DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * * Set constant to control owerflow * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) / EPS BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Apply permutations IPIV to RHS * CALL DLASWP( 1, RHS, LDA, 1, N-1, IPIV, 1 ) * * Solve for L part * DO 20 I = 1, N - 1 DO 10 J = I + 1, N RHS( J ) = RHS( J ) - A( J, I )*RHS( I ) 10 CONTINUE 20 CONTINUE * * Solve for U part * SCALE = ONE * * Check for scaling * I = IDAMAX( N, RHS, 1 ) IF( TWO*SMLNUM*ABS( RHS( I ) ).GT.ABS( A( N, N ) ) ) THEN TEMP = ( ONE / TWO ) / ABS( RHS( I ) ) CALL DSCAL( N, TEMP, RHS( 1 ), 1 ) SCALE = SCALE*TEMP END IF * DO 40 I = N, 1, -1 TEMP = ONE / A( I, I ) RHS( I ) = RHS( I )*TEMP DO 30 J = I + 1, N RHS( I ) = RHS( I ) - RHS( J )*( A( I, J )*TEMP ) 30 CONTINUE 40 CONTINUE * * Apply permutations JPIV to the solution (RHS) * CALL DLASWP( 1, RHS, LDA, 1, N-1, JPIV, -1 ) RETURN * * End of DGESC2 * END SUBROUTINE DGESVD( JOBU, JOBVT, M, N, A, LDA, S, U, LDU, VT, LDVT, $ WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBU, JOBVT INTEGER INFO, LDA, LDU, LDVT, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), S( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DGESVD computes the singular value decomposition (SVD) of a real * M-by-N matrix A, optionally computing the left and/or right singular * vectors. The SVD is written * * A = U * SIGMA * transpose(V) * * where SIGMA is an M-by-N matrix which is zero except for its * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA * are the singular values of A; they are real and non-negative, and * are returned in descending order. The first min(m,n) columns of * U and V are the left and right singular vectors of A. * * Note that the routine returns V**T, not V. * * Arguments * ========= * * JOBU (input) CHARACTER*1 * Specifies options for computing all or part of the matrix U: * = 'A': all M columns of U are returned in array U: * = 'S': the first min(m,n) columns of U (the left singular * vectors) are returned in the array U; * = 'O': the first min(m,n) columns of U (the left singular * vectors) are overwritten on the array A; * = 'N': no columns of U (no left singular vectors) are * computed. * * JOBVT (input) CHARACTER*1 * Specifies options for computing all or part of the matrix * V**T: * = 'A': all N rows of V**T are returned in the array VT; * = 'S': the first min(m,n) rows of V**T (the right singular * vectors) are returned in the array VT; * = 'O': the first min(m,n) rows of V**T (the right singular * vectors) are overwritten on the array A; * = 'N': no rows of V**T (no right singular vectors) are * computed. * * JOBVT and JOBU cannot both be 'O'. * * 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. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, * if JOBU = 'O', A is overwritten with the first min(m,n) * columns of U (the left singular vectors, * stored columnwise); * if JOBVT = 'O', A is overwritten with the first min(m,n) * rows of V**T (the right singular vectors, * stored rowwise); * if JOBU .ne. 'O' and JOBVT .ne. 'O', the contents of A * are destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A, sorted so that S(i) >= S(i+1). * * U (output) DOUBLE PRECISION array, dimension (LDU,UCOL) * (LDU,M) if JOBU = 'A' or (LDU,min(M,N)) if JOBU = 'S'. * If JOBU = 'A', U contains the M-by-M orthogonal matrix U; * if JOBU = 'S', U contains the first min(m,n) columns of U * (the left singular vectors, stored columnwise); * if JOBU = 'N' or 'O', U is not referenced. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= 1; if * JOBU = 'S' or 'A', LDU >= M. * * VT (output) DOUBLE PRECISION array, dimension (LDVT,N) * If JOBVT = 'A', VT contains the N-by-N orthogonal matrix * V**T; * if JOBVT = 'S', VT contains the first min(m,n) rows of * V**T (the right singular vectors, stored rowwise); * if JOBVT = 'N' or 'O', VT is not referenced. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= 1; if * JOBVT = 'A', LDVT >= N; if JOBVT = 'S', LDVT >= min(M,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK; * if INFO > 0, WORK(2:MIN(M,N)) contains the unconverged * superdiagonal elements of an upper bidiagonal matrix B * whose diagonal is in S (not necessarily sorted). B * satisfies A = U * B * VT, so it has the same singular values * as A, and singular vectors related by U and VT. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1. * LWORK >= MAX(3*MIN(M,N)+MAX(M,N),5*MIN(M,N)). * For good performance, LWORK should generally be larger. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if DBDSQR did not converge, INFO specifies how many * superdiagonals of an intermediate bidiagonal form B * did not converge to zero. See the description of WORK * above for details. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WNTUA, WNTUAS, WNTUN, WNTUO, WNTUS, $ WNTVA, WNTVAS, WNTVN, WNTVO, WNTVS INTEGER BDSPAC, BLK, CHUNK, I, IE, IERR, IR, ISCL, $ ITAU, ITAUP, ITAUQ, IU, IWORK, LDWRKR, LDWRKU, $ MAXWRK, MINMN, MINWRK, MNTHR, NCU, NCVT, NRU, $ NRVT, WRKBL DOUBLE PRECISION ANRM, BIGNUM, EPS, SMLNUM * .. * .. Local Arrays .. DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DBDSQR, DGEBRD, DGELQF, DGEMM, DGEQRF, DLACPY, $ DLASCL, DLASET, DORGBR, DORGLQ, DORGQR, DORMBR, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL LSAME, ILAENV, DLAMCH, DLANGE * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 MINMN = MIN( M, N ) MNTHR = ILAENV( 6, 'DGESVD', JOBU // JOBVT, M, N, 0, 0 ) WNTUA = LSAME( JOBU, 'A' ) WNTUS = LSAME( JOBU, 'S' ) WNTUAS = WNTUA .OR. WNTUS WNTUO = LSAME( JOBU, 'O' ) WNTUN = LSAME( JOBU, 'N' ) WNTVA = LSAME( JOBVT, 'A' ) WNTVS = LSAME( JOBVT, 'S' ) WNTVAS = WNTVA .OR. WNTVS WNTVO = LSAME( JOBVT, 'O' ) WNTVN = LSAME( JOBVT, 'N' ) MINWRK = 1 LQUERY = ( LWORK.EQ.-1 ) * IF( .NOT.( WNTUA .OR. WNTUS .OR. WNTUO .OR. WNTUN ) ) THEN INFO = -1 ELSE IF( .NOT.( WNTVA .OR. WNTVS .OR. WNTVO .OR. WNTVN ) .OR. $ ( WNTVO .AND. WNTUO ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -6 ELSE IF( LDU.LT.1 .OR. ( WNTUAS .AND. LDU.LT.M ) ) THEN INFO = -9 ELSE IF( LDVT.LT.1 .OR. ( WNTVA .AND. LDVT.LT.N ) .OR. $ ( WNTVS .AND. LDVT.LT.MINMN ) ) THEN INFO = -11 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * IF( INFO.EQ.0 .AND. ( LWORK.GE.1 .OR. LQUERY ) .AND. M.GT.0 .AND. $ N.GT.0 ) THEN IF( M.GE.N ) THEN * * Compute space needed for DBDSQR * BDSPAC = 5*N IF( M.GE.MNTHR ) THEN IF( WNTUN ) THEN * * Path 1 (M much larger than N, JOBU='N') * MAXWRK = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, $ -1 ) MAXWRK = MAX( MAXWRK, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) IF( WNTVO .OR. WNTVAS ) $ MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 4*N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUO .AND. WNTVN ) THEN * * Path 2 (M much larger than N, JOBU='O', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( N*N+WRKBL, N*N+M*N+N ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUO .AND. WNTVAS ) THEN * * Path 3 (M much larger than N, JOBU='O', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( N*N+WRKBL, N*N+M*N+N ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVN ) THEN * * Path 4 (M much larger than N, JOBU='S', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVO ) THEN * * Path 5 (M much larger than N, JOBU='S', JOBVT='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUS .AND. WNTVAS ) THEN * * Path 6 (M much larger than N, JOBU='S', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVN ) THEN * * Path 7 (M much larger than N, JOBU='A', JOBVT='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVO ) THEN * * Path 8 (M much larger than N, JOBU='A', JOBVT='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTUA .AND. WNTVAS ) THEN * * Path 9 (M much larger than N, JOBU='A', JOBVT='S' or * 'A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = N*N + WRKBL MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Path 10 (M at least N, but not much larger) * MAXWRK = 3*N + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) IF( WNTUS .OR. WNTUO ) $ MAXWRK = MAX( MAXWRK, 3*N+N* $ ILAENV( 1, 'DORGBR', 'Q', M, N, N, -1 ) ) IF( WNTUA ) $ MAXWRK = MAX( MAXWRK, 3*N+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, N, -1 ) ) IF( .NOT.WNTVN ) $ MAXWRK = MAX( MAXWRK, 3*N+( N-1 )* $ ILAENV( 1, 'DORGBR', 'P', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 3*N+M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Compute space needed for DBDSQR * BDSPAC = 5*M IF( N.GE.MNTHR ) THEN IF( WNTVN ) THEN * * Path 1t(N much larger than M, JOBVT='N') * MAXWRK = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, $ -1 ) MAXWRK = MAX( MAXWRK, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) IF( WNTUO .OR. WNTUAS ) $ MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 4*M, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVO .AND. WNTUN ) THEN * * Path 2t(N much larger than M, JOBU='N', JOBVT='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( M*M+WRKBL, M*M+M*N+M ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVO .AND. WNTUAS ) THEN * * Path 3t(N much larger than M, JOBU='S' or 'A', * JOBVT='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = MAX( M*M+WRKBL, M*M+M*N+M ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUN ) THEN * * Path 4t(N much larger than M, JOBU='N', JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUO ) THEN * * Path 5t(N much larger than M, JOBU='O', JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVS .AND. WNTUAS ) THEN * * Path 6t(N much larger than M, JOBU='S' or 'A', * JOBVT='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUN ) THEN * * Path 7t(N much larger than M, JOBU='N', JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUO ) THEN * * Path 8t(N much larger than M, JOBU='O', JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = 2*M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) ELSE IF( WNTVA .AND. WNTUAS ) THEN * * Path 9t(N much larger than M, JOBU='S' or 'A', * JOBVT='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'P', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC ) MAXWRK = M*M + WRKBL MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF ELSE * * Path 10t(N greater than M, but not much larger) * MAXWRK = 3*M + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, $ -1, -1 ) IF( WNTVS .OR. WNTVO ) $ MAXWRK = MAX( MAXWRK, 3*M+M* $ ILAENV( 1, 'DORGBR', 'P', M, N, M, -1 ) ) IF( WNTVA ) $ MAXWRK = MAX( MAXWRK, 3*M+N* $ ILAENV( 1, 'DORGBR', 'P', N, N, M, -1 ) ) IF( .NOT.WNTUN ) $ MAXWRK = MAX( MAXWRK, 3*M+( M-1 )* $ ILAENV( 1, 'DORGBR', 'Q', M, M, M, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC ) MINWRK = MAX( 3*M+N, BDSPAC ) MAXWRK = MAX( MAXWRK, MINWRK ) END IF END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESVD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN IF( LWORK.GE.1 ) $ WORK( 1 ) = ONE RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = SQRT( DLAMCH( 'S' ) ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, DUM ) ISCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, IERR ) ELSE IF( ANRM.GT.BIGNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, IERR ) END IF * IF( M.GE.N ) THEN * * A has at least as many rows as columns. If A has sufficiently * more rows than columns, first reduce using the QR * decomposition (if sufficient workspace available) * IF( M.GE.MNTHR ) THEN * IF( WNTUN ) THEN * * Path 1 (M much larger than N, JOBU='N') * No left singular vectors to be computed * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Zero out below R * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) NCVT = 0 IF( WNTVO .OR. WNTVAS ) THEN * * If right singular vectors desired, generate P'. * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) NCVT = N END IF IWORK = IE + N * * Perform bidiagonal QR iteration, computing right * singular vectors of A in A if desired * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, 0, 0, S, WORK( IE ), A, LDA, $ DUM, 1, DUM, 1, WORK( IWORK ), INFO ) * * If right singular vectors desired in VT, copy them there * IF( WNTVAS ) $ CALL DLACPY( 'F', N, N, A, LDA, VT, LDVT ) * ELSE IF( WNTUO .AND. WNTVN ) THEN * * Path 2 (M much larger than N, JOBU='O', JOBVT='N') * N left singular vectors to be overwritten on A and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+LDA*N ) THEN * * WORK(IU) is LDA by N, WORK(IR) is LDA by N * LDWRKU = LDA LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+N*N ) THEN * * WORK(IU) is LDA by N, WORK(IR) is N by N * LDWRKU = LDA LDWRKR = N ELSE * * WORK(IU) is LDWRKU by N, WORK(IR) is N by N * LDWRKU = ( LWORK-N*N-N ) / N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IR) and zero out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing R * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, 1, $ WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + N * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in WORK(IU) and copying to A * (Workspace: need N*N+2*N, prefer N*N+M*N+N) * DO 10 I = 1, M, LDWRKU CHUNK = MIN( M-I+1, LDWRKU ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IR ), LDWRKR, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', CHUNK, N, WORK( IU ), LDWRKU, $ A( I, 1 ), LDA ) 10 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing A * (Workspace: need 4*N, prefer 3*N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, 1, $ A, LDA, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTUO .AND. WNTVAS ) THEN * * Path 3 (M much larger than N, JOBU='O', JOBVT='S' or 'A') * N left singular vectors to be overwritten on A and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+N )+N*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA LDWRKR = N ELSE * * WORK(IU) is LDWRKU by N and WORK(IR) is N by N * LDWRKU = ( LWORK-N*N-N ) / N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT, copying result to WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', N, N, VT, LDVT, WORK( IR ), LDWRKR ) * * Generate left vectors bidiagonalizing R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in VT * (Workspace: need N*N+4*N-1, prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) and computing right * singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, LDVT, $ WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + N * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in WORK(IU) and copying to A * (Workspace: need N*N+2*N, prefer N*N+M*N+N) * DO 20 I = 1, M, LDWRKU CHUNK = MIN( M-I+1, LDWRKU ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IR ), LDWRKR, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', CHUNK, N, WORK( IU ), LDWRKU, $ A( I, 1 ), LDA ) 20 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) * * Generate Q in A * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in A by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), A, LDA, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, LDVT, $ A, LDA, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTUS ) THEN * IF( WNTVN ) THEN * * Path 4 (M much larger than N, JOBU='S', JOBVT='N') * N left singular vectors to be computed in U and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IR) is LDA by N * LDWRKR = LDA ELSE * * WORK(IR) is N by N * LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IR+1 ), LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, $ 1, WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IR ), LDWRKR, ZERO, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, $ 1, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVO ) THEN * * Path 5 (M much larger than N, JOBU='S', JOBVT='O') * N left singular vectors to be computed in U and * N right singular vectors to be overwritten on A * IF( LWORK.GE.2*N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+N )*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = N ELSE * * WORK(IU) is N by N and WORK(IR) is N by N * LDWRKU = N IR = IU + LDWRKU*N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) * * Generate Q in A * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*N*N+4*N, * prefer 2*N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*N*N+4*N, prefer 2*N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*N*N+4*N-1, * prefer 2*N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in WORK(IR) * (Workspace: need 2*N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, WORK( IU ), $ LDWRKU, DUM, 1, WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IU ), LDWRKU, ZERO, U, LDU ) * * Copy right singular vectors of R to A * (Workspace: need N*N) * CALL DLACPY( 'F', N, N, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left vectors bidiagonalizing R * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing R in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), A, $ LDA, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVAS ) THEN * * Path 6 (M much larger than N, JOBU='S', JOBVT='S' * or 'A') * N left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is N by N * LDWRKU = N END IF ITAU = IU + LDWRKU*N IWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to VT * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, VT, $ LDVT ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need N*N+4*N-1, * prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, $ LDVT, WORK( IU ), LDWRKU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in U * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, $ WORK( IU ), LDWRKU, ZERO, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N, prefer N+N*NB) * CALL DORGQR( M, N, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in VT * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * ELSE IF( WNTUA ) THEN * IF( WNTVN ) THEN * * Path 7 (M much larger than N, JOBU='A', JOBVT='N') * M left singular vectors to be computed in U and * no right singular vectors to be computed * IF( LWORK.GE.N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IR) is LDA by N * LDWRKR = LDA ELSE * * WORK(IR) is N by N * LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IR+1 ), LDWRKR ) * * Generate Q in U * (Workspace: need N*N+N+M, prefer N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IR) * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, 0, N, 0, S, WORK( IE ), DUM, $ 1, WORK( IR ), LDWRKR, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IR), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IR ), LDWRKR, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in A * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, 0, M, 0, S, WORK( IE ), DUM, $ 1, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVO ) THEN * * Path 8 (M much larger than N, JOBU='A', JOBVT='O') * M left singular vectors to be computed in U and * N right singular vectors to be overwritten on A * IF( LWORK.GE.2*N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+N )*N ) THEN * * WORK(IU) is LDA by N and WORK(IR) is N by N * LDWRKU = LDA IR = IU + LDWRKU*N LDWRKR = N ELSE * * WORK(IU) is N by N and WORK(IR) is N by N * LDWRKU = N IR = IU + LDWRKU*N LDWRKR = N END IF ITAU = IR + LDWRKR*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N*N+2*N, prefer 2*N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need 2*N*N+N+M, prefer 2*N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*N*N+4*N, * prefer 2*N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*N*N+4*N, prefer 2*N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*N*N+4*N-1, * prefer 2*N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in WORK(IR) * (Workspace: need 2*N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, WORK( IU ), $ LDWRKU, DUM, 1, WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IU ), LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * * Copy right singular vectors of R from WORK(IR) to A * CALL DLACPY( 'F', N, N, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Zero out below R in A * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), $ LDA ) * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in A * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), A, $ LDA, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTVAS ) THEN * * Path 9 (M much larger than N, JOBU='A', JOBVT='S' * or 'A') * M left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IF( LWORK.GE.N*N+MAX( N+M, 4*N, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*N ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is N by N * LDWRKU = N END IF ITAU = IU + LDWRKU*N IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N*N+N+M, prefer N*N+N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R to WORK(IU), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, $ WORK( IU+1 ), LDWRKU ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in WORK(IU), copying result to VT * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', N, N, WORK( IU ), LDWRKU, VT, $ LDVT ) * * Generate left bidiagonalizing vectors in WORK(IU) * (Workspace: need N*N+4*N, prefer N*N+3*N+N*NB) * CALL DORGBR( 'Q', N, N, N, WORK( IU ), LDWRKU, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need N*N+4*N-1, * prefer N*N+3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of R in WORK(IU) and computing * right singular vectors of R in VT * (Workspace: need N*N+BDSPAC) * CALL DBDSQR( 'U', N, N, N, 0, S, WORK( IE ), VT, $ LDVT, WORK( IU ), LDWRKU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, $ WORK( IU ), LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N+M, prefer N+M*NB) * CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy R from A to VT, zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, VT( 2, 1 ), $ LDVT ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize R in VT * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, VT, LDVT, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply Q in U by left bidiagonalizing vectors * in VT * (Workspace: need 3*N+M, prefer 3*N+M*NB) * CALL DORMBR( 'Q', 'R', 'N', M, N, N, VT, LDVT, $ WORK( ITAUQ ), U, LDU, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + N * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * END IF * ELSE * * M .LT. MNTHR * * Path 10 (M at least N, but not much larger) * Reduce to bidiagonal form without QR decomposition * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N IWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUAS ) THEN * * If left singular vectors desired in U, copy result to U * and generate left bidiagonalizing vectors in U * (Workspace: need 3*N+NCU, prefer 3*N+NCU*NB) * CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) IF( WNTUS ) $ NCU = N IF( WNTUA ) $ NCU = M CALL DORGBR( 'Q', M, NCU, N, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVAS ) THEN * * If right singular vectors desired in VT, copy result to * VT and generate right bidiagonalizing vectors in VT * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DLACPY( 'U', N, N, A, LDA, VT, LDVT ) CALL DORGBR( 'P', N, N, N, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTUO ) THEN * * If left singular vectors desired in A, generate left * bidiagonalizing vectors in A * (Workspace: need 4*N, prefer 3*N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVO ) THEN * * If right singular vectors desired in A, generate right * bidiagonalizing vectors in A * (Workspace: need 4*N-1, prefer 3*N+(N-1)*NB) * CALL DORGBR( 'P', N, N, N, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + N IF( WNTUAS .OR. WNTUO ) $ NRU = M IF( WNTUN ) $ NRU = 0 IF( WNTVAS .OR. WNTVO ) $ NCVT = N IF( WNTVN ) $ NCVT = 0 IF( ( .NOT.WNTUO ) .AND. ( .NOT.WNTVO ) ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE IF( ( .NOT.WNTUO ) .AND. WNTVO ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in A and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', N, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), INFO ) END IF * END IF * ELSE * * A has more columns than rows. If A has sufficiently more * columns than rows, first reduce using the LQ decomposition (if * sufficient workspace available) * IF( N.GE.MNTHR ) THEN * IF( WNTVN ) THEN * * Path 1t(N much larger than M, JOBVT='N') * No right singular vectors to be computed * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Zero out above L * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUO .OR. WNTUAS ) THEN * * If left singular vectors desired, generate Q * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + M NRU = 0 IF( WNTUO .OR. WNTUAS ) $ NRU = M * * Perform bidiagonal QR iteration, computing left singular * vectors of A in A if desired * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, 0, NRU, 0, S, WORK( IE ), DUM, 1, A, $ LDA, DUM, 1, WORK( IWORK ), INFO ) * * If left singular vectors desired in U, copy them there * IF( WNTUAS ) $ CALL DLACPY( 'F', M, M, A, LDA, U, LDU ) * ELSE IF( WNTVO .AND. WNTUN ) THEN * * Path 2t(N much larger than M, JOBU='N', JOBVT='O') * M right singular vectors to be overwritten on A and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+LDA*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by M * LDWRKU = LDA CHUNK = N LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+M*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is M by M * LDWRKU = LDA CHUNK = N LDWRKR = M ELSE * * WORK(IU) is M by CHUNK and WORK(IR) is M by M * LDWRKU = M CHUNK = ( LWORK-M*M-M ) / M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IR) and zero out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing L * (Workspace: need M*M+4*M-1, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + M * * Multiply right singular vectors of L in WORK(IR) by Q * in A, storing result in WORK(IU) and copying to A * (Workspace: need M*M+2*M, prefer M*M+M*N+M) * DO 30 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IR ), $ LDWRKR, A( 1, I ), LDA, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', M, BLK, WORK( IU ), LDWRKU, $ A( 1, I ), LDA ) 30 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, N, 0, 0, S, WORK( IE ), A, LDA, $ DUM, 1, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTVO .AND. WNTUAS ) THEN * * Path 3t(N much larger than M, JOBU='S' or 'A', JOBVT='O') * M right singular vectors to be overwritten on A and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+LDA*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is LDA by M * LDWRKU = LDA CHUNK = N LDWRKR = LDA ELSE IF( LWORK.GE.MAX( WRKBL, LDA*N+M )+M*M ) THEN * * WORK(IU) is LDA by N and WORK(IR) is M by M * LDWRKU = LDA CHUNK = N LDWRKR = M ELSE * * WORK(IU) is M by CHUNK and WORK(IR) is M by M * LDWRKU = M CHUNK = ( LWORK-M*M-M ) / M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing about above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U, copying result to WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, M, U, LDU, WORK( IR ), LDWRKR ) * * Generate right vectors bidiagonalizing L in WORK(IR) * (Workspace: need M*M+4*M-1, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing L in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U, and computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) IU = IE + M * * Multiply right singular vectors of L in WORK(IR) by Q * in A, storing result in WORK(IU) and copying to A * (Workspace: need M*M+2*M, prefer M*M+M*N+M)) * DO 40 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IR ), $ LDWRKR, A( 1, I ), LDA, ZERO, $ WORK( IU ), LDWRKU ) CALL DLACPY( 'F', M, BLK, WORK( IU ), LDWRKU, $ A( 1, I ), LDA ) 40 CONTINUE * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) * * Generate Q in A * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in A * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), A, LDA, WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left vectors bidiagonalizing L in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) * END IF * ELSE IF( WNTVS ) THEN * IF( WNTUN ) THEN * * Path 4t(N much larger than M, JOBU='N', JOBVT='S') * M right singular vectors to be computed in VT and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IR) is LDA by M * LDWRKR = LDA ELSE * * WORK(IR) is M by M * LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IR), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right vectors bidiagonalizing L in * WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IR) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IR ), $ LDWRKR, A, LDA, ZERO, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy result to VT * CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, 0, 0, S, WORK( IE ), VT, $ LDVT, DUM, 1, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUO ) THEN * * Path 5t(N much larger than M, JOBU='O', JOBVT='S') * M right singular vectors to be computed in VT and * M left singular vectors to be overwritten on A * IF( LWORK.GE.2*M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is LDA by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+M )*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is M by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = M ELSE * * WORK(IU) is M by M and WORK(IR) is M by M * LDWRKU = M IR = IU + LDWRKU*M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out below it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) * * Generate Q in A * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*M*M+4*M, * prefer 2*M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*M*M+4*M-1, * prefer 2*M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*M*M+4*M, prefer 2*M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in WORK(IR) and computing * right singular vectors of L in WORK(IU) * (Workspace: need 2*M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, WORK( IR ), $ LDWRKR, DUM, 1, WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, A, LDA, ZERO, VT, LDVT ) * * Copy left singular vectors of L to A * (Workspace: need M*M) * CALL DLACPY( 'F', M, M, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right vectors bidiagonalizing L by Q in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors of L in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, compute left * singular vectors of A in A and compute right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUAS ) THEN * * Path 6t(N much larger than M, JOBU='S' or 'A', * JOBVT='S') * M right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IU) is LDA by N * LDWRKU = LDA ELSE * * WORK(IU) is LDA by M * LDWRKU = M END IF ITAU = IU + LDWRKU*M IWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, U, $ LDU ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need M*M+4*M-1, * prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U and computing right * singular vectors of L in WORK(IU) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, A, LDA, ZERO, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DORGLQ( M, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in U by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * ELSE IF( WNTVA ) THEN * IF( WNTUN ) THEN * * Path 7t(N much larger than M, JOBU='N', JOBVT='A') * N right singular vectors to be computed in VT and * no left singular vectors to be computed * IF( LWORK.GE.M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IR = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IR) is LDA by M * LDWRKR = LDA ELSE * * WORK(IR) is M by M * LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Copy L to WORK(IR), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IR ), $ LDWRKR ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IR+LDWRKR ), LDWRKR ) * * Generate Q in VT * (Workspace: need M*M+M+N, prefer M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IR) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IR ), LDWRKR, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate right bidiagonalizing vectors in WORK(IR) * (Workspace: need M*M+4*M-1, * prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of L in WORK(IR) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, 0, 0, S, WORK( IE ), $ WORK( IR ), LDWRKR, DUM, 1, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IR) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IR ), $ LDWRKR, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in A by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, 0, 0, S, WORK( IE ), VT, $ LDVT, DUM, 1, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUO ) THEN * * Path 8t(N much larger than M, JOBU='O', JOBVT='A') * N right singular vectors to be computed in VT and * M left singular vectors to be overwritten on A * IF( LWORK.GE.2*M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+2*LDA*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is LDA by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = LDA ELSE IF( LWORK.GE.WRKBL+( LDA+M )*M ) THEN * * WORK(IU) is LDA by M and WORK(IR) is M by M * LDWRKU = LDA IR = IU + LDWRKU*M LDWRKR = M ELSE * * WORK(IU) is M by M and WORK(IR) is M by M * LDWRKU = M IR = IU + LDWRKU*M LDWRKR = M END IF ITAU = IR + LDWRKR*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M*M+2*M, prefer 2*M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need 2*M*M+M+N, prefer 2*M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to * WORK(IR) * (Workspace: need 2*M*M+4*M, * prefer 2*M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, $ WORK( IR ), LDWRKR ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need 2*M*M+4*M-1, * prefer 2*M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in WORK(IR) * (Workspace: need 2*M*M+4*M, prefer 2*M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in WORK(IR) and computing * right singular vectors of L in WORK(IU) * (Workspace: need 2*M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, WORK( IR ), $ LDWRKR, DUM, 1, WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * * Copy left singular vectors of A from WORK(IR) to A * CALL DLACPY( 'F', M, M, WORK( IR ), LDWRKR, A, $ LDA ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Zero out above L in A * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), $ LDA ) * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in A by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in A and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * ELSE IF( WNTUAS ) THEN * * Path 9t(N much larger than M, JOBU='S' or 'A', * JOBVT='A') * N right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IF( LWORK.GE.M*M+MAX( N+M, 4*M, BDSPAC ) ) THEN * * Sufficient workspace for a fast algorithm * IU = 1 IF( LWORK.GE.WRKBL+LDA*M ) THEN * * WORK(IU) is LDA by M * LDWRKU = LDA ELSE * * WORK(IU) is M by M * LDWRKU = M END IF ITAU = IU + LDWRKU*M IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M*M+M+N, prefer M*M+M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to WORK(IU), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IU ), $ LDWRKU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IU+LDWRKU ), LDWRKU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IU ), LDWRKU, S, $ WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) CALL DLACPY( 'L', M, M, WORK( IU ), LDWRKU, U, $ LDU ) * * Generate right bidiagonalizing vectors in WORK(IU) * (Workspace: need M*M+4*M, prefer M*M+3*M+(M-1)*NB) * CALL DORGBR( 'P', M, M, M, WORK( IU ), LDWRKU, $ WORK( ITAUP ), WORK( IWORK ), $ LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need M*M+4*M, prefer M*M+3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of L in U and computing right * singular vectors of L in WORK(IU) * (Workspace: need M*M+BDSPAC) * CALL DBDSQR( 'U', M, M, M, 0, S, WORK( IE ), $ WORK( IU ), LDWRKU, U, LDU, DUM, 1, $ WORK( IWORK ), INFO ) * * Multiply right singular vectors of L in WORK(IU) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IU ), $ LDWRKU, VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * ELSE * * Insufficient workspace for a fast algorithm * ITAU = 1 IWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M+N, prefer M+N*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Copy L to U, zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, U( 1, 2 ), $ LDU ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize L in U * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, U, LDU, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Multiply right bidiagonalizing vectors in U by Q * in VT * (Workspace: need 3*M+N, prefer 3*M+N*NB) * CALL DORMBR( 'P', 'L', 'T', M, N, M, U, LDU, $ WORK( ITAUP ), VT, LDVT, $ WORK( IWORK ), LWORK-IWORK+1, IERR ) * * Generate left bidiagonalizing vectors in U * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'Q', M, M, M, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) IWORK = IE + M * * Perform bidiagonal QR iteration, computing left * singular vectors of A in U and computing right * singular vectors of A in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'U', M, N, M, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), $ INFO ) * END IF * END IF * END IF * ELSE * * N .LT. MNTHR * * Path 10t(N greater than M, but not much larger) * Reduce to bidiagonal form without LQ decomposition * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M IWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( IWORK ), LWORK-IWORK+1, $ IERR ) IF( WNTUAS ) THEN * * If left singular vectors desired in U, copy result to U * and generate left bidiagonalizing vectors in U * (Workspace: need 4*M-1, prefer 3*M+(M-1)*NB) * CALL DLACPY( 'L', M, M, A, LDA, U, LDU ) CALL DORGBR( 'Q', M, M, N, U, LDU, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVAS ) THEN * * If right singular vectors desired in VT, copy result to * VT and generate right bidiagonalizing vectors in VT * (Workspace: need 3*M+NRVT, prefer 3*M+NRVT*NB) * CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) IF( WNTVA ) $ NRVT = N IF( WNTVS ) $ NRVT = M CALL DORGBR( 'P', NRVT, N, M, VT, LDVT, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTUO ) THEN * * If left singular vectors desired in A, generate left * bidiagonalizing vectors in A * (Workspace: need 4*M-1, prefer 3*M+(M-1)*NB) * CALL DORGBR( 'Q', M, M, N, A, LDA, WORK( ITAUQ ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IF( WNTVO ) THEN * * If right singular vectors desired in A, generate right * bidiagonalizing vectors in A * (Workspace: need 4*M, prefer 3*M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( IWORK ), LWORK-IWORK+1, IERR ) END IF IWORK = IE + M IF( WNTUAS .OR. WNTUO ) $ NRU = M IF( WNTUN ) $ NRU = 0 IF( WNTVAS .OR. WNTVO ) $ NCVT = N IF( WNTVN ) $ NCVT = 0 IF( ( .NOT.WNTUO ) .AND. ( .NOT.WNTVO ) ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE IF( ( .NOT.WNTUO ) .AND. WNTVO ) THEN * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in U and computing right singular * vectors in A * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), A, LDA, $ U, LDU, DUM, 1, WORK( IWORK ), INFO ) ELSE * * Perform bidiagonal QR iteration, if desired, computing * left singular vectors in A and computing right singular * vectors in VT * (Workspace: need BDSPAC) * CALL DBDSQR( 'L', M, NCVT, NRU, 0, S, WORK( IE ), VT, $ LDVT, A, LDA, DUM, 1, WORK( IWORK ), INFO ) END IF * END IF * END IF * * If DBDSQR failed to converge, copy unconverged superdiagonals * to WORK( 2:MINMN ) * IF( INFO.NE.0 ) THEN IF( IE.GT.2 ) THEN DO 50 I = 1, MINMN - 1 WORK( I+1 ) = WORK( I+IE-1 ) 50 CONTINUE END IF IF( IE.LT.2 ) THEN DO 60 I = MINMN - 1, 1, -1 WORK( I+1 ) = WORK( I+IE-1 ) 60 CONTINUE END IF END IF * * Undo scaling if necessary * IF( ISCL.EQ.1 ) THEN IF( ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( INFO.NE.0 .AND. ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN-1, 1, WORK( 2 ), $ MINMN, IERR ) IF( ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( INFO.NE.0 .AND. ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN-1, 1, WORK( 2 ), $ MINMN, IERR ) END IF * * Return optimal workspace in WORK(1) * WORK( 1 ) = MAXWRK * RETURN * * End of DGESVD * END SUBROUTINE DHSEQR( JOB, COMPZ, N, ILO, IHI, H, LDH, WR, WI, Z, $ LDZ, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER COMPZ, JOB INTEGER IHI, ILO, INFO, LDH, LDZ, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION H( LDH, * ), WI( * ), WORK( * ), WR( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DHSEQR computes the eigenvalues of a real upper Hessenberg matrix H * and, optionally, the matrices T and Z from the Schur decomposition * H = Z T Z**T, where T is an upper quasi-triangular matrix (the Schur * form), and Z is the orthogonal matrix of Schur vectors. * * Optionally Z may be postmultiplied into an input orthogonal matrix Q, * so that this routine can give the Schur factorization of a matrix A * which has been reduced to the Hessenberg form H by the orthogonal * matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T. * * Arguments * ========= * * JOB (input) CHARACTER*1 * = 'E': compute eigenvalues only; * = 'S': compute eigenvalues and the Schur form T. * * COMPZ (input) CHARACTER*1 * = 'N': no Schur vectors are computed; * = 'I': Z is initialized to the unit matrix and the matrix Z * of Schur vectors of H is returned; * = 'V': Z must contain an orthogonal matrix Q on entry, and * the product Q*Z is returned. * * N (input) INTEGER * The order of the matrix H. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * It is assumed that H is already upper triangular in rows * and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally * set by a previous call to DGEBAL, and then passed to SGEHRD * when the matrix output by DGEBAL is reduced to Hessenberg * form. Otherwise ILO and IHI should be set to 1 and N * respectively. * 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. * * H (input/output) DOUBLE PRECISION array, dimension (LDH,N) * On entry, the upper Hessenberg matrix H. * On exit, if JOB = 'S', H contains the upper quasi-triangular * matrix T from the Schur decomposition (the Schur form); * 2-by-2 diagonal blocks (corresponding to complex conjugate * pairs of eigenvalues) are returned in standard form, with * H(i,i) = H(i+1,i+1) and H(i+1,i)*H(i,i+1) < 0. If JOB = 'E', * the contents of H are unspecified on exit. * * LDH (input) INTEGER * The leading dimension of the array H. LDH >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * The real and imaginary parts, respectively, of the computed * eigenvalues. If two eigenvalues are computed as a complex * conjugate pair, they are stored in consecutive elements of * WR and WI, say the i-th and (i+1)th, with WI(i) > 0 and * WI(i+1) < 0. If JOB = 'S', the eigenvalues are stored in the * same order as on the diagonal of the Schur form returned in * H, with WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 * diagonal block, WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and * WI(i+1) = -WI(i). * * Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N) * If COMPZ = 'N': Z is not referenced. * If COMPZ = 'I': on entry, Z need not be set, and on exit, Z * contains the orthogonal matrix Z of the Schur vectors of H. * If COMPZ = 'V': on entry Z must contain an N-by-N matrix Q, * which is assumed to be equal to the unit matrix except for * the submatrix Z(ILO:IHI,ILO:IHI); on exit Z contains Q*Z. * Normally Q is the orthogonal matrix generated by DORGHR after * the call to DGEHRD which formed the Hessenberg matrix H. * * LDZ (input) INTEGER * The leading dimension of the array Z. * LDZ >= max(1,N) if COMPZ = 'I' or 'V'; LDZ >= 1 otherwise. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, DHSEQR failed to compute all of the * eigenvalues in a total of 30*(IHI-ILO+1) iterations; * elements 1:ilo-1 and i+1:n of WR and WI contain those * eigenvalues which have been successfully computed. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0 ) DOUBLE PRECISION CONST PARAMETER ( CONST = 1.5D+0 ) INTEGER NSMAX, LDS PARAMETER ( NSMAX = 15, LDS = NSMAX ) * .. * .. Local Scalars .. LOGICAL INITZ, LQUERY, WANTT, WANTZ INTEGER I, I1, I2, IERR, II, ITEMP, ITN, ITS, J, K, L, $ MAXB, NH, NR, NS, NV DOUBLE PRECISION ABSW, OVFL, SMLNUM, TAU, TEMP, TST1, ULP, UNFL * .. * .. Local Arrays .. DOUBLE PRECISION S( LDS, NSMAX ), V( NSMAX+1 ), VV( NSMAX+1 ) * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX, ILAENV DOUBLE PRECISION DLAMCH, DLANHS, DLAPY2 EXTERNAL LSAME, IDAMAX, ILAENV, DLAMCH, DLANHS, DLAPY2 * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMV, DLACPY, DLAHQR, DLARFG, DLARFX, $ DLASET, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * * Decode and test the input parameters * WANTT = LSAME( JOB, 'S' ) INITZ = LSAME( COMPZ, 'I' ) WANTZ = INITZ .OR. LSAME( COMPZ, 'V' ) * INFO = 0 WORK( 1 ) = MAX( 1, N ) LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.LSAME( JOB, 'E' ) .AND. .NOT.WANTT ) THEN INFO = -1 ELSE IF( .NOT.LSAME( COMPZ, 'N' ) .AND. .NOT.WANTZ ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( ILO.LT.1 .OR. ILO.GT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( IHI.LT.MIN( ILO, N ) .OR. IHI.GT.N ) THEN INFO = -5 ELSE IF( LDH.LT.MAX( 1, N ) ) THEN INFO = -7 ELSE IF( LDZ.LT.1 .OR. WANTZ .AND. LDZ.LT.MAX( 1, N ) ) THEN INFO = -11 ELSE IF( LWORK.LT.MAX( 1, N ) .AND. .NOT.LQUERY ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DHSEQR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Initialize Z, if necessary * IF( INITZ ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, Z, LDZ ) * * Store the eigenvalues isolated by DGEBAL. * DO 10 I = 1, ILO - 1 WR( I ) = H( I, I ) WI( I ) = ZERO 10 CONTINUE DO 20 I = IHI + 1, N WR( I ) = H( I, I ) WI( I ) = ZERO 20 CONTINUE * * Quick return if possible. * IF( N.EQ.0 ) $ RETURN IF( ILO.EQ.IHI ) THEN WR( ILO ) = H( ILO, ILO ) WI( ILO ) = ZERO RETURN END IF * * Set rows and columns ILO to IHI to zero below the first * subdiagonal. * DO 40 J = ILO, IHI - 2 DO 30 I = J + 2, N H( I, J ) = ZERO 30 CONTINUE 40 CONTINUE NH = IHI - ILO + 1 * * Determine the order of the multi-shift QR algorithm to be used. * NS = ILAENV( 4, 'DHSEQR', JOB // COMPZ, N, ILO, IHI, -1 ) MAXB = ILAENV( 8, 'DHSEQR', JOB // COMPZ, N, ILO, IHI, -1 ) IF( NS.LE.2 .OR. NS.GT.NH .OR. MAXB.GE.NH ) THEN * * Use the standard double-shift algorithm * CALL DLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, ILO, $ IHI, Z, LDZ, INFO ) RETURN END IF MAXB = MAX( 3, MAXB ) NS = MIN( NS, MAXB, NSMAX ) * * Now 2 < NS <= MAXB < NH. * * Set machine-dependent constants for the stopping criterion. * If norm(H) <= sqrt(OVFL), overflow should not occur. * UNFL = DLAMCH( 'Safe minimum' ) OVFL = ONE / UNFL CALL DLABAD( UNFL, OVFL ) ULP = DLAMCH( 'Precision' ) SMLNUM = UNFL*( NH / ULP ) * * I1 and I2 are the indices of the first row and last column of H * to which transformations must be applied. If eigenvalues only are * being computed, I1 and I2 are set inside the main loop. * IF( WANTT ) THEN I1 = 1 I2 = N END IF * * ITN is the total number of multiple-shift QR iterations allowed. * ITN = 30*NH * * The main loop begins here. I is the loop index and decreases from * IHI to ILO in steps of at most MAXB. Each iteration of the loop * works with the active submatrix in rows and columns L to I. * Eigenvalues I+1 to IHI have already converged. Either L = ILO or * H(L,L-1) is negligible so that the matrix splits. * I = IHI 50 CONTINUE L = ILO IF( I.LT.ILO ) $ GO TO 170 * * Perform multiple-shift QR iterations on rows and columns ILO to I * until a submatrix of order at most MAXB splits off at the bottom * because a subdiagonal element has become negligible. * DO 150 ITS = 0, ITN * * Look for a single small subdiagonal element. * DO 60 K = I, L + 1, -1 TST1 = ABS( H( K-1, K-1 ) ) + ABS( H( K, K ) ) IF( TST1.EQ.ZERO ) $ TST1 = DLANHS( '1', I-L+1, H( L, L ), LDH, WORK ) IF( ABS( H( K, K-1 ) ).LE.MAX( ULP*TST1, SMLNUM ) ) $ GO TO 70 60 CONTINUE 70 CONTINUE L = K IF( L.GT.ILO ) THEN * * H(L,L-1) is negligible. * H( L, L-1 ) = ZERO END IF * * Exit from loop if a submatrix of order <= MAXB has split off. * IF( L.GE.I-MAXB+1 ) $ GO TO 160 * * Now the active submatrix is in rows and columns L to I. If * eigenvalues only are being computed, only the active submatrix * need be transformed. * IF( .NOT.WANTT ) THEN I1 = L I2 = I END IF * IF( ITS.EQ.20 .OR. ITS.EQ.30 ) THEN * * Exceptional shifts. * DO 80 II = I - NS + 1, I WR( II ) = CONST*( ABS( H( II, II-1 ) )+ $ ABS( H( II, II ) ) ) WI( II ) = ZERO 80 CONTINUE ELSE * * Use eigenvalues of trailing submatrix of order NS as shifts. * CALL DLACPY( 'Full', NS, NS, H( I-NS+1, I-NS+1 ), LDH, S, $ LDS ) CALL DLAHQR( .FALSE., .FALSE., NS, 1, NS, S, LDS, $ WR( I-NS+1 ), WI( I-NS+1 ), 1, NS, Z, LDZ, $ IERR ) IF( IERR.GT.0 ) THEN * * If DLAHQR failed to compute all NS eigenvalues, use the * unconverged diagonal elements as the remaining shifts. * DO 90 II = 1, IERR WR( I-NS+II ) = S( II, II ) WI( I-NS+II ) = ZERO 90 CONTINUE END IF END IF * * Form the first column of (G-w(1)) (G-w(2)) . . . (G-w(ns)) * where G is the Hessenberg submatrix H(L:I,L:I) and w is * the vector of shifts (stored in WR and WI). The result is * stored in the local array V. * V( 1 ) = ONE DO 100 II = 2, NS + 1 V( II ) = ZERO 100 CONTINUE NV = 1 DO 120 J = I - NS + 1, I IF( WI( J ).GE.ZERO ) THEN IF( WI( J ).EQ.ZERO ) THEN * * real shift * CALL DCOPY( NV+1, V, 1, VV, 1 ) CALL DGEMV( 'No transpose', NV+1, NV, ONE, H( L, L ), $ LDH, VV, 1, -WR( J ), V, 1 ) NV = NV + 1 ELSE IF( WI( J ).GT.ZERO ) THEN * * complex conjugate pair of shifts * CALL DCOPY( NV+1, V, 1, VV, 1 ) CALL DGEMV( 'No transpose', NV+1, NV, ONE, H( L, L ), $ LDH, V, 1, -TWO*WR( J ), VV, 1 ) ITEMP = IDAMAX( NV+1, VV, 1 ) TEMP = ONE / MAX( ABS( VV( ITEMP ) ), SMLNUM ) CALL DSCAL( NV+1, TEMP, VV, 1 ) ABSW = DLAPY2( WR( J ), WI( J ) ) TEMP = ( TEMP*ABSW )*ABSW CALL DGEMV( 'No transpose', NV+2, NV+1, ONE, $ H( L, L ), LDH, VV, 1, TEMP, V, 1 ) NV = NV + 2 END IF * * Scale V(1:NV) so that max(abs(V(i))) = 1. If V is zero, * reset it to the unit vector. * ITEMP = IDAMAX( NV, V, 1 ) TEMP = ABS( V( ITEMP ) ) IF( TEMP.EQ.ZERO ) THEN V( 1 ) = ONE DO 110 II = 2, NV V( II ) = ZERO 110 CONTINUE ELSE TEMP = MAX( TEMP, SMLNUM ) CALL DSCAL( NV, ONE / TEMP, V, 1 ) END IF END IF 120 CONTINUE * * Multiple-shift QR step * DO 140 K = L, I - 1 * * The first iteration of this loop determines a reflection G * from the vector V and applies it from left and right to H, * thus creating a nonzero bulge below the subdiagonal. * * Each subsequent iteration determines a reflection G to * restore the Hessenberg form in the (K-1)th column, and thus * chases the bulge one step toward the bottom of the active * submatrix. NR is the order of G. * NR = MIN( NS+1, I-K+1 ) IF( K.GT.L ) $ CALL DCOPY( NR, H( K, K-1 ), 1, V, 1 ) CALL DLARFG( NR, V( 1 ), V( 2 ), 1, TAU ) IF( K.GT.L ) THEN H( K, K-1 ) = V( 1 ) DO 130 II = K + 1, I H( II, K-1 ) = ZERO 130 CONTINUE END IF V( 1 ) = ONE * * Apply G from the left to transform the rows of the matrix in * columns K to I2. * CALL DLARFX( 'Left', NR, I2-K+1, V, TAU, H( K, K ), LDH, $ WORK ) * * Apply G from the right to transform the columns of the * matrix in rows I1 to min(K+NR,I). * CALL DLARFX( 'Right', MIN( K+NR, I )-I1+1, NR, V, TAU, $ H( I1, K ), LDH, WORK ) * IF( WANTZ ) THEN * * Accumulate transformations in the matrix Z * CALL DLARFX( 'Right', NH, NR, V, TAU, Z( ILO, K ), LDZ, $ WORK ) END IF 140 CONTINUE * 150 CONTINUE * * Failure to converge in remaining number of iterations * INFO = I RETURN * 160 CONTINUE * * A submatrix of order <= MAXB in rows and columns L to I has split * off. Use the double-shift QR algorithm to handle it. * CALL DLAHQR( WANTT, WANTZ, N, L, I, H, LDH, WR, WI, ILO, IHI, Z, $ LDZ, INFO ) IF( INFO.GT.0 ) $ RETURN * * Decrement number of remaining iterations, and return to start of * the main loop with a new value of I. * ITN = ITN - ITS I = L - 1 GO TO 50 * 170 CONTINUE WORK( 1 ) = MAX( 1, N ) RETURN * * End of DHSEQR * END SUBROUTINE DLABAD( SMALL, LARGE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION LARGE, SMALL * .. * * Purpose * ======= * * DLABAD takes as input the values computed by DLAMCH for underflow and * overflow, and returns the square root of each of these values if the * log of LARGE is sufficiently large. This subroutine is intended to * identify machines with a large exponent range, such as the Crays, and * redefine the underflow and overflow limits to be the square roots of * the values computed by DLAMCH. This subroutine is needed because * DLAMCH does not compensate for poor arithmetic in the upper half of * the exponent range, as is found on a Cray. * * Arguments * ========= * * SMALL (input/output) DOUBLE PRECISION * On entry, the underflow threshold as computed by DLAMCH. * On exit, if LOG10(LARGE) is sufficiently large, the square * root of SMALL, otherwise unchanged. * * LARGE (input/output) DOUBLE PRECISION * On entry, the overflow threshold as computed by DLAMCH. * On exit, if LOG10(LARGE) is sufficiently large, the square * root of LARGE, otherwise unchanged. * * ===================================================================== * * .. Intrinsic Functions .. INTRINSIC LOG10, SQRT * .. * .. Executable Statements .. * * If it looks like we're on a Cray, take the square root of * SMALL and LARGE to avoid overflow and underflow problems. * IF( LOG10( LARGE ).GT.2000.D0 ) THEN SMALL = SQRT( SMALL ) LARGE = SQRT( LARGE ) END IF * RETURN * * End of DLABAD * END SUBROUTINE DLABRD( M, N, NB, A, LDA, D, E, TAUQ, TAUP, X, LDX, Y, $ LDY ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER LDA, LDX, LDY, M, N, NB * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAUP( * ), $ TAUQ( * ), X( LDX, * ), Y( LDY, * ) * .. * * Purpose * ======= * * DLABRD reduces the first NB rows and columns of a real general * m by n matrix A to upper or lower bidiagonal form by an orthogonal * transformation Q' * A * P, and returns the matrices X and Y which * are needed to apply the transformation to the unreduced part of A. * * If m >= n, A is reduced to upper bidiagonal form; if m < n, to lower * bidiagonal form. * * This is an auxiliary routine called by DGEBRD * * Arguments * ========= * * M (input) INTEGER * The number of rows in the matrix A. * * N (input) INTEGER * The number of columns in the matrix A. * * NB (input) INTEGER * The number of leading rows and columns of A to be reduced. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the m by n general matrix to be reduced. * On exit, the first NB rows and columns of the matrix are * overwritten; the rest of the array is unchanged. * If m >= n, elements on and below the diagonal in the first NB * columns, with the array TAUQ, represent the orthogonal * matrix Q as a product of elementary reflectors; and * elements above the diagonal in the first NB rows, with the * array TAUP, represent the orthogonal matrix P as a product * of elementary reflectors. * If m < n, elements below the diagonal in the first NB * columns, with the array TAUQ, represent the orthogonal * matrix Q as a product of elementary reflectors, and * elements on and above the diagonal in the first NB rows, * with the array TAUP, represent the orthogonal matrix P as * a product of elementary reflectors. * See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * D (output) DOUBLE PRECISION array, dimension (NB) * The diagonal elements of the first NB rows and columns of * the reduced matrix. D(i) = A(i,i). * * E (output) DOUBLE PRECISION array, dimension (NB) * The off-diagonal elements of the first NB rows and columns of * the reduced matrix. * * TAUQ (output) DOUBLE PRECISION array dimension (NB) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix Q. See Further Details. * * TAUP (output) DOUBLE PRECISION array, dimension (NB) * The scalar factors of the elementary reflectors which * represent the orthogonal matrix P. See Further Details. * * X (output) DOUBLE PRECISION array, dimension (LDX,NB) * The m-by-nb matrix X required to update the unreduced part * of A. * * LDX (input) INTEGER * The leading dimension of the array X. LDX >= M. * * Y (output) DOUBLE PRECISION array, dimension (LDY,NB) * The n-by-nb matrix Y required to update the unreduced part * of A. * * LDY (output) INTEGER * The leading dimension of the array Y. LDY >= N. * * Further Details * =============== * * The matrices Q and P are represented as products of elementary * reflectors: * * Q = H(1) H(2) . . . H(nb) and P = G(1) G(2) . . . G(nb) * * Each H(i) and G(i) has the form: * * H(i) = I - tauq * v * v' and G(i) = I - taup * u * u' * * where tauq and taup are real scalars, and v and u are real vectors. * * If m >= n, v(1:i-1) = 0, v(i) = 1, and v(i:m) is stored on exit in * A(i:m,i); u(1:i) = 0, u(i+1) = 1, and u(i+1:n) is stored on exit in * A(i,i+1:n); tauq is stored in TAUQ(i) and taup in TAUP(i). * * If m < n, v(1:i) = 0, v(i+1) = 1, and v(i+1:m) is stored on exit in * A(i+2:m,i); u(1:i-1) = 0, u(i) = 1, and u(i:n) is stored on exit in * A(i,i+1:n); tauq is stored in TAUQ(i) and taup in TAUP(i). * * The elements of the vectors v and u together form the m-by-nb matrix * V and the nb-by-n matrix U' which are needed, with X and Y, to apply * the transformation to the unreduced part of the matrix, using a block * update of the form: A := A - V*Y' - X*U'. * * The contents of A on exit are illustrated by the following examples * with nb = 2: * * m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n): * * ( 1 1 u1 u1 u1 ) ( 1 u1 u1 u1 u1 u1 ) * ( v1 1 1 u2 u2 ) ( 1 1 u2 u2 u2 u2 ) * ( v1 v2 a a a ) ( v1 1 a a a a ) * ( v1 v2 a a a ) ( v1 v2 a a a a ) * ( v1 v2 a a a ) ( v1 v2 a a a a ) * ( v1 v2 a a a ) * * where a denotes an element of the original matrix which is unchanged, * vi denotes an element of the vector defining H(i), and ui an element * of the vector defining G(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. INTEGER I * .. * .. External Subroutines .. EXTERNAL DGEMV, DLARFG, DSCAL * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * * Quick return if possible * IF( M.LE.0 .OR. N.LE.0 ) $ RETURN * IF( M.GE.N ) THEN * * Reduce to upper bidiagonal form * DO 10 I = 1, NB * * Update A(i:m,i) * CALL DGEMV( 'No transpose', M-I+1, I-1, -ONE, A( I, 1 ), $ LDA, Y( I, 1 ), LDY, ONE, A( I, I ), 1 ) CALL DGEMV( 'No transpose', M-I+1, I-1, -ONE, X( I, 1 ), $ LDX, A( 1, I ), 1, ONE, A( I, I ), 1 ) * * Generate reflection Q(i) to annihilate A(i+1:m,i) * CALL DLARFG( M-I+1, A( I, I ), A( MIN( I+1, M ), I ), 1, $ TAUQ( I ) ) D( I ) = A( I, I ) IF( I.LT.N ) THEN A( I, I ) = ONE * * Compute Y(i+1:n,i) * CALL DGEMV( 'Transpose', M-I+1, N-I, ONE, A( I, I+1 ), $ LDA, A( I, I ), 1, ZERO, Y( I+1, I ), 1 ) CALL DGEMV( 'Transpose', M-I+1, I-1, ONE, A( I, 1 ), LDA, $ A( I, I ), 1, ZERO, Y( 1, I ), 1 ) CALL DGEMV( 'No transpose', N-I, I-1, -ONE, Y( I+1, 1 ), $ LDY, Y( 1, I ), 1, ONE, Y( I+1, I ), 1 ) CALL DGEMV( 'Transpose', M-I+1, I-1, ONE, X( I, 1 ), LDX, $ A( I, I ), 1, ZERO, Y( 1, I ), 1 ) CALL DGEMV( 'Transpose', I-1, N-I, -ONE, A( 1, I+1 ), $ LDA, Y( 1, I ), 1, ONE, Y( I+1, I ), 1 ) CALL DSCAL( N-I, TAUQ( I ), Y( I+1, I ), 1 ) * * Update A(i,i+1:n) * CALL DGEMV( 'No transpose', N-I, I, -ONE, Y( I+1, 1 ), $ LDY, A( I, 1 ), LDA, ONE, A( I, I+1 ), LDA ) CALL DGEMV( 'Transpose', I-1, N-I, -ONE, A( 1, I+1 ), $ LDA, X( I, 1 ), LDX, ONE, A( I, I+1 ), LDA ) * * Generate reflection P(i) to annihilate A(i,i+2:n) * CALL DLARFG( N-I, A( I, I+1 ), A( I, MIN( I+2, N ) ), $ LDA, TAUP( I ) ) E( I ) = A( I, I+1 ) A( I, I+1 ) = ONE * * Compute X(i+1:m,i) * CALL DGEMV( 'No transpose', M-I, N-I, ONE, A( I+1, I+1 ), $ LDA, A( I, I+1 ), LDA, ZERO, X( I+1, I ), 1 ) CALL DGEMV( 'Transpose', N-I, I, ONE, Y( I+1, 1 ), LDY, $ A( I, I+1 ), LDA, ZERO, X( 1, I ), 1 ) CALL DGEMV( 'No transpose', M-I, I, -ONE, A( I+1, 1 ), $ LDA, X( 1, I ), 1, ONE, X( I+1, I ), 1 ) CALL DGEMV( 'No transpose', I-1, N-I, ONE, A( 1, I+1 ), $ LDA, A( I, I+1 ), LDA, ZERO, X( 1, I ), 1 ) CALL DGEMV( 'No transpose', M-I, I-1, -ONE, X( I+1, 1 ), $ LDX, X( 1, I ), 1, ONE, X( I+1, I ), 1 ) CALL DSCAL( M-I, TAUP( I ), X( I+1, I ), 1 ) END IF 10 CONTINUE ELSE * * Reduce to lower bidiagonal form * DO 20 I = 1, NB * * Update A(i,i:n) * CALL DGEMV( 'No transpose', N-I+1, I-1, -ONE, Y( I, 1 ), $ LDY, A( I, 1 ), LDA, ONE, A( I, I ), LDA ) CALL DGEMV( 'Transpose', I-1, N-I+1, -ONE, A( 1, I ), LDA, $ X( I, 1 ), LDX, ONE, A( I, I ), LDA ) * * Generate reflection P(i) to annihilate A(i,i+1:n) * CALL DLARFG( N-I+1, A( I, I ), A( I, MIN( I+1, N ) ), LDA, $ TAUP( I ) ) D( I ) = A( I, I ) IF( I.LT.M ) THEN A( I, I ) = ONE * * Compute X(i+1:m,i) * CALL DGEMV( 'No transpose', M-I, N-I+1, ONE, A( I+1, I ), $ LDA, A( I, I ), LDA, ZERO, X( I+1, I ), 1 ) CALL DGEMV( 'Transpose', N-I+1, I-1, ONE, Y( I, 1 ), LDY, $ A( I, I ), LDA, ZERO, X( 1, I ), 1 ) CALL DGEMV( 'No transpose', M-I, I-1, -ONE, A( I+1, 1 ), $ LDA, X( 1, I ), 1, ONE, X( I+1, I ), 1 ) CALL DGEMV( 'No transpose', I-1, N-I+1, ONE, A( 1, I ), $ LDA, A( I, I ), LDA, ZERO, X( 1, I ), 1 ) CALL DGEMV( 'No transpose', M-I, I-1, -ONE, X( I+1, 1 ), $ LDX, X( 1, I ), 1, ONE, X( I+1, I ), 1 ) CALL DSCAL( M-I, TAUP( I ), X( I+1, I ), 1 ) * * Update A(i+1:m,i) * CALL DGEMV( 'No transpose', M-I, I-1, -ONE, A( I+1, 1 ), $ LDA, Y( I, 1 ), LDY, ONE, A( I+1, I ), 1 ) CALL DGEMV( 'No transpose', M-I, I, -ONE, X( I+1, 1 ), $ LDX, A( 1, I ), 1, ONE, A( I+1, I ), 1 ) * * Generate reflection Q(i) to annihilate A(i+2:m,i) * CALL DLARFG( M-I, A( I+1, I ), A( MIN( I+2, M ), I ), 1, $ TAUQ( I ) ) E( I ) = A( I+1, I ) A( I+1, I ) = ONE * * Compute Y(i+1:n,i) * CALL DGEMV( 'Transpose', M-I, N-I, ONE, A( I+1, I+1 ), $ LDA, A( I+1, I ), 1, ZERO, Y( I+1, I ), 1 ) CALL DGEMV( 'Transpose', M-I, I-1, ONE, A( I+1, 1 ), LDA, $ A( I+1, I ), 1, ZERO, Y( 1, I ), 1 ) CALL DGEMV( 'No transpose', N-I, I-1, -ONE, Y( I+1, 1 ), $ LDY, Y( 1, I ), 1, ONE, Y( I+1, I ), 1 ) CALL DGEMV( 'Transpose', M-I, I, ONE, X( I+1, 1 ), LDX, $ A( I+1, I ), 1, ZERO, Y( 1, I ), 1 ) CALL DGEMV( 'Transpose', I, N-I, -ONE, A( 1, I+1 ), LDA, $ Y( 1, I ), 1, ONE, Y( I+1, I ), 1 ) CALL DSCAL( N-I, TAUQ( I ), Y( I+1, I ), 1 ) END IF 20 CONTINUE END IF RETURN * * End of DLABRD * END SUBROUTINE DLACON( N, V, X, ISGN, EST, KASE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER KASE, N DOUBLE PRECISION EST * .. * .. Array Arguments .. INTEGER ISGN( * ) DOUBLE PRECISION V( * ), X( * ) * .. * * Purpose * ======= * * DLACON estimates the 1-norm of a square, real matrix A. * Reverse communication is used for evaluating matrix-vector products. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. N >= 1. * * V (workspace) DOUBLE PRECISION array, dimension (N) * On the final return, V = A*W, where EST = norm(V)/norm(W) * (W is not returned). * * X (input/output) DOUBLE PRECISION array, dimension (N) * On an intermediate return, X should be overwritten by * A * X, if KASE=1, * A' * X, if KASE=2, * and DLACON must be re-called with all the other parameters * unchanged. * * ISGN (workspace) INTEGER array, dimension (N) * * EST (output) DOUBLE PRECISION * An estimate (a lower bound) for norm(A). * * KASE (input/output) INTEGER * On the initial call to DLACON, KASE should be 0. * On an intermediate return, KASE will be 1 or 2, indicating * whether X should be overwritten by A * X or A' * X. * On the final return from DLACON, KASE will again be 0. * * Further Details * ======= ======= * * Contributed by Nick Higham, University of Manchester. * Originally named SONEST, dated March 16, 1988. * * Reference: N.J. Higham, "FORTRAN codes for estimating the one-norm of * a real or complex matrix, with applications to condition estimation", * ACM Trans. Math. Soft., vol. 14, no. 4, pp. 381-396, December 1988. * * ===================================================================== * * .. Parameters .. INTEGER ITMAX PARAMETER ( ITMAX = 5 ) DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0 ) * .. * .. Local Scalars .. INTEGER I, ITER, J, JLAST, JUMP DOUBLE PRECISION ALTSGN, ESTOLD, TEMP * .. * .. External Functions .. INTEGER IDAMAX DOUBLE PRECISION DASUM EXTERNAL IDAMAX, DASUM * .. * .. External Subroutines .. EXTERNAL DCOPY * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, NINT, SIGN * .. * .. Save statement .. SAVE * .. * .. Executable Statements .. * IF( KASE.EQ.0 ) THEN DO 10 I = 1, N X( I ) = ONE / DBLE( N ) 10 CONTINUE KASE = 1 JUMP = 1 RETURN END IF * GO TO ( 20, 40, 70, 110, 140 )JUMP * * ................ ENTRY (JUMP = 1) * FIRST ITERATION. X HAS BEEN OVERWRITTEN BY A*X. * 20 CONTINUE IF( N.EQ.1 ) THEN V( 1 ) = X( 1 ) EST = ABS( V( 1 ) ) * ... QUIT GO TO 150 END IF EST = DASUM( N, X, 1 ) * DO 30 I = 1, N X( I ) = SIGN( ONE, X( I ) ) ISGN( I ) = NINT( X( I ) ) 30 CONTINUE KASE = 2 JUMP = 2 RETURN * * ................ ENTRY (JUMP = 2) * FIRST ITERATION. X HAS BEEN OVERWRITTEN BY TRANDPOSE(A)*X. * 40 CONTINUE J = IDAMAX( N, X, 1 ) ITER = 2 * * MAIN LOOP - ITERATIONS 2,3,...,ITMAX. * 50 CONTINUE DO 60 I = 1, N X( I ) = ZERO 60 CONTINUE X( J ) = ONE KASE = 1 JUMP = 3 RETURN * * ................ ENTRY (JUMP = 3) * X HAS BEEN OVERWRITTEN BY A*X. * 70 CONTINUE CALL DCOPY( N, X, 1, V, 1 ) ESTOLD = EST EST = DASUM( N, V, 1 ) DO 80 I = 1, N IF( NINT( SIGN( ONE, X( I ) ) ).NE.ISGN( I ) ) $ GO TO 90 80 CONTINUE * REPEATED SIGN VECTOR DETECTED, HENCE ALGORITHM HAS CONVERGED. GO TO 120 * 90 CONTINUE * TEST FOR CYCLING. IF( EST.LE.ESTOLD ) $ GO TO 120 * DO 100 I = 1, N X( I ) = SIGN( ONE, X( I ) ) ISGN( I ) = NINT( X( I ) ) 100 CONTINUE KASE = 2 JUMP = 4 RETURN * * ................ ENTRY (JUMP = 4) * X HAS BEEN OVERWRITTEN BY TRANDPOSE(A)*X. * 110 CONTINUE JLAST = J J = IDAMAX( N, X, 1 ) IF( ( X( JLAST ).NE.ABS( X( J ) ) ) .AND. ( ITER.LT.ITMAX ) ) THEN ITER = ITER + 1 GO TO 50 END IF * * ITERATION COMPLETE. FINAL STAGE. * 120 CONTINUE ALTSGN = ONE DO 130 I = 1, N X( I ) = ALTSGN*( ONE+DBLE( I-1 ) / DBLE( N-1 ) ) ALTSGN = -ALTSGN 130 CONTINUE KASE = 1 JUMP = 5 RETURN * * ................ ENTRY (JUMP = 5) * X HAS BEEN OVERWRITTEN BY A*X. * 140 CONTINUE TEMP = TWO*( DASUM( N, X, 1 ) / DBLE( 3*N ) ) IF( TEMP.GT.EST ) THEN CALL DCOPY( N, X, 1, V, 1 ) EST = TEMP END IF * 150 CONTINUE KASE = 0 RETURN * * End of DLACON * END SUBROUTINE DLACPY( UPLO, M, N, A, LDA, B, LDB ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER LDA, LDB, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ) * .. * * Purpose * ======= * * DLACPY copies all or part of a two-dimensional matrix A to another * matrix B. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * Specifies the part of the matrix A to be copied to B. * = 'U': Upper triangular part * = 'L': Lower triangular part * Otherwise: All of the matrix A * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The m by n matrix A. If UPLO = 'U', only the upper triangle * or trapezoid is accessed; if UPLO = 'L', only the lower * triangle or trapezoid is accessed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (output) DOUBLE PRECISION array, dimension (LDB,N) * On exit, B = A in the locations specified by UPLO. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,M). * * ===================================================================== * * .. Local Scalars .. INTEGER I, J * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * IF( LSAME( UPLO, 'U' ) ) THEN DO 20 J = 1, N DO 10 I = 1, MIN( J, M ) B( I, J ) = A( I, J ) 10 CONTINUE 20 CONTINUE ELSE IF( LSAME( UPLO, 'L' ) ) THEN DO 40 J = 1, N DO 30 I = J, M B( I, J ) = A( I, J ) 30 CONTINUE 40 CONTINUE ELSE DO 60 J = 1, N DO 50 I = 1, M B( I, J ) = A( I, J ) 50 CONTINUE 60 CONTINUE END IF RETURN * * End of DLACPY * END SUBROUTINE DLADIV( A, B, C, D, P, Q ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION A, B, C, D, P, Q * .. * * Purpose * ======= * * DLADIV performs complex division in real arithmetic * * a + i*b * p + i*q = --------- * c + i*d * * The algorithm is due to Robert L. Smith and can be found * in D. Knuth, The art of Computer Programming, Vol.2, p.195 * * Arguments * ========= * * A (input) DOUBLE PRECISION * B (input) DOUBLE PRECISION * C (input) DOUBLE PRECISION * D (input) DOUBLE PRECISION * The scalars a, b, c, and d in the above expression. * * P (output) DOUBLE PRECISION * Q (output) DOUBLE PRECISION * The scalars p and q in the above expression. * * ===================================================================== * * .. Local Scalars .. DOUBLE PRECISION E, F * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * IF( ABS( D ).LT.ABS( C ) ) THEN E = D / C F = C + D*E P = ( A+B*E ) / F Q = ( B-A*E ) / F ELSE E = C / D F = D + C*E P = ( B+A*E ) / F Q = ( -A+B*E ) / F END IF * RETURN * * End of DLADIV * END SUBROUTINE DLAE2( A, B, C, RT1, RT2 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION A, B, C, RT1, RT2 * .. * * Purpose * ======= * * DLAE2 computes the eigenvalues of a 2-by-2 symmetric matrix * [ A B ] * [ B C ]. * On return, RT1 is the eigenvalue of larger absolute value, and RT2 * is the eigenvalue of smaller absolute value. * * Arguments * ========= * * A (input) DOUBLE PRECISION * The (1,1) element of the 2-by-2 matrix. * * B (input) DOUBLE PRECISION * The (1,2) and (2,1) elements of the 2-by-2 matrix. * * C (input) DOUBLE PRECISION * The (2,2) element of the 2-by-2 matrix. * * RT1 (output) DOUBLE PRECISION * The eigenvalue of larger absolute value. * * RT2 (output) DOUBLE PRECISION * The eigenvalue of smaller absolute value. * * Further Details * =============== * * RT1 is accurate to a few ulps barring over/underflow. * * RT2 may be inaccurate if there is massive cancellation in the * determinant A*C-B*B; higher precision or correctly rounded or * correctly truncated arithmetic would be needed to compute RT2 * accurately in all cases. * * Overflow is possible only if RT1 is within a factor of 5 of overflow. * Underflow is harmless if the input data is 0 or exceeds * underflow_threshold / macheps. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION HALF PARAMETER ( HALF = 0.5D0 ) * .. * .. Local Scalars .. DOUBLE PRECISION AB, ACMN, ACMX, ADF, DF, RT, SM, TB * .. * .. Intrinsic Functions .. INTRINSIC ABS, SQRT * .. * .. Executable Statements .. * * Compute the eigenvalues * SM = A + C DF = A - C ADF = ABS( DF ) TB = B + B AB = ABS( TB ) IF( ABS( A ).GT.ABS( C ) ) THEN ACMX = A ACMN = C ELSE ACMX = C ACMN = A END IF IF( ADF.GT.AB ) THEN RT = ADF*SQRT( ONE+( AB / ADF )**2 ) ELSE IF( ADF.LT.AB ) THEN RT = AB*SQRT( ONE+( ADF / AB )**2 ) ELSE * * Includes case AB=ADF=0 * RT = AB*SQRT( TWO ) END IF IF( SM.LT.ZERO ) THEN RT1 = HALF*( SM-RT ) * * Order of execution important. * To get fully accurate smaller eigenvalue, * next line needs to be executed in higher precision. * RT2 = ( ACMX / RT1 )*ACMN - ( B / RT1 )*B ELSE IF( SM.GT.ZERO ) THEN RT1 = HALF*( SM+RT ) * * Order of execution important. * To get fully accurate smaller eigenvalue, * next line needs to be executed in higher precision. * RT2 = ( ACMX / RT1 )*ACMN - ( B / RT1 )*B ELSE * * Includes case RT1 = RT2 = 0 * RT1 = HALF*RT RT2 = -HALF*RT END IF RETURN * * End of DLAE2 * END SUBROUTINE DLAEV2( A, B, C, RT1, RT2, CS1, SN1 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION A, B, C, CS1, RT1, RT2, SN1 * .. * * Purpose * ======= * * DLAEV2 computes the eigendecomposition of a 2-by-2 symmetric matrix * [ A B ] * [ B C ]. * On return, RT1 is the eigenvalue of larger absolute value, RT2 is the * eigenvalue of smaller absolute value, and (CS1,SN1) is the unit right * eigenvector for RT1, giving the decomposition * * [ CS1 SN1 ] [ A B ] [ CS1 -SN1 ] = [ RT1 0 ] * [-SN1 CS1 ] [ B C ] [ SN1 CS1 ] [ 0 RT2 ]. * * Arguments * ========= * * A (input) DOUBLE PRECISION * The (1,1) element of the 2-by-2 matrix. * * B (input) DOUBLE PRECISION * The (1,2) element and the conjugate of the (2,1) element of * the 2-by-2 matrix. * * C (input) DOUBLE PRECISION * The (2,2) element of the 2-by-2 matrix. * * RT1 (output) DOUBLE PRECISION * The eigenvalue of larger absolute value. * * RT2 (output) DOUBLE PRECISION * The eigenvalue of smaller absolute value. * * CS1 (output) DOUBLE PRECISION * SN1 (output) DOUBLE PRECISION * The vector (CS1, SN1) is a unit right eigenvector for RT1. * * Further Details * =============== * * RT1 is accurate to a few ulps barring over/underflow. * * RT2 may be inaccurate if there is massive cancellation in the * determinant A*C-B*B; higher precision or correctly rounded or * correctly truncated arithmetic would be needed to compute RT2 * accurately in all cases. * * CS1 and SN1 are accurate to a few ulps barring over/underflow. * * Overflow is possible only if RT1 is within a factor of 5 of overflow. * Underflow is harmless if the input data is 0 or exceeds * underflow_threshold / macheps. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION HALF PARAMETER ( HALF = 0.5D0 ) * .. * .. Local Scalars .. INTEGER SGN1, SGN2 DOUBLE PRECISION AB, ACMN, ACMX, ACS, ADF, CS, CT, DF, RT, SM, $ TB, TN * .. * .. Intrinsic Functions .. INTRINSIC ABS, SQRT * .. * .. Executable Statements .. * * Compute the eigenvalues * SM = A + C DF = A - C ADF = ABS( DF ) TB = B + B AB = ABS( TB ) IF( ABS( A ).GT.ABS( C ) ) THEN ACMX = A ACMN = C ELSE ACMX = C ACMN = A END IF IF( ADF.GT.AB ) THEN RT = ADF*SQRT( ONE+( AB / ADF )**2 ) ELSE IF( ADF.LT.AB ) THEN RT = AB*SQRT( ONE+( ADF / AB )**2 ) ELSE * * Includes case AB=ADF=0 * RT = AB*SQRT( TWO ) END IF IF( SM.LT.ZERO ) THEN RT1 = HALF*( SM-RT ) SGN1 = -1 * * Order of execution important. * To get fully accurate smaller eigenvalue, * next line needs to be executed in higher precision. * RT2 = ( ACMX / RT1 )*ACMN - ( B / RT1 )*B ELSE IF( SM.GT.ZERO ) THEN RT1 = HALF*( SM+RT ) SGN1 = 1 * * Order of execution important. * To get fully accurate smaller eigenvalue, * next line needs to be executed in higher precision. * RT2 = ( ACMX / RT1 )*ACMN - ( B / RT1 )*B ELSE * * Includes case RT1 = RT2 = 0 * RT1 = HALF*RT RT2 = -HALF*RT SGN1 = 1 END IF * * Compute the eigenvector * IF( DF.GE.ZERO ) THEN CS = DF + RT SGN2 = 1 ELSE CS = DF - RT SGN2 = -1 END IF ACS = ABS( CS ) IF( ACS.GT.AB ) THEN CT = -TB / CS SN1 = ONE / SQRT( ONE+CT*CT ) CS1 = CT*SN1 ELSE IF( AB.EQ.ZERO ) THEN CS1 = ONE SN1 = ZERO ELSE TN = -CS / TB CS1 = ONE / SQRT( ONE+TN*TN ) SN1 = TN*CS1 END IF END IF IF( SGN1.EQ.SGN2 ) THEN TN = CS1 CS1 = -SN1 SN1 = TN END IF RETURN * * End of DLAEV2 * END SUBROUTINE DLAEXC( WANTQ, N, T, LDT, Q, LDQ, J1, N1, N2, WORK, $ INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. LOGICAL WANTQ INTEGER INFO, J1, LDQ, LDT, N, N1, N2 * .. * .. Array Arguments .. DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WORK( * ) * .. * * Purpose * ======= * * DLAEXC swaps adjacent diagonal blocks T11 and T22 of order 1 or 2 in * an upper quasi-triangular matrix T by an orthogonal similarity * transformation. * * T must be in Schur canonical form, that is, block upper triangular * with 1-by-1 and 2-by-2 diagonal blocks; each 2-by-2 diagonal block * has its diagonal elemnts equal and its off-diagonal elements of * opposite sign. * * Arguments * ========= * * WANTQ (input) LOGICAL * = .TRUE. : accumulate the transformation in the matrix Q; * = .FALSE.: do not accumulate the transformation. * * N (input) INTEGER * The order of the matrix T. N >= 0. * * T (input/output) DOUBLE PRECISION array, dimension (LDT,N) * On entry, the upper quasi-triangular matrix T, in Schur * canonical form. * On exit, the updated matrix T, again in Schur canonical form. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= max(1,N). * * Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N) * On entry, if WANTQ is .TRUE., the orthogonal matrix Q. * On exit, if WANTQ is .TRUE., the updated matrix Q. * If WANTQ is .FALSE., Q is not referenced. * * LDQ (input) INTEGER * The leading dimension of the array Q. * LDQ >= 1; and if WANTQ is .TRUE., LDQ >= N. * * J1 (input) INTEGER * The index of the first row of the first block T11. * * N1 (input) INTEGER * The order of the first block T11. N1 = 0, 1 or 2. * * N2 (input) INTEGER * The order of the second block T22. N2 = 0, 1 or 2. * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * = 1: the transformed matrix T would be too far from Schur * form; the blocks are not swapped and T and Q are * unchanged. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) DOUBLE PRECISION TEN PARAMETER ( TEN = 1.0D+1 ) INTEGER LDD, LDX PARAMETER ( LDD = 4, LDX = 2 ) * .. * .. Local Scalars .. INTEGER IERR, J2, J3, J4, K, ND DOUBLE PRECISION CS, DNORM, EPS, SCALE, SMLNUM, SN, T11, T22, $ T33, TAU, TAU1, TAU2, TEMP, THRESH, WI1, WI2, $ WR1, WR2, XNORM * .. * .. Local Arrays .. DOUBLE PRECISION D( LDD, 4 ), U( 3 ), U1( 3 ), U2( 3 ), $ X( LDX, 2 ) * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DLACPY, DLANV2, DLARFG, DLARFX, DLARTG, DLASY2, $ DROT * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * INFO = 0 * * Quick return if possible * IF( N.EQ.0 .OR. N1.EQ.0 .OR. N2.EQ.0 ) $ RETURN IF( J1+N1.GT.N ) $ RETURN * J2 = J1 + 1 J3 = J1 + 2 J4 = J1 + 3 * IF( N1.EQ.1 .AND. N2.EQ.1 ) THEN * * Swap two 1-by-1 blocks. * T11 = T( J1, J1 ) T22 = T( J2, J2 ) * * Determine the transformation to perform the interchange. * CALL DLARTG( T( J1, J2 ), T22-T11, CS, SN, TEMP ) * * Apply transformation to the matrix T. * IF( J3.LE.N ) $ CALL DROT( N-J1-1, T( J1, J3 ), LDT, T( J2, J3 ), LDT, CS, $ SN ) CALL DROT( J1-1, T( 1, J1 ), 1, T( 1, J2 ), 1, CS, SN ) * T( J1, J1 ) = T22 T( J2, J2 ) = T11 * IF( WANTQ ) THEN * * Accumulate transformation in the matrix Q. * CALL DROT( N, Q( 1, J1 ), 1, Q( 1, J2 ), 1, CS, SN ) END IF * ELSE * * Swapping involves at least one 2-by-2 block. * * Copy the diagonal block of order N1+N2 to the local array D * and compute its norm. * ND = N1 + N2 CALL DLACPY( 'Full', ND, ND, T( J1, J1 ), LDT, D, LDD ) DNORM = DLANGE( 'Max', ND, ND, D, LDD, WORK ) * * Compute machine-dependent threshold for test for accepting * swap. * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) / EPS THRESH = MAX( TEN*EPS*DNORM, SMLNUM ) * * Solve T11*X - X*T22 = scale*T12 for X. * CALL DLASY2( .FALSE., .FALSE., -1, N1, N2, D, LDD, $ D( N1+1, N1+1 ), LDD, D( 1, N1+1 ), LDD, SCALE, X, $ LDX, XNORM, IERR ) * * Swap the adjacent diagonal blocks. * K = N1 + N1 + N2 - 3 GO TO ( 10, 20, 30 )K * 10 CONTINUE * * N1 = 1, N2 = 2: generate elementary reflector H so that: * * ( scale, X11, X12 ) H = ( 0, 0, * ) * U( 1 ) = SCALE U( 2 ) = X( 1, 1 ) U( 3 ) = X( 1, 2 ) CALL DLARFG( 3, U( 3 ), U, 1, TAU ) U( 3 ) = ONE T11 = T( J1, J1 ) * * Perform swap provisionally on diagonal block in D. * CALL DLARFX( 'L', 3, 3, U, TAU, D, LDD, WORK ) CALL DLARFX( 'R', 3, 3, U, TAU, D, LDD, WORK ) * * Test whether to reject swap. * IF( MAX( ABS( D( 3, 1 ) ), ABS( D( 3, 2 ) ), ABS( D( 3, $ 3 )-T11 ) ).GT.THRESH )GO TO 50 * * Accept swap: apply transformation to the entire matrix T. * CALL DLARFX( 'L', 3, N-J1+1, U, TAU, T( J1, J1 ), LDT, WORK ) CALL DLARFX( 'R', J2, 3, U, TAU, T( 1, J1 ), LDT, WORK ) * T( J3, J1 ) = ZERO T( J3, J2 ) = ZERO T( J3, J3 ) = T11 * IF( WANTQ ) THEN * * Accumulate transformation in the matrix Q. * CALL DLARFX( 'R', N, 3, U, TAU, Q( 1, J1 ), LDQ, WORK ) END IF GO TO 40 * 20 CONTINUE * * N1 = 2, N2 = 1: generate elementary reflector H so that: * * H ( -X11 ) = ( * ) * ( -X21 ) = ( 0 ) * ( scale ) = ( 0 ) * U( 1 ) = -X( 1, 1 ) U( 2 ) = -X( 2, 1 ) U( 3 ) = SCALE CALL DLARFG( 3, U( 1 ), U( 2 ), 1, TAU ) U( 1 ) = ONE T33 = T( J3, J3 ) * * Perform swap provisionally on diagonal block in D. * CALL DLARFX( 'L', 3, 3, U, TAU, D, LDD, WORK ) CALL DLARFX( 'R', 3, 3, U, TAU, D, LDD, WORK ) * * Test whether to reject swap. * IF( MAX( ABS( D( 2, 1 ) ), ABS( D( 3, 1 ) ), ABS( D( 1, $ 1 )-T33 ) ).GT.THRESH )GO TO 50 * * Accept swap: apply transformation to the entire matrix T. * CALL DLARFX( 'R', J3, 3, U, TAU, T( 1, J1 ), LDT, WORK ) CALL DLARFX( 'L', 3, N-J1, U, TAU, T( J1, J2 ), LDT, WORK ) * T( J1, J1 ) = T33 T( J2, J1 ) = ZERO T( J3, J1 ) = ZERO * IF( WANTQ ) THEN * * Accumulate transformation in the matrix Q. * CALL DLARFX( 'R', N, 3, U, TAU, Q( 1, J1 ), LDQ, WORK ) END IF GO TO 40 * 30 CONTINUE * * N1 = 2, N2 = 2: generate elementary reflectors H(1) and H(2) so * that: * * H(2) H(1) ( -X11 -X12 ) = ( * * ) * ( -X21 -X22 ) ( 0 * ) * ( scale 0 ) ( 0 0 ) * ( 0 scale ) ( 0 0 ) * U1( 1 ) = -X( 1, 1 ) U1( 2 ) = -X( 2, 1 ) U1( 3 ) = SCALE CALL DLARFG( 3, U1( 1 ), U1( 2 ), 1, TAU1 ) U1( 1 ) = ONE * TEMP = -TAU1*( X( 1, 2 )+U1( 2 )*X( 2, 2 ) ) U2( 1 ) = -TEMP*U1( 2 ) - X( 2, 2 ) U2( 2 ) = -TEMP*U1( 3 ) U2( 3 ) = SCALE CALL DLARFG( 3, U2( 1 ), U2( 2 ), 1, TAU2 ) U2( 1 ) = ONE * * Perform swap provisionally on diagonal block in D. * CALL DLARFX( 'L', 3, 4, U1, TAU1, D, LDD, WORK ) CALL DLARFX( 'R', 4, 3, U1, TAU1, D, LDD, WORK ) CALL DLARFX( 'L', 3, 4, U2, TAU2, D( 2, 1 ), LDD, WORK ) CALL DLARFX( 'R', 4, 3, U2, TAU2, D( 1, 2 ), LDD, WORK ) * * Test whether to reject swap. * IF( MAX( ABS( D( 3, 1 ) ), ABS( D( 3, 2 ) ), ABS( D( 4, 1 ) ), $ ABS( D( 4, 2 ) ) ).GT.THRESH )GO TO 50 * * Accept swap: apply transformation to the entire matrix T. * CALL DLARFX( 'L', 3, N-J1+1, U1, TAU1, T( J1, J1 ), LDT, WORK ) CALL DLARFX( 'R', J4, 3, U1, TAU1, T( 1, J1 ), LDT, WORK ) CALL DLARFX( 'L', 3, N-J1+1, U2, TAU2, T( J2, J1 ), LDT, WORK ) CALL DLARFX( 'R', J4, 3, U2, TAU2, T( 1, J2 ), LDT, WORK ) * T( J3, J1 ) = ZERO T( J3, J2 ) = ZERO T( J4, J1 ) = ZERO T( J4, J2 ) = ZERO * IF( WANTQ ) THEN * * Accumulate transformation in the matrix Q. * CALL DLARFX( 'R', N, 3, U1, TAU1, Q( 1, J1 ), LDQ, WORK ) CALL DLARFX( 'R', N, 3, U2, TAU2, Q( 1, J2 ), LDQ, WORK ) END IF * 40 CONTINUE * IF( N2.EQ.2 ) THEN * * Standardize new 2-by-2 block T11 * CALL DLANV2( T( J1, J1 ), T( J1, J2 ), T( J2, J1 ), $ T( J2, J2 ), WR1, WI1, WR2, WI2, CS, SN ) CALL DROT( N-J1-1, T( J1, J1+2 ), LDT, T( J2, J1+2 ), LDT, $ CS, SN ) CALL DROT( J1-1, T( 1, J1 ), 1, T( 1, J2 ), 1, CS, SN ) IF( WANTQ ) $ CALL DROT( N, Q( 1, J1 ), 1, Q( 1, J2 ), 1, CS, SN ) END IF * IF( N1.EQ.2 ) THEN * * Standardize new 2-by-2 block T22 * J3 = J1 + N2 J4 = J3 + 1 CALL DLANV2( T( J3, J3 ), T( J3, J4 ), T( J4, J3 ), $ T( J4, J4 ), WR1, WI1, WR2, WI2, CS, SN ) IF( J3+2.LE.N ) $ CALL DROT( N-J3-1, T( J3, J3+2 ), LDT, T( J4, J3+2 ), $ LDT, CS, SN ) CALL DROT( J3-1, T( 1, J3 ), 1, T( 1, J4 ), 1, CS, SN ) IF( WANTQ ) $ CALL DROT( N, Q( 1, J3 ), 1, Q( 1, J4 ), 1, CS, SN ) END IF * END IF RETURN * * Exit with INFO = 1 if swap was rejected. * 50 CONTINUE INFO = 1 RETURN * * End of DLAEXC * END SUBROUTINE DLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, $ ILOZ, IHIZ, Z, LDZ, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. LOGICAL WANTT, WANTZ INTEGER IHI, IHIZ, ILO, ILOZ, INFO, LDH, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION H( LDH, * ), WI( * ), WR( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DLAHQR is an auxiliary routine called by DHSEQR to update the * eigenvalues and Schur decomposition already computed by DHSEQR, by * dealing with the Hessenberg submatrix in rows and columns ILO to IHI. * * Arguments * ========= * * WANTT (input) LOGICAL * = .TRUE. : the full Schur form T is required; * = .FALSE.: only eigenvalues are required. * * WANTZ (input) LOGICAL * = .TRUE. : the matrix of Schur vectors Z is required; * = .FALSE.: Schur vectors are not required. * * N (input) INTEGER * The order of the matrix H. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * It is assumed that H is already upper quasi-triangular in * rows and columns IHI+1:N, and that H(ILO,ILO-1) = 0 (unless * ILO = 1). DLAHQR works primarily with the Hessenberg * submatrix in rows and columns ILO to IHI, but applies * transformations to all of H if WANTT is .TRUE.. * 1 <= ILO <= max(1,IHI); IHI <= N. * * H (input/output) DOUBLE PRECISION array, dimension (LDH,N) * On entry, the upper Hessenberg matrix H. * On exit, if WANTT is .TRUE., H is upper quasi-triangular in * rows and columns ILO:IHI, with any 2-by-2 diagonal blocks in * standard form. If WANTT is .FALSE., the contents of H are * unspecified on exit. * * LDH (input) INTEGER * The leading dimension of the array H. LDH >= max(1,N). * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * The real and imaginary parts, respectively, of the computed * eigenvalues ILO to IHI are stored in the corresponding * elements of WR and WI. If two eigenvalues are computed as a * complex conjugate pair, they are stored in consecutive * elements of WR and WI, say the i-th and (i+1)th, with * WI(i) > 0 and WI(i+1) < 0. If WANTT is .TRUE., the * eigenvalues are stored in the same order as on the diagonal * of the Schur form returned in H, with WR(i) = H(i,i), and, if * H(i:i+1,i:i+1) is a 2-by-2 diagonal block, * WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and WI(i+1) = -WI(i). * * ILOZ (input) INTEGER * IHIZ (input) INTEGER * Specify the rows of Z to which transformations must be * applied if WANTZ is .TRUE.. * 1 <= ILOZ <= ILO; IHI <= IHIZ <= N. * * Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N) * If WANTZ is .TRUE., on entry Z must contain the current * matrix Z of transformations accumulated by DHSEQR, and on * exit Z has been updated; transformations are applied only to * the submatrix Z(ILOZ:IHIZ,ILO:IHI). * If WANTZ is .FALSE., Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= max(1,N). * * INFO (output) INTEGER * = 0: successful exit * > 0: DLAHQR failed to compute all the eigenvalues ILO to IHI * in a total of 30*(IHI-ILO+1) iterations; if INFO = i, * elements i+1:ihi of WR and WI contain those eigenvalues * which have been successfully computed. * * Further Details * =============== * * 2-96 Based on modifications by * David Day, Sandia National Laboratory, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, HALF PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, HALF = 0.5D0 ) DOUBLE PRECISION DAT1, DAT2 PARAMETER ( DAT1 = 0.75D+0, DAT2 = -0.4375D+0 ) * .. * .. Local Scalars .. INTEGER I, I1, I2, ITN, ITS, J, K, L, M, NH, NR, NZ DOUBLE PRECISION AVE, CS, DISC, H00, H10, H11, H12, H21, H22, $ H33, H33S, H43H34, H44, H44S, OVFL, S, SMLNUM, $ SN, SUM, T1, T2, T3, TST1, ULP, UNFL, V1, V2, $ V3 * .. * .. Local Arrays .. DOUBLE PRECISION V( 3 ), WORK( 1 ) * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLANHS EXTERNAL DLAMCH, DLANHS * .. * .. External Subroutines .. EXTERNAL DCOPY, DLANV2, DLARFG, DROT * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SIGN, SQRT * .. * .. Executable Statements .. * INFO = 0 * * Quick return if possible * IF( N.EQ.0 ) $ RETURN IF( ILO.EQ.IHI ) THEN WR( ILO ) = H( ILO, ILO ) WI( ILO ) = ZERO RETURN END IF * NH = IHI - ILO + 1 NZ = IHIZ - ILOZ + 1 * * Set machine-dependent constants for the stopping criterion. * If norm(H) <= sqrt(OVFL), overflow should not occur. * UNFL = DLAMCH( 'Safe minimum' ) OVFL = ONE / UNFL CALL DLABAD( UNFL, OVFL ) ULP = DLAMCH( 'Precision' ) SMLNUM = UNFL*( NH / ULP ) * * I1 and I2 are the indices of the first row and last column of H * to which transformations must be applied. If eigenvalues only are * being computed, I1 and I2 are set inside the main loop. * IF( WANTT ) THEN I1 = 1 I2 = N END IF * * ITN is the total number of QR iterations allowed. * ITN = 30*NH * * The main loop begins here. I is the loop index and decreases from * IHI to ILO in steps of 1 or 2. Each iteration of the loop works * with the active submatrix in rows and columns L to I. * Eigenvalues I+1 to IHI have already converged. Either L = ILO or * H(L,L-1) is negligible so that the matrix splits. * I = IHI 10 CONTINUE L = ILO IF( I.LT.ILO ) $ GO TO 150 * * Perform QR iterations on rows and columns ILO to I until a * submatrix of order 1 or 2 splits off at the bottom because a * subdiagonal element has become negligible. * DO 130 ITS = 0, ITN * * Look for a single small subdiagonal element. * DO 20 K = I, L + 1, -1 TST1 = ABS( H( K-1, K-1 ) ) + ABS( H( K, K ) ) IF( TST1.EQ.ZERO ) $ TST1 = DLANHS( '1', I-L+1, H( L, L ), LDH, WORK ) IF( ABS( H( K, K-1 ) ).LE.MAX( ULP*TST1, SMLNUM ) ) $ GO TO 30 20 CONTINUE 30 CONTINUE L = K IF( L.GT.ILO ) THEN * * H(L,L-1) is negligible * H( L, L-1 ) = ZERO END IF * * Exit from loop if a submatrix of order 1 or 2 has split off. * IF( L.GE.I-1 ) $ GO TO 140 * * Now the active submatrix is in rows and columns L to I. If * eigenvalues only are being computed, only the active submatrix * need be transformed. * IF( .NOT.WANTT ) THEN I1 = L I2 = I END IF * IF( ITS.EQ.10 .OR. ITS.EQ.20 ) THEN * * Exceptional shift. * S = ABS( H( I, I-1 ) ) + ABS( H( I-1, I-2 ) ) H44 = DAT1*S + H( I, I ) H33 = H44 H43H34 = DAT2*S*S ELSE * * Prepare to use Francis' double shift * (i.e. 2nd degree generalized Rayleigh quotient) * H44 = H( I, I ) H33 = H( I-1, I-1 ) H43H34 = H( I, I-1 )*H( I-1, I ) S = H( I-1, I-2 )*H( I-1, I-2 ) DISC = ( H33-H44 )*HALF DISC = DISC*DISC + H43H34 IF( DISC.GT.ZERO ) THEN * * Real roots: use Wilkinson's shift twice * DISC = SQRT( DISC ) AVE = HALF*( H33+H44 ) IF( ABS( H33 )-ABS( H44 ).GT.ZERO ) THEN H33 = H33*H44 - H43H34 H44 = H33 / ( SIGN( DISC, AVE )+AVE ) ELSE H44 = SIGN( DISC, AVE ) + AVE END IF H33 = H44 H43H34 = ZERO END IF END IF * * Look for two consecutive small subdiagonal elements. * DO 40 M = I - 2, L, -1 * Determine the effect of starting the double-shift QR * iteration at row M, and see if this would make H(M,M-1) * negligible. * H11 = H( M, M ) H22 = H( M+1, M+1 ) H21 = H( M+1, M ) H12 = H( M, M+1 ) H44S = H44 - H11 H33S = H33 - H11 V1 = ( H33S*H44S-H43H34 ) / H21 + H12 V2 = H22 - H11 - H33S - H44S V3 = H( M+2, M+1 ) S = ABS( V1 ) + ABS( V2 ) + ABS( V3 ) V1 = V1 / S V2 = V2 / S V3 = V3 / S V( 1 ) = V1 V( 2 ) = V2 V( 3 ) = V3 IF( M.EQ.L ) $ GO TO 50 H00 = H( M-1, M-1 ) H10 = H( M, M-1 ) TST1 = ABS( V1 )*( ABS( H00 )+ABS( H11 )+ABS( H22 ) ) IF( ABS( H10 )*( ABS( V2 )+ABS( V3 ) ).LE.ULP*TST1 ) $ GO TO 50 40 CONTINUE 50 CONTINUE * * Double-shift QR step * DO 120 K = M, I - 1 * * The first iteration of this loop determines a reflection G * from the vector V and applies it from left and right to H, * thus creating a nonzero bulge below the subdiagonal. * * Each subsequent iteration determines a reflection G to * restore the Hessenberg form in the (K-1)th column, and thus * chases the bulge one step toward the bottom of the active * submatrix. NR is the order of G. * NR = MIN( 3, I-K+1 ) IF( K.GT.M ) $ CALL DCOPY( NR, H( K, K-1 ), 1, V, 1 ) CALL DLARFG( NR, V( 1 ), V( 2 ), 1, T1 ) IF( K.GT.M ) THEN H( K, K-1 ) = V( 1 ) H( K+1, K-1 ) = ZERO IF( K.LT.I-1 ) $ H( K+2, K-1 ) = ZERO ELSE IF( M.GT.L ) THEN H( K, K-1 ) = -H( K, K-1 ) END IF V2 = V( 2 ) T2 = T1*V2 IF( NR.EQ.3 ) THEN V3 = V( 3 ) T3 = T1*V3 * * Apply G from the left to transform the rows of the matrix * in columns K to I2. * DO 60 J = K, I2 SUM = H( K, J ) + V2*H( K+1, J ) + V3*H( K+2, J ) H( K, J ) = H( K, J ) - SUM*T1 H( K+1, J ) = H( K+1, J ) - SUM*T2 H( K+2, J ) = H( K+2, J ) - SUM*T3 60 CONTINUE * * Apply G from the right to transform the columns of the * matrix in rows I1 to min(K+3,I). * DO 70 J = I1, MIN( K+3, I ) SUM = H( J, K ) + V2*H( J, K+1 ) + V3*H( J, K+2 ) H( J, K ) = H( J, K ) - SUM*T1 H( J, K+1 ) = H( J, K+1 ) - SUM*T2 H( J, K+2 ) = H( J, K+2 ) - SUM*T3 70 CONTINUE * IF( WANTZ ) THEN * * Accumulate transformations in the matrix Z * DO 80 J = ILOZ, IHIZ SUM = Z( J, K ) + V2*Z( J, K+1 ) + V3*Z( J, K+2 ) Z( J, K ) = Z( J, K ) - SUM*T1 Z( J, K+1 ) = Z( J, K+1 ) - SUM*T2 Z( J, K+2 ) = Z( J, K+2 ) - SUM*T3 80 CONTINUE END IF ELSE IF( NR.EQ.2 ) THEN * * Apply G from the left to transform the rows of the matrix * in columns K to I2. * DO 90 J = K, I2 SUM = H( K, J ) + V2*H( K+1, J ) H( K, J ) = H( K, J ) - SUM*T1 H( K+1, J ) = H( K+1, J ) - SUM*T2 90 CONTINUE * * Apply G from the right to transform the columns of the * matrix in rows I1 to min(K+3,I). * DO 100 J = I1, I SUM = H( J, K ) + V2*H( J, K+1 ) H( J, K ) = H( J, K ) - SUM*T1 H( J, K+1 ) = H( J, K+1 ) - SUM*T2 100 CONTINUE * IF( WANTZ ) THEN * * Accumulate transformations in the matrix Z * DO 110 J = ILOZ, IHIZ SUM = Z( J, K ) + V2*Z( J, K+1 ) Z( J, K ) = Z( J, K ) - SUM*T1 Z( J, K+1 ) = Z( J, K+1 ) - SUM*T2 110 CONTINUE END IF END IF 120 CONTINUE * 130 CONTINUE * * Failure to converge in remaining number of iterations * INFO = I RETURN * 140 CONTINUE * IF( L.EQ.I ) THEN * * H(I,I-1) is negligible: one eigenvalue has converged. * WR( I ) = H( I, I ) WI( I ) = ZERO ELSE IF( L.EQ.I-1 ) THEN * * H(I-1,I-2) is negligible: a pair of eigenvalues have converged. * * Transform the 2-by-2 submatrix to standard Schur form, * and compute and store the eigenvalues. * CALL DLANV2( H( I-1, I-1 ), H( I-1, I ), H( I, I-1 ), $ H( I, I ), WR( I-1 ), WI( I-1 ), WR( I ), WI( I ), $ CS, SN ) * IF( WANTT ) THEN * * Apply the transformation to the rest of H. * IF( I2.GT.I ) $ CALL DROT( I2-I, H( I-1, I+1 ), LDH, H( I, I+1 ), LDH, $ CS, SN ) CALL DROT( I-I1-1, H( I1, I-1 ), 1, H( I1, I ), 1, CS, SN ) END IF IF( WANTZ ) THEN * * Apply the transformation to Z. * CALL DROT( NZ, Z( ILOZ, I-1 ), 1, Z( ILOZ, I ), 1, CS, SN ) END IF END IF * * Decrement number of remaining iterations, and return to start of * the main loop with new value of I. * ITN = ITN - ITS I = L - 1 GO TO 10 * 150 CONTINUE RETURN * * End of DLAHQR * END SUBROUTINE DLAHRD( N, K, NB, A, LDA, TAU, T, LDT, Y, LDY ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER K, LDA, LDT, LDY, N, NB * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), T( LDT, NB ), TAU( NB ), $ Y( LDY, NB ) * .. * * Purpose * ======= * * DLAHRD reduces the first NB columns of a real general n-by-(n-k+1) * matrix A so that elements below the k-th subdiagonal are zero. The * reduction is performed by an orthogonal similarity transformation * Q' * A * Q. The routine returns the matrices V and T which determine * Q as a block reflector I - V*T*V', and also the matrix Y = A * V * T. * * This is an auxiliary routine called by DGEHRD. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix A. * * K (input) INTEGER * The offset for the reduction. Elements below the k-th * subdiagonal in the first NB columns are reduced to zero. * * NB (input) INTEGER * The number of columns to be reduced. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N-K+1) * On entry, the n-by-(n-k+1) general matrix A. * On exit, the elements on and above the k-th subdiagonal in * the first NB columns are overwritten with the corresponding * elements of the reduced matrix; the elements below the k-th * subdiagonal, with the array TAU, represent the matrix Q as a * product of elementary reflectors. The other columns of A are * unchanged. See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * TAU (output) DOUBLE PRECISION array, dimension (NB) * The scalar factors of the elementary reflectors. See Further * Details. * * T (output) DOUBLE PRECISION array, dimension (LDT,NB) * The upper triangular matrix T. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= NB. * * Y (output) DOUBLE PRECISION array, dimension (LDY,NB) * The n-by-nb matrix Y. * * LDY (input) INTEGER * The leading dimension of the array Y. LDY >= N. * * Further Details * =============== * * The matrix Q is represented as a product of nb elementary reflectors * * Q = H(1) H(2) . . . H(nb). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i+k-1) = 0, v(i+k) = 1; v(i+k+1:n) is stored on exit in * A(i+k+1:n,i), and tau in TAU(i). * * The elements of the vectors v together form the (n-k+1)-by-nb matrix * V which is needed, with T and Y, to apply the transformation to the * unreduced part of the matrix, using an update of the form: * A := (I - V*T*V') * (A - Y*V'). * * The contents of A on exit are illustrated by the following example * with n = 7, k = 3 and nb = 2: * * ( a h a a a ) * ( a h a a a ) * ( a h a a a ) * ( h h a a a ) * ( v1 h a a a ) * ( v1 v2 a a a ) * ( v1 v2 a a a ) * * where a denotes an element of the original matrix A, h denotes a * modified element of the upper Hessenberg matrix H, and vi denotes an * element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I DOUBLE PRECISION EI * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DGEMV, DLARFG, DSCAL, DTRMV * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * * Quick return if possible * IF( N.LE.1 ) $ RETURN * DO 10 I = 1, NB IF( I.GT.1 ) THEN * * Update A(1:n,i) * * Compute i-th column of A - Y * V' * CALL DGEMV( 'No transpose', N, I-1, -ONE, Y, LDY, $ A( K+I-1, 1 ), LDA, ONE, A( 1, I ), 1 ) * * Apply I - V * T' * V' to this column (call it b) from the * left, using the last column of T as workspace * * Let V = ( V1 ) and b = ( b1 ) (first I-1 rows) * ( V2 ) ( b2 ) * * where V1 is unit lower triangular * * w := V1' * b1 * CALL DCOPY( I-1, A( K+1, I ), 1, T( 1, NB ), 1 ) CALL DTRMV( 'Lower', 'Transpose', 'Unit', I-1, A( K+1, 1 ), $ LDA, T( 1, NB ), 1 ) * * w := w + V2'*b2 * CALL DGEMV( 'Transpose', N-K-I+1, I-1, ONE, A( K+I, 1 ), $ LDA, A( K+I, I ), 1, ONE, T( 1, NB ), 1 ) * * w := T'*w * CALL DTRMV( 'Upper', 'Transpose', 'Non-unit', I-1, T, LDT, $ T( 1, NB ), 1 ) * * b2 := b2 - V2*w * CALL DGEMV( 'No transpose', N-K-I+1, I-1, -ONE, A( K+I, 1 ), $ LDA, T( 1, NB ), 1, ONE, A( K+I, I ), 1 ) * * b1 := b1 - V1*w * CALL DTRMV( 'Lower', 'No transpose', 'Unit', I-1, $ A( K+1, 1 ), LDA, T( 1, NB ), 1 ) CALL DAXPY( I-1, -ONE, T( 1, NB ), 1, A( K+1, I ), 1 ) * A( K+I-1, I-1 ) = EI END IF * * Generate the elementary reflector H(i) to annihilate * A(k+i+1:n,i) * CALL DLARFG( N-K-I+1, A( K+I, I ), A( MIN( K+I+1, N ), I ), 1, $ TAU( I ) ) EI = A( K+I, I ) A( K+I, I ) = ONE * * Compute Y(1:n,i) * CALL DGEMV( 'No transpose', N, N-K-I+1, ONE, A( 1, I+1 ), LDA, $ A( K+I, I ), 1, ZERO, Y( 1, I ), 1 ) CALL DGEMV( 'Transpose', N-K-I+1, I-1, ONE, A( K+I, 1 ), LDA, $ A( K+I, I ), 1, ZERO, T( 1, I ), 1 ) CALL DGEMV( 'No transpose', N, I-1, -ONE, Y, LDY, T( 1, I ), 1, $ ONE, Y( 1, I ), 1 ) CALL DSCAL( N, TAU( I ), Y( 1, I ), 1 ) * * Compute T(1:i,i) * CALL DSCAL( I-1, -TAU( I ), T( 1, I ), 1 ) CALL DTRMV( 'Upper', 'No transpose', 'Non-unit', I-1, T, LDT, $ T( 1, I ), 1 ) T( I, I ) = TAU( I ) * 10 CONTINUE A( K+NB, NB ) = EI * RETURN * * End of DLAHRD * END SUBROUTINE DLALN2( LTRANS, NA, NW, SMIN, CA, A, LDA, D1, D2, B, $ LDB, WR, WI, X, LDX, SCALE, XNORM, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. LOGICAL LTRANS INTEGER INFO, LDA, LDB, LDX, NA, NW DOUBLE PRECISION CA, D1, D2, SCALE, SMIN, WI, WR, XNORM * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), X( LDX, * ) * .. * * Purpose * ======= * * DLALN2 solves a system of the form (ca A - w D ) X = s B * or (ca A' - w D) X = s B with possible scaling ("s") and * perturbation of A. (A' means A-transpose.) * * A is an NA x NA real matrix, ca is a real scalar, D is an NA x NA * real diagonal matrix, w is a real or complex value, and X and B are * NA x 1 matrices -- real if w is real, complex if w is complex. NA * may be 1 or 2. * * If w is complex, X and B are represented as NA x 2 matrices, * the first column of each being the real part and the second * being the imaginary part. * * "s" is a scaling factor (.LE. 1), computed by DLALN2, which is * so chosen that X can be computed without overflow. X is further * scaled if necessary to assure that norm(ca A - w D)*norm(X) is less * than overflow. * * If both singular values of (ca A - w D) are less than SMIN, * SMIN*identity will be used instead of (ca A - w D). If only one * singular value is less than SMIN, one element of (ca A - w D) will be * perturbed enough to make the smallest singular value roughly SMIN. * If both singular values are at least SMIN, (ca A - w D) will not be * perturbed. In any case, the perturbation will be at most some small * multiple of max( SMIN, ulp*norm(ca A - w D) ). The singular values * are computed by infinity-norm approximations, and thus will only be * correct to a factor of 2 or so. * * Note: all input quantities are assumed to be smaller than overflow * by a reasonable factor. (See BIGNUM.) * * Arguments * ========== * * LTRANS (input) LOGICAL * =.TRUE.: A-transpose will be used. * =.FALSE.: A will be used (not transposed.) * * NA (input) INTEGER * The size of the matrix A. It may (only) be 1 or 2. * * NW (input) INTEGER * 1 if "w" is real, 2 if "w" is complex. It may only be 1 * or 2. * * SMIN (input) DOUBLE PRECISION * The desired lower bound on the singular values of A. This * should be a safe distance away from underflow or overflow, * say, between (underflow/machine precision) and (machine * precision * overflow ). (See BIGNUM and ULP.) * * CA (input) DOUBLE PRECISION * The coefficient c, which A is multiplied by. * * A (input) DOUBLE PRECISION array, dimension (LDA,NA) * The NA x NA matrix A. * * LDA (input) INTEGER * The leading dimension of A. It must be at least NA. * * D1 (input) DOUBLE PRECISION * The 1,1 element in the diagonal matrix D. * * D2 (input) DOUBLE PRECISION * The 2,2 element in the diagonal matrix D. Not used if NW=1. * * B (input) DOUBLE PRECISION array, dimension (LDB,NW) * The NA x NW matrix B (right-hand side). If NW=2 ("w" is * complex), column 1 contains the real part of B and column 2 * contains the imaginary part. * * LDB (input) INTEGER * The leading dimension of B. It must be at least NA. * * WR (input) DOUBLE PRECISION * The real part of the scalar "w". * * WI (input) DOUBLE PRECISION * The imaginary part of the scalar "w". Not used if NW=1. * * X (output) DOUBLE PRECISION array, dimension (LDX,NW) * The NA x NW matrix X (unknowns), as computed by DLALN2. * If NW=2 ("w" is complex), on exit, column 1 will contain * the real part of X and column 2 will contain the imaginary * part. * * LDX (input) INTEGER * The leading dimension of X. It must be at least NA. * * SCALE (output) DOUBLE PRECISION * The scale factor that B must be multiplied by to insure * that overflow does not occur when computing X. Thus, * (ca A - w D) X will be SCALE*B, not B (ignoring * perturbations of A.) It will be at most 1. * * XNORM (output) DOUBLE PRECISION * The infinity-norm of X, when X is regarded as an NA x NW * real matrix. * * INFO (output) INTEGER * An error flag. It will be set to zero if no error occurs, * a negative number if an argument is in error, or a positive * number if ca A - w D had to be perturbed. * The possible values are: * = 0: No error occurred, and (ca A - w D) did not have to be * perturbed. * = 1: (ca A - w D) had to be perturbed to make its smallest * (or only) singular value greater than SMIN. * NOTE: In the interests of speed, this routine does not * check the inputs for errors. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) * .. * .. Local Scalars .. INTEGER ICMAX, J DOUBLE PRECISION BBND, BI1, BI2, BIGNUM, BNORM, BR1, BR2, CI21, $ CI22, CMAX, CNORM, CR21, CR22, CSI, CSR, LI21, $ LR21, SMINI, SMLNUM, TEMP, U22ABS, UI11, UI11R, $ UI12, UI12S, UI22, UR11, UR11R, UR12, UR12S, $ UR22, XI1, XI2, XR1, XR2 * .. * .. Local Arrays .. LOGICAL RSWAP( 4 ), ZSWAP( 4 ) INTEGER IPIVOT( 4, 4 ) DOUBLE PRECISION CI( 2, 2 ), CIV( 4 ), CR( 2, 2 ), CRV( 4 ) * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. External Subroutines .. EXTERNAL DLADIV * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Equivalences .. EQUIVALENCE ( CI( 1, 1 ), CIV( 1 ) ), $ ( CR( 1, 1 ), CRV( 1 ) ) * .. * .. Data statements .. DATA ZSWAP / .FALSE., .FALSE., .TRUE., .TRUE. / DATA RSWAP / .FALSE., .TRUE., .FALSE., .TRUE. / DATA IPIVOT / 1, 2, 3, 4, 2, 1, 4, 3, 3, 4, 1, 2, 4, $ 3, 2, 1 / * .. * .. Executable Statements .. * * Compute BIGNUM * SMLNUM = TWO*DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SMLNUM SMINI = MAX( SMIN, SMLNUM ) * * Don't check for input errors * INFO = 0 * * Standard Initializations * SCALE = ONE * IF( NA.EQ.1 ) THEN * * 1 x 1 (i.e., scalar) system C X = B * IF( NW.EQ.1 ) THEN * * Real 1x1 system. * * C = ca A - w D * CSR = CA*A( 1, 1 ) - WR*D1 CNORM = ABS( CSR ) * * If | C | < SMINI, use C = SMINI * IF( CNORM.LT.SMINI ) THEN CSR = SMINI CNORM = SMINI INFO = 1 END IF * * Check scaling for X = B / C * BNORM = ABS( B( 1, 1 ) ) IF( CNORM.LT.ONE .AND. BNORM.GT.ONE ) THEN IF( BNORM.GT.BIGNUM*CNORM ) $ SCALE = ONE / BNORM END IF * * Compute X * X( 1, 1 ) = ( B( 1, 1 )*SCALE ) / CSR XNORM = ABS( X( 1, 1 ) ) ELSE * * Complex 1x1 system (w is complex) * * C = ca A - w D * CSR = CA*A( 1, 1 ) - WR*D1 CSI = -WI*D1 CNORM = ABS( CSR ) + ABS( CSI ) * * If | C | < SMINI, use C = SMINI * IF( CNORM.LT.SMINI ) THEN CSR = SMINI CSI = ZERO CNORM = SMINI INFO = 1 END IF * * Check scaling for X = B / C * BNORM = ABS( B( 1, 1 ) ) + ABS( B( 1, 2 ) ) IF( CNORM.LT.ONE .AND. BNORM.GT.ONE ) THEN IF( BNORM.GT.BIGNUM*CNORM ) $ SCALE = ONE / BNORM END IF * * Compute X * CALL DLADIV( SCALE*B( 1, 1 ), SCALE*B( 1, 2 ), CSR, CSI, $ X( 1, 1 ), X( 1, 2 ) ) XNORM = ABS( X( 1, 1 ) ) + ABS( X( 1, 2 ) ) END IF * ELSE * * 2x2 System * * Compute the real part of C = ca A - w D (or ca A' - w D ) * CR( 1, 1 ) = CA*A( 1, 1 ) - WR*D1 CR( 2, 2 ) = CA*A( 2, 2 ) - WR*D2 IF( LTRANS ) THEN CR( 1, 2 ) = CA*A( 2, 1 ) CR( 2, 1 ) = CA*A( 1, 2 ) ELSE CR( 2, 1 ) = CA*A( 2, 1 ) CR( 1, 2 ) = CA*A( 1, 2 ) END IF * IF( NW.EQ.1 ) THEN * * Real 2x2 system (w is real) * * Find the largest element in C * CMAX = ZERO ICMAX = 0 * DO 10 J = 1, 4 IF( ABS( CRV( J ) ).GT.CMAX ) THEN CMAX = ABS( CRV( J ) ) ICMAX = J END IF 10 CONTINUE * * If norm(C) < SMINI, use SMINI*identity. * IF( CMAX.LT.SMINI ) THEN BNORM = MAX( ABS( B( 1, 1 ) ), ABS( B( 2, 1 ) ) ) IF( SMINI.LT.ONE .AND. BNORM.GT.ONE ) THEN IF( BNORM.GT.BIGNUM*SMINI ) $ SCALE = ONE / BNORM END IF TEMP = SCALE / SMINI X( 1, 1 ) = TEMP*B( 1, 1 ) X( 2, 1 ) = TEMP*B( 2, 1 ) XNORM = TEMP*BNORM INFO = 1 RETURN END IF * * Gaussian elimination with complete pivoting. * UR11 = CRV( ICMAX ) CR21 = CRV( IPIVOT( 2, ICMAX ) ) UR12 = CRV( IPIVOT( 3, ICMAX ) ) CR22 = CRV( IPIVOT( 4, ICMAX ) ) UR11R = ONE / UR11 LR21 = UR11R*CR21 UR22 = CR22 - UR12*LR21 * * If smaller pivot < SMINI, use SMINI * IF( ABS( UR22 ).LT.SMINI ) THEN UR22 = SMINI INFO = 1 END IF IF( RSWAP( ICMAX ) ) THEN BR1 = B( 2, 1 ) BR2 = B( 1, 1 ) ELSE BR1 = B( 1, 1 ) BR2 = B( 2, 1 ) END IF BR2 = BR2 - LR21*BR1 BBND = MAX( ABS( BR1*( UR22*UR11R ) ), ABS( BR2 ) ) IF( BBND.GT.ONE .AND. ABS( UR22 ).LT.ONE ) THEN IF( BBND.GE.BIGNUM*ABS( UR22 ) ) $ SCALE = ONE / BBND END IF * XR2 = ( BR2*SCALE ) / UR22 XR1 = ( SCALE*BR1 )*UR11R - XR2*( UR11R*UR12 ) IF( ZSWAP( ICMAX ) ) THEN X( 1, 1 ) = XR2 X( 2, 1 ) = XR1 ELSE X( 1, 1 ) = XR1 X( 2, 1 ) = XR2 END IF XNORM = MAX( ABS( XR1 ), ABS( XR2 ) ) * * Further scaling if norm(A) norm(X) > overflow * IF( XNORM.GT.ONE .AND. CMAX.GT.ONE ) THEN IF( XNORM.GT.BIGNUM / CMAX ) THEN TEMP = CMAX / BIGNUM X( 1, 1 ) = TEMP*X( 1, 1 ) X( 2, 1 ) = TEMP*X( 2, 1 ) XNORM = TEMP*XNORM SCALE = TEMP*SCALE END IF END IF ELSE * * Complex 2x2 system (w is complex) * * Find the largest element in C * CI( 1, 1 ) = -WI*D1 CI( 2, 1 ) = ZERO CI( 1, 2 ) = ZERO CI( 2, 2 ) = -WI*D2 CMAX = ZERO ICMAX = 0 * DO 20 J = 1, 4 IF( ABS( CRV( J ) )+ABS( CIV( J ) ).GT.CMAX ) THEN CMAX = ABS( CRV( J ) ) + ABS( CIV( J ) ) ICMAX = J END IF 20 CONTINUE * * If norm(C) < SMINI, use SMINI*identity. * IF( CMAX.LT.SMINI ) THEN BNORM = MAX( ABS( B( 1, 1 ) )+ABS( B( 1, 2 ) ), $ ABS( B( 2, 1 ) )+ABS( B( 2, 2 ) ) ) IF( SMINI.LT.ONE .AND. BNORM.GT.ONE ) THEN IF( BNORM.GT.BIGNUM*SMINI ) $ SCALE = ONE / BNORM END IF TEMP = SCALE / SMINI X( 1, 1 ) = TEMP*B( 1, 1 ) X( 2, 1 ) = TEMP*B( 2, 1 ) X( 1, 2 ) = TEMP*B( 1, 2 ) X( 2, 2 ) = TEMP*B( 2, 2 ) XNORM = TEMP*BNORM INFO = 1 RETURN END IF * * Gaussian elimination with complete pivoting. * UR11 = CRV( ICMAX ) UI11 = CIV( ICMAX ) CR21 = CRV( IPIVOT( 2, ICMAX ) ) CI21 = CIV( IPIVOT( 2, ICMAX ) ) UR12 = CRV( IPIVOT( 3, ICMAX ) ) UI12 = CIV( IPIVOT( 3, ICMAX ) ) CR22 = CRV( IPIVOT( 4, ICMAX ) ) CI22 = CIV( IPIVOT( 4, ICMAX ) ) IF( ICMAX.EQ.1 .OR. ICMAX.EQ.4 ) THEN * * Code when off-diagonals of pivoted C are real * IF( ABS( UR11 ).GT.ABS( UI11 ) ) THEN TEMP = UI11 / UR11 UR11R = ONE / ( UR11*( ONE+TEMP**2 ) ) UI11R = -TEMP*UR11R ELSE TEMP = UR11 / UI11 UI11R = -ONE / ( UI11*( ONE+TEMP**2 ) ) UR11R = -TEMP*UI11R END IF LR21 = CR21*UR11R LI21 = CR21*UI11R UR12S = UR12*UR11R UI12S = UR12*UI11R UR22 = CR22 - UR12*LR21 UI22 = CI22 - UR12*LI21 ELSE * * Code when diagonals of pivoted C are real * UR11R = ONE / UR11 UI11R = ZERO LR21 = CR21*UR11R LI21 = CI21*UR11R UR12S = UR12*UR11R UI12S = UI12*UR11R UR22 = CR22 - UR12*LR21 + UI12*LI21 UI22 = -UR12*LI21 - UI12*LR21 END IF U22ABS = ABS( UR22 ) + ABS( UI22 ) * * If smaller pivot < SMINI, use SMINI * IF( U22ABS.LT.SMINI ) THEN UR22 = SMINI UI22 = ZERO INFO = 1 END IF IF( RSWAP( ICMAX ) ) THEN BR2 = B( 1, 1 ) BR1 = B( 2, 1 ) BI2 = B( 1, 2 ) BI1 = B( 2, 2 ) ELSE BR1 = B( 1, 1 ) BR2 = B( 2, 1 ) BI1 = B( 1, 2 ) BI2 = B( 2, 2 ) END IF BR2 = BR2 - LR21*BR1 + LI21*BI1 BI2 = BI2 - LI21*BR1 - LR21*BI1 BBND = MAX( ( ABS( BR1 )+ABS( BI1 ) )* $ ( U22ABS*( ABS( UR11R )+ABS( UI11R ) ) ), $ ABS( BR2 )+ABS( BI2 ) ) IF( BBND.GT.ONE .AND. U22ABS.LT.ONE ) THEN IF( BBND.GE.BIGNUM*U22ABS ) THEN SCALE = ONE / BBND BR1 = SCALE*BR1 BI1 = SCALE*BI1 BR2 = SCALE*BR2 BI2 = SCALE*BI2 END IF END IF * CALL DLADIV( BR2, BI2, UR22, UI22, XR2, XI2 ) XR1 = UR11R*BR1 - UI11R*BI1 - UR12S*XR2 + UI12S*XI2 XI1 = UI11R*BR1 + UR11R*BI1 - UI12S*XR2 - UR12S*XI2 IF( ZSWAP( ICMAX ) ) THEN X( 1, 1 ) = XR2 X( 2, 1 ) = XR1 X( 1, 2 ) = XI2 X( 2, 2 ) = XI1 ELSE X( 1, 1 ) = XR1 X( 2, 1 ) = XR2 X( 1, 2 ) = XI1 X( 2, 2 ) = XI2 END IF XNORM = MAX( ABS( XR1 )+ABS( XI1 ), ABS( XR2 )+ABS( XI2 ) ) * * Further scaling if norm(A) norm(X) > overflow * IF( XNORM.GT.ONE .AND. CMAX.GT.ONE ) THEN IF( XNORM.GT.BIGNUM / CMAX ) THEN TEMP = CMAX / BIGNUM X( 1, 1 ) = TEMP*X( 1, 1 ) X( 2, 1 ) = TEMP*X( 2, 1 ) X( 1, 2 ) = TEMP*X( 1, 2 ) X( 2, 2 ) = TEMP*X( 2, 2 ) XNORM = TEMP*XNORM SCALE = TEMP*SCALE END IF END IF END IF END IF * RETURN * * End of DLALN2 * END DOUBLE PRECISION FUNCTION DLAMCH( CMACH ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER CMACH * .. * * Purpose * ======= * * DLAMCH determines double precision machine parameters. * * Arguments * ========= * * CMACH (input) CHARACTER*1 * Specifies the value to be returned by DLAMCH: * = 'E' or 'e', DLAMCH := eps * = 'S' or 's , DLAMCH := sfmin * = 'B' or 'b', DLAMCH := base * = 'P' or 'p', DLAMCH := eps*base * = 'N' or 'n', DLAMCH := t * = 'R' or 'r', DLAMCH := rnd * = 'M' or 'm', DLAMCH := emin * = 'U' or 'u', DLAMCH := rmin * = 'L' or 'l', DLAMCH := emax * = 'O' or 'o', DLAMCH := rmax * * where * * eps = relative machine precision * sfmin = safe minimum, such that 1/sfmin does not overflow * base = base of the machine * prec = eps*base * t = number of (base) digits in the mantissa * rnd = 1.0 when rounding occurs in addition, 0.0 otherwise * emin = minimum exponent before (gradual) underflow * rmin = underflow threshold - base**(emin-1) * emax = largest exponent before overflow * rmax = overflow threshold - (base**emax)*(1-eps) * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL FIRST, LRND INTEGER BETA, IMAX, IMIN, IT DOUBLE PRECISION BASE, EMAX, EMIN, EPS, PREC, RMACH, RMAX, RMIN, $ RND, SFMIN, SMALL, T * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLAMC2 * .. * .. Save statement .. SAVE FIRST, EPS, SFMIN, BASE, T, RND, EMIN, RMIN, $ EMAX, RMAX, PREC * .. * .. Data statements .. DATA FIRST / .TRUE. / * .. * .. Executable Statements .. * IF( FIRST ) THEN FIRST = .FALSE. CALL DLAMC2( BETA, IT, LRND, EPS, IMIN, RMIN, IMAX, RMAX ) BASE = BETA T = IT IF( LRND ) THEN RND = ONE EPS = ( BASE**( 1-IT ) ) / 2 ELSE RND = ZERO EPS = BASE**( 1-IT ) END IF PREC = EPS*BASE EMIN = IMIN EMAX = IMAX SFMIN = RMIN SMALL = ONE / RMAX IF( SMALL.GE.SFMIN ) THEN * * Use SMALL plus a bit, to avoid the possibility of rounding * causing overflow when computing 1/sfmin. * SFMIN = SMALL*( ONE+EPS ) END IF END IF * IF( LSAME( CMACH, 'E' ) ) THEN RMACH = EPS ELSE IF( LSAME( CMACH, 'S' ) ) THEN RMACH = SFMIN ELSE IF( LSAME( CMACH, 'B' ) ) THEN RMACH = BASE ELSE IF( LSAME( CMACH, 'P' ) ) THEN RMACH = PREC ELSE IF( LSAME( CMACH, 'N' ) ) THEN RMACH = T ELSE IF( LSAME( CMACH, 'R' ) ) THEN RMACH = RND ELSE IF( LSAME( CMACH, 'M' ) ) THEN RMACH = EMIN ELSE IF( LSAME( CMACH, 'U' ) ) THEN RMACH = RMIN ELSE IF( LSAME( CMACH, 'L' ) ) THEN RMACH = EMAX ELSE IF( LSAME( CMACH, 'O' ) ) THEN RMACH = RMAX END IF * DLAMCH = RMACH RETURN * * End of DLAMCH * END * ************************************************************************ * SUBROUTINE DLAMC1( BETA, T, RND, IEEE1 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. LOGICAL IEEE1, RND INTEGER BETA, T * .. * * Purpose * ======= * * DLAMC1 determines the machine parameters given by BETA, T, RND, and * IEEE1. * * Arguments * ========= * * BETA (output) INTEGER * The base of the machine. * * T (output) INTEGER * The number of ( BETA ) digits in the mantissa. * * RND (output) LOGICAL * Specifies whether proper rounding ( RND = .TRUE. ) or * chopping ( RND = .FALSE. ) occurs in addition. This may not * be a reliable guide to the way in which the machine performs * its arithmetic. * * IEEE1 (output) LOGICAL * Specifies whether rounding appears to be done in the IEEE * 'round to nearest' style. * * Further Details * =============== * * The routine is based on the routine ENVRON by Malcolm and * incorporates suggestions by Gentleman and Marovich. See * * Malcolm M. A. (1972) Algorithms to reveal properties of * floating-point arithmetic. Comms. of the ACM, 15, 949-951. * * Gentleman W. M. and Marovich S. B. (1974) More on algorithms * that reveal properties of floating point arithmetic units. * Comms. of the ACM, 17, 276-277. * * ===================================================================== * * .. Local Scalars .. LOGICAL FIRST, LIEEE1, LRND INTEGER LBETA, LT DOUBLE PRECISION A, B, C, F, ONE, QTR, SAVEC, T1, T2 * .. * .. External Functions .. DOUBLE PRECISION DLAMC3 EXTERNAL DLAMC3 * .. * .. Save statement .. SAVE FIRST, LIEEE1, LBETA, LRND, LT * .. * .. Data statements .. DATA FIRST / .TRUE. / * .. * .. Executable Statements .. * IF( FIRST ) THEN FIRST = .FALSE. ONE = 1 * * LBETA, LIEEE1, LT and LRND are the local values of BETA, * IEEE1, T and RND. * * Throughout this routine we use the function DLAMC3 to ensure * that relevant values are stored and not held in registers, or * are not affected by optimizers. * * Compute a = 2.0**m with the smallest positive integer m such * that * * fl( a + 1.0 ) = a. * A = 1 C = 1 * *+ WHILE( C.EQ.ONE )LOOP 10 CONTINUE IF( C.EQ.ONE ) THEN A = 2*A C = DLAMC3( A, ONE ) C = DLAMC3( C, -A ) GO TO 10 END IF *+ END WHILE * * Now compute b = 2.0**m with the smallest positive integer m * such that * * fl( a + b ) .gt. a. * B = 1 C = DLAMC3( A, B ) * *+ WHILE( C.EQ.A )LOOP 20 CONTINUE IF( C.EQ.A ) THEN B = 2*B C = DLAMC3( A, B ) GO TO 20 END IF *+ END WHILE * * Now compute the base. a and c are neighbouring floating point * numbers in the interval ( beta**t, beta**( t + 1 ) ) and so * their difference is beta. Adding 0.25 to c is to ensure that it * is truncated to beta and not ( beta - 1 ). * QTR = ONE / 4 SAVEC = C C = DLAMC3( C, -A ) LBETA = C + QTR * * Now determine whether rounding or chopping occurs, by adding a * bit less than beta/2 and a bit more than beta/2 to a. * B = LBETA F = DLAMC3( B / 2, -B / 100 ) C = DLAMC3( F, A ) IF( C.EQ.A ) THEN LRND = .TRUE. ELSE LRND = .FALSE. END IF F = DLAMC3( B / 2, B / 100 ) C = DLAMC3( F, A ) IF( ( LRND ) .AND. ( C.EQ.A ) ) $ LRND = .FALSE. * * Try and decide whether rounding is done in the IEEE 'round to * nearest' style. B/2 is half a unit in the last place of the two * numbers A and SAVEC. Furthermore, A is even, i.e. has last bit * zero, and SAVEC is odd. Thus adding B/2 to A should not change * A, but adding B/2 to SAVEC should change SAVEC. * T1 = DLAMC3( B / 2, A ) T2 = DLAMC3( B / 2, SAVEC ) LIEEE1 = ( T1.EQ.A ) .AND. ( T2.GT.SAVEC ) .AND. LRND * * Now find the mantissa, t. It should be the integer part of * log to the base beta of a, however it is safer to determine t * by powering. So we find t as the smallest positive integer for * which * * fl( beta**t + 1.0 ) = 1.0. * LT = 0 A = 1 C = 1 * *+ WHILE( C.EQ.ONE )LOOP 30 CONTINUE IF( C.EQ.ONE ) THEN LT = LT + 1 A = A*LBETA C = DLAMC3( A, ONE ) C = DLAMC3( C, -A ) GO TO 30 END IF *+ END WHILE * END IF * BETA = LBETA T = LT RND = LRND IEEE1 = LIEEE1 RETURN * * End of DLAMC1 * END * ************************************************************************ * SUBROUTINE DLAMC2( BETA, T, RND, EPS, EMIN, RMIN, EMAX, RMAX ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. LOGICAL RND INTEGER BETA, EMAX, EMIN, T DOUBLE PRECISION EPS, RMAX, RMIN * .. * * Purpose * ======= * * DLAMC2 determines the machine parameters specified in its argument * list. * * Arguments * ========= * * BETA (output) INTEGER * The base of the machine. * * T (output) INTEGER * The number of ( BETA ) digits in the mantissa. * * RND (output) LOGICAL * Specifies whether proper rounding ( RND = .TRUE. ) or * chopping ( RND = .FALSE. ) occurs in addition. This may not * be a reliable guide to the way in which the machine performs * its arithmetic. * * EPS (output) DOUBLE PRECISION * The smallest positive number such that * * fl( 1.0 - EPS ) .LT. 1.0, * * where fl denotes the computed value. * * EMIN (output) INTEGER * The minimum exponent before (gradual) underflow occurs. * * RMIN (output) DOUBLE PRECISION * The smallest normalized number for the machine, given by * BASE**( EMIN - 1 ), where BASE is the floating point value * of BETA. * * EMAX (output) INTEGER * The maximum exponent before overflow occurs. * * RMAX (output) DOUBLE PRECISION * The largest positive number for the machine, given by * BASE**EMAX * ( 1 - EPS ), where BASE is the floating point * value of BETA. * * Further Details * =============== * * The computation of EPS is based on a routine PARANOIA by * W. Kahan of the University of California at Berkeley. * * ===================================================================== * * .. Local Scalars .. LOGICAL FIRST, IEEE, IWARN, LIEEE1, LRND INTEGER GNMIN, GPMIN, I, LBETA, LEMAX, LEMIN, LT, $ NGNMIN, NGPMIN DOUBLE PRECISION A, B, C, HALF, LEPS, LRMAX, LRMIN, ONE, RBASE, $ SIXTH, SMALL, THIRD, TWO, ZERO * .. * .. External Functions .. DOUBLE PRECISION DLAMC3 EXTERNAL DLAMC3 * .. * .. External Subroutines .. EXTERNAL DLAMC1, DLAMC4, DLAMC5 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Save statement .. SAVE FIRST, IWARN, LBETA, LEMAX, LEMIN, LEPS, LRMAX, $ LRMIN, LT * .. * .. Data statements .. DATA FIRST / .TRUE. / , IWARN / .FALSE. / * .. * .. Executable Statements .. * IF( FIRST ) THEN FIRST = .FALSE. ZERO = 0 ONE = 1 TWO = 2 * * LBETA, LT, LRND, LEPS, LEMIN and LRMIN are the local values of * BETA, T, RND, EPS, EMIN and RMIN. * * Throughout this routine we use the function DLAMC3 to ensure * that relevant values are stored and not held in registers, or * are not affected by optimizers. * * DLAMC1 returns the parameters LBETA, LT, LRND and LIEEE1. * CALL DLAMC1( LBETA, LT, LRND, LIEEE1 ) * * Start to find EPS. * B = LBETA A = B**( -LT ) LEPS = A * * Try some tricks to see whether or not this is the correct EPS. * B = TWO / 3 HALF = ONE / 2 SIXTH = DLAMC3( B, -HALF ) THIRD = DLAMC3( SIXTH, SIXTH ) B = DLAMC3( THIRD, -HALF ) B = DLAMC3( B, SIXTH ) B = ABS( B ) IF( B.LT.LEPS ) $ B = LEPS * LEPS = 1 * *+ WHILE( ( LEPS.GT.B ).AND.( B.GT.ZERO ) )LOOP 10 CONTINUE IF( ( LEPS.GT.B ) .AND. ( B.GT.ZERO ) ) THEN LEPS = B C = DLAMC3( HALF*LEPS, ( TWO**5 )*( LEPS**2 ) ) C = DLAMC3( HALF, -C ) B = DLAMC3( HALF, C ) C = DLAMC3( HALF, -B ) B = DLAMC3( HALF, C ) GO TO 10 END IF *+ END WHILE * IF( A.LT.LEPS ) $ LEPS = A * * Computation of EPS complete. * * Now find EMIN. Let A = + or - 1, and + or - (1 + BASE**(-3)). * Keep dividing A by BETA until (gradual) underflow occurs. This * is detected when we cannot recover the previous A. * RBASE = ONE / LBETA SMALL = ONE DO 20 I = 1, 3 SMALL = DLAMC3( SMALL*RBASE, ZERO ) 20 CONTINUE A = DLAMC3( ONE, SMALL ) CALL DLAMC4( NGPMIN, ONE, LBETA ) CALL DLAMC4( NGNMIN, -ONE, LBETA ) CALL DLAMC4( GPMIN, A, LBETA ) CALL DLAMC4( GNMIN, -A, LBETA ) IEEE = .FALSE. * IF( ( NGPMIN.EQ.NGNMIN ) .AND. ( GPMIN.EQ.GNMIN ) ) THEN IF( NGPMIN.EQ.GPMIN ) THEN LEMIN = NGPMIN * ( Non twos-complement machines, no gradual underflow; * e.g., VAX ) ELSE IF( ( GPMIN-NGPMIN ).EQ.3 ) THEN LEMIN = NGPMIN - 1 + LT IEEE = .TRUE. * ( Non twos-complement machines, with gradual underflow; * e.g., IEEE standard followers ) ELSE LEMIN = MIN( NGPMIN, GPMIN ) * ( A guess; no known machine ) IWARN = .TRUE. END IF * ELSE IF( ( NGPMIN.EQ.GPMIN ) .AND. ( NGNMIN.EQ.GNMIN ) ) THEN IF( ABS( NGPMIN-NGNMIN ).EQ.1 ) THEN LEMIN = MAX( NGPMIN, NGNMIN ) * ( Twos-complement machines, no gradual underflow; * e.g., CYBER 205 ) ELSE LEMIN = MIN( NGPMIN, NGNMIN ) * ( A guess; no known machine ) IWARN = .TRUE. END IF * ELSE IF( ( ABS( NGPMIN-NGNMIN ).EQ.1 ) .AND. $ ( GPMIN.EQ.GNMIN ) ) THEN IF( ( GPMIN-MIN( NGPMIN, NGNMIN ) ).EQ.3 ) THEN LEMIN = MAX( NGPMIN, NGNMIN ) - 1 + LT * ( Twos-complement machines with gradual underflow; * no known machine ) ELSE LEMIN = MIN( NGPMIN, NGNMIN ) * ( A guess; no known machine ) IWARN = .TRUE. END IF * ELSE LEMIN = MIN( NGPMIN, NGNMIN, GPMIN, GNMIN ) * ( A guess; no known machine ) IWARN = .TRUE. END IF *** * Comment out this if block if EMIN is ok IF( IWARN ) THEN FIRST = .TRUE. WRITE( 6, FMT = 9999 )LEMIN END IF *** * * Assume IEEE arithmetic if we found denormalised numbers above, * or if arithmetic seems to round in the IEEE style, determined * in routine DLAMC1. A true IEEE machine should have both things * true; however, faulty machines may have one or the other. * IEEE = IEEE .OR. LIEEE1 * * Compute RMIN by successive division by BETA. We could compute * RMIN as BASE**( EMIN - 1 ), but some machines underflow during * this computation. * LRMIN = 1 DO 30 I = 1, 1 - LEMIN LRMIN = DLAMC3( LRMIN*RBASE, ZERO ) 30 CONTINUE * * Finally, call DLAMC5 to compute EMAX and RMAX. * CALL DLAMC5( LBETA, LT, LEMIN, IEEE, LEMAX, LRMAX ) END IF * BETA = LBETA T = LT RND = LRND EPS = LEPS EMIN = LEMIN RMIN = LRMIN EMAX = LEMAX RMAX = LRMAX * RETURN * 9999 FORMAT( / / ' WARNING. The value EMIN may be incorrect:-', $ ' EMIN = ', I8, / $ ' If, after inspection, the value EMIN looks', $ ' acceptable please comment out ', $ / ' the IF block as marked within the code of routine', $ ' DLAMC2,', / ' otherwise supply EMIN explicitly.', / ) * * End of DLAMC2 * END * ************************************************************************ * DOUBLE PRECISION FUNCTION DLAMC3( A, B ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION A, B * .. * * Purpose * ======= * * DLAMC3 is intended to force A and B to be stored prior to doing * the addition of A and B , for use in situations where optimizers * might hold one of these in a register. * * Arguments * ========= * * A, B (input) DOUBLE PRECISION * The values A and B. * * ===================================================================== * * .. Executable Statements .. * DLAMC3 = A + B * RETURN * * End of DLAMC3 * END * ************************************************************************ * SUBROUTINE DLAMC4( EMIN, START, BASE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. INTEGER BASE, EMIN DOUBLE PRECISION START * .. * * Purpose * ======= * * DLAMC4 is a service routine for DLAMC2. * * Arguments * ========= * * EMIN (output) EMIN * The minimum exponent before (gradual) underflow, computed by * setting A = START and dividing by BASE until the previous A * can not be recovered. * * START (input) DOUBLE PRECISION * The starting point for determining EMIN. * * BASE (input) INTEGER * The base of the machine. * * ===================================================================== * * .. Local Scalars .. INTEGER I DOUBLE PRECISION A, B1, B2, C1, C2, D1, D2, ONE, RBASE, ZERO * .. * .. External Functions .. DOUBLE PRECISION DLAMC3 EXTERNAL DLAMC3 * .. * .. Executable Statements .. * A = START ONE = 1 RBASE = ONE / BASE ZERO = 0 EMIN = 1 B1 = DLAMC3( A*RBASE, ZERO ) C1 = A C2 = A D1 = A D2 = A *+ WHILE( ( C1.EQ.A ).AND.( C2.EQ.A ).AND. * $ ( D1.EQ.A ).AND.( D2.EQ.A ) )LOOP 10 CONTINUE IF( ( C1.EQ.A ) .AND. ( C2.EQ.A ) .AND. ( D1.EQ.A ) .AND. $ ( D2.EQ.A ) ) THEN EMIN = EMIN - 1 A = B1 B1 = DLAMC3( A / BASE, ZERO ) C1 = DLAMC3( B1*BASE, ZERO ) D1 = ZERO DO 20 I = 1, BASE D1 = D1 + B1 20 CONTINUE B2 = DLAMC3( A*RBASE, ZERO ) C2 = DLAMC3( B2 / RBASE, ZERO ) D2 = ZERO DO 30 I = 1, BASE D2 = D2 + B2 30 CONTINUE GO TO 10 END IF *+ END WHILE * RETURN * * End of DLAMC4 * END * ************************************************************************ * SUBROUTINE DLAMC5( BETA, P, EMIN, IEEE, EMAX, RMAX ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. LOGICAL IEEE INTEGER BETA, EMAX, EMIN, P DOUBLE PRECISION RMAX * .. * * Purpose * ======= * * DLAMC5 attempts to compute RMAX, the largest machine floating-point * number, without overflow. It assumes that EMAX + abs(EMIN) sum * approximately to a power of 2. It will fail on machines where this * assumption does not hold, for example, the Cyber 205 (EMIN = -28625, * EMAX = 28718). It will also fail if the value supplied for EMIN is * too large (i.e. too close to zero), probably with overflow. * * Arguments * ========= * * BETA (input) INTEGER * The base of floating-point arithmetic. * * P (input) INTEGER * The number of base BETA digits in the mantissa of a * floating-point value. * * EMIN (input) INTEGER * The minimum exponent before (gradual) underflow. * * IEEE (input) LOGICAL * A logical flag specifying whether or not the arithmetic * system is thought to comply with the IEEE standard. * * EMAX (output) INTEGER * The largest exponent before overflow * * RMAX (output) DOUBLE PRECISION * The largest machine floating-point number. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. INTEGER EXBITS, EXPSUM, I, LEXP, NBITS, TRY, UEXP DOUBLE PRECISION OLDY, RECBAS, Y, Z * .. * .. External Functions .. DOUBLE PRECISION DLAMC3 EXTERNAL DLAMC3 * .. * .. Intrinsic Functions .. INTRINSIC MOD * .. * .. Executable Statements .. * * First compute LEXP and UEXP, two powers of 2 that bound * abs(EMIN). We then assume that EMAX + abs(EMIN) will sum * approximately to the bound that is closest to abs(EMIN). * (EMAX is the exponent of the required number RMAX). * LEXP = 1 EXBITS = 1 10 CONTINUE TRY = LEXP*2 IF( TRY.LE.( -EMIN ) ) THEN LEXP = TRY EXBITS = EXBITS + 1 GO TO 10 END IF IF( LEXP.EQ.-EMIN ) THEN UEXP = LEXP ELSE UEXP = TRY EXBITS = EXBITS + 1 END IF * * Now -LEXP is less than or equal to EMIN, and -UEXP is greater * than or equal to EMIN. EXBITS is the number of bits needed to * store the exponent. * IF( ( UEXP+EMIN ).GT.( -LEXP-EMIN ) ) THEN EXPSUM = 2*LEXP ELSE EXPSUM = 2*UEXP END IF * * EXPSUM is the exponent range, approximately equal to * EMAX - EMIN + 1 . * EMAX = EXPSUM + EMIN - 1 NBITS = 1 + EXBITS + P * * NBITS is the total number of bits needed to store a * floating-point number. * IF( ( MOD( NBITS, 2 ).EQ.1 ) .AND. ( BETA.EQ.2 ) ) THEN * * Either there are an odd number of bits used to store a * floating-point number, which is unlikely, or some bits are * not used in the representation of numbers, which is possible, * (e.g. Cray machines) or the mantissa has an implicit bit, * (e.g. IEEE machines, Dec Vax machines), which is perhaps the * most likely. We have to assume the last alternative. * If this is true, then we need to reduce EMAX by one because * there must be some way of representing zero in an implicit-bit * system. On machines like Cray, we are reducing EMAX by one * unnecessarily. * EMAX = EMAX - 1 END IF * IF( IEEE ) THEN * * Assume we are on an IEEE machine which reserves one exponent * for infinity and NaN. * EMAX = EMAX - 1 END IF * * Now create RMAX, the largest machine number, which should * be equal to (1.0 - BETA**(-P)) * BETA**EMAX . * * First compute 1.0 - BETA**(-P), being careful that the * result is less than 1.0 . * RECBAS = ONE / BETA Z = BETA - ONE Y = ZERO DO 20 I = 1, P Z = Z*RECBAS IF( Y.LT.ONE ) $ OLDY = Y Y = DLAMC3( Y, Z ) 20 CONTINUE IF( Y.GE.ONE ) $ Y = OLDY * * Now multiply by BETA**EMAX to get RMAX. * DO 30 I = 1, EMAX Y = DLAMC3( Y*BETA, ZERO ) 30 CONTINUE * RMAX = Y RETURN * * End of DLAMC5 * END DOUBLE PRECISION FUNCTION DLANGE( NORM, M, N, A, LDA, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER NORM INTEGER LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), WORK( * ) * .. * * Purpose * ======= * * DLANGE returns the value of the one norm, or the Frobenius norm, or * the infinity norm, or the element of largest absolute value of a * real matrix A. * * Description * =========== * * DLANGE returns the value * * DLANGE = ( max(abs(A(i,j))), NORM = 'M' or 'm' * ( * ( norm1(A), NORM = '1', 'O' or 'o' * ( * ( normI(A), NORM = 'I' or 'i' * ( * ( normF(A), NORM = 'F', 'f', 'E' or 'e' * * where norm1 denotes the one norm of a matrix (maximum column sum), * normI denotes the infinity norm of a matrix (maximum row sum) and * normF denotes the Frobenius norm of a matrix (square root of sum of * squares). Note that max(abs(A(i,j))) is not a matrix norm. * * Arguments * ========= * * NORM (input) CHARACTER*1 * Specifies the value to be returned in DLANGE as described * above. * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. When M = 0, * DLANGE is set to zero. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. When N = 0, * DLANGE is set to zero. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The m by n matrix A. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(M,1). * * WORK (workspace) DOUBLE PRECISION array, dimension (LWORK), * where LWORK >= M when NORM = 'I'; otherwise, WORK is not * referenced. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J DOUBLE PRECISION SCALE, SUM, VALUE * .. * .. External Subroutines .. EXTERNAL DLASSQ * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Executable Statements .. * IF( MIN( M, N ).EQ.0 ) THEN VALUE = ZERO ELSE IF( LSAME( NORM, 'M' ) ) THEN * * Find max(abs(A(i,j))). * VALUE = ZERO DO 20 J = 1, N DO 10 I = 1, M VALUE = MAX( VALUE, ABS( A( I, J ) ) ) 10 CONTINUE 20 CONTINUE ELSE IF( ( LSAME( NORM, 'O' ) ) .OR. ( NORM.EQ.'1' ) ) THEN * * Find norm1(A). * VALUE = ZERO DO 40 J = 1, N SUM = ZERO DO 30 I = 1, M SUM = SUM + ABS( A( I, J ) ) 30 CONTINUE VALUE = MAX( VALUE, SUM ) 40 CONTINUE ELSE IF( LSAME( NORM, 'I' ) ) THEN * * Find normI(A). * DO 50 I = 1, M WORK( I ) = ZERO 50 CONTINUE DO 70 J = 1, N DO 60 I = 1, M WORK( I ) = WORK( I ) + ABS( A( I, J ) ) 60 CONTINUE 70 CONTINUE VALUE = ZERO DO 80 I = 1, M VALUE = MAX( VALUE, WORK( I ) ) 80 CONTINUE ELSE IF( ( LSAME( NORM, 'F' ) ) .OR. ( LSAME( NORM, 'E' ) ) ) THEN * * Find normF(A). * SCALE = ZERO SUM = ONE DO 90 J = 1, N CALL DLASSQ( M, A( 1, J ), 1, SCALE, SUM ) 90 CONTINUE VALUE = SCALE*SQRT( SUM ) END IF * DLANGE = VALUE RETURN * * End of DLANGE * END DOUBLE PRECISION FUNCTION DLANHS( NORM, N, A, LDA, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER NORM INTEGER LDA, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), WORK( * ) * .. * * Purpose * ======= * * DLANHS returns the value of the one norm, or the Frobenius norm, or * the infinity norm, or the element of largest absolute value of a * Hessenberg matrix A. * * Description * =========== * * DLANHS returns the value * * DLANHS = ( max(abs(A(i,j))), NORM = 'M' or 'm' * ( * ( norm1(A), NORM = '1', 'O' or 'o' * ( * ( normI(A), NORM = 'I' or 'i' * ( * ( normF(A), NORM = 'F', 'f', 'E' or 'e' * * where norm1 denotes the one norm of a matrix (maximum column sum), * normI denotes the infinity norm of a matrix (maximum row sum) and * normF denotes the Frobenius norm of a matrix (square root of sum of * squares). Note that max(abs(A(i,j))) is not a matrix norm. * * Arguments * ========= * * NORM (input) CHARACTER*1 * Specifies the value to be returned in DLANHS as described * above. * * N (input) INTEGER * The order of the matrix A. N >= 0. When N = 0, DLANHS is * set to zero. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The n by n upper Hessenberg matrix A; the part of A below the * first sub-diagonal is not referenced. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(N,1). * * WORK (workspace) DOUBLE PRECISION array, dimension (LWORK), * where LWORK >= N when NORM = 'I'; otherwise, WORK is not * referenced. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J DOUBLE PRECISION SCALE, SUM, VALUE * .. * .. External Subroutines .. EXTERNAL DLASSQ * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Executable Statements .. * IF( N.EQ.0 ) THEN VALUE = ZERO ELSE IF( LSAME( NORM, 'M' ) ) THEN * * Find max(abs(A(i,j))). * VALUE = ZERO DO 20 J = 1, N DO 10 I = 1, MIN( N, J+1 ) VALUE = MAX( VALUE, ABS( A( I, J ) ) ) 10 CONTINUE 20 CONTINUE ELSE IF( ( LSAME( NORM, 'O' ) ) .OR. ( NORM.EQ.'1' ) ) THEN * * Find norm1(A). * VALUE = ZERO DO 40 J = 1, N SUM = ZERO DO 30 I = 1, MIN( N, J+1 ) SUM = SUM + ABS( A( I, J ) ) 30 CONTINUE VALUE = MAX( VALUE, SUM ) 40 CONTINUE ELSE IF( LSAME( NORM, 'I' ) ) THEN * * Find normI(A). * DO 50 I = 1, N WORK( I ) = ZERO 50 CONTINUE DO 70 J = 1, N DO 60 I = 1, MIN( N, J+1 ) WORK( I ) = WORK( I ) + ABS( A( I, J ) ) 60 CONTINUE 70 CONTINUE VALUE = ZERO DO 80 I = 1, N VALUE = MAX( VALUE, WORK( I ) ) 80 CONTINUE ELSE IF( ( LSAME( NORM, 'F' ) ) .OR. ( LSAME( NORM, 'E' ) ) ) THEN * * Find normF(A). * SCALE = ZERO SUM = ONE DO 90 J = 1, N CALL DLASSQ( MIN( N, J+1 ), A( 1, J ), 1, SCALE, SUM ) 90 CONTINUE VALUE = SCALE*SQRT( SUM ) END IF * DLANHS = VALUE RETURN * * End of DLANHS * END DOUBLE PRECISION FUNCTION DLANST( NORM, N, D, E ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER NORM INTEGER N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ) * .. * * Purpose * ======= * * DLANST returns the value of the one norm, or the Frobenius norm, or * the infinity norm, or the element of largest absolute value of a * real symmetric tridiagonal matrix A. * * Description * =========== * * DLANST returns the value * * DLANST = ( max(abs(A(i,j))), NORM = 'M' or 'm' * ( * ( norm1(A), NORM = '1', 'O' or 'o' * ( * ( normI(A), NORM = 'I' or 'i' * ( * ( normF(A), NORM = 'F', 'f', 'E' or 'e' * * where norm1 denotes the one norm of a matrix (maximum column sum), * normI denotes the infinity norm of a matrix (maximum row sum) and * normF denotes the Frobenius norm of a matrix (square root of sum of * squares). Note that max(abs(A(i,j))) is not a matrix norm. * * Arguments * ========= * * NORM (input) CHARACTER*1 * Specifies the value to be returned in DLANST as described * above. * * N (input) INTEGER * The order of the matrix A. N >= 0. When N = 0, DLANST is * set to zero. * * D (input) DOUBLE PRECISION array, dimension (N) * The diagonal elements of A. * * E (input) DOUBLE PRECISION array, dimension (N-1) * The (n-1) sub-diagonal or super-diagonal elements of A. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I DOUBLE PRECISION ANORM, SCALE, SUM * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLASSQ * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * IF( N.LE.0 ) THEN ANORM = ZERO ELSE IF( LSAME( NORM, 'M' ) ) THEN * * Find max(abs(A(i,j))). * ANORM = ABS( D( N ) ) DO 10 I = 1, N - 1 ANORM = MAX( ANORM, ABS( D( I ) ) ) ANORM = MAX( ANORM, ABS( E( I ) ) ) 10 CONTINUE ELSE IF( LSAME( NORM, 'O' ) .OR. NORM.EQ.'1' .OR. $ LSAME( NORM, 'I' ) ) THEN * * Find norm1(A). * IF( N.EQ.1 ) THEN ANORM = ABS( D( 1 ) ) ELSE ANORM = MAX( ABS( D( 1 ) )+ABS( E( 1 ) ), $ ABS( E( N-1 ) )+ABS( D( N ) ) ) DO 20 I = 2, N - 1 ANORM = MAX( ANORM, ABS( D( I ) )+ABS( E( I ) )+ $ ABS( E( I-1 ) ) ) 20 CONTINUE END IF ELSE IF( ( LSAME( NORM, 'F' ) ) .OR. ( LSAME( NORM, 'E' ) ) ) THEN * * Find normF(A). * SCALE = ZERO SUM = ONE IF( N.GT.1 ) THEN CALL DLASSQ( N-1, E, 1, SCALE, SUM ) SUM = 2*SUM END IF CALL DLASSQ( N, D, 1, SCALE, SUM ) ANORM = SCALE*SQRT( SUM ) END IF * DLANST = ANORM RETURN * * End of DLANST * END DOUBLE PRECISION FUNCTION DLANSY( NORM, UPLO, N, A, LDA, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER NORM, UPLO INTEGER LDA, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), WORK( * ) * .. * * Purpose * ======= * * DLANSY returns the value of the one norm, or the Frobenius norm, or * the infinity norm, or the element of largest absolute value of a * real symmetric matrix A. * * Description * =========== * * DLANSY returns the value * * DLANSY = ( max(abs(A(i,j))), NORM = 'M' or 'm' * ( * ( norm1(A), NORM = '1', 'O' or 'o' * ( * ( normI(A), NORM = 'I' or 'i' * ( * ( normF(A), NORM = 'F', 'f', 'E' or 'e' * * where norm1 denotes the one norm of a matrix (maximum column sum), * normI denotes the infinity norm of a matrix (maximum row sum) and * normF denotes the Frobenius norm of a matrix (square root of sum of * squares). Note that max(abs(A(i,j))) is not a matrix norm. * * Arguments * ========= * * NORM (input) CHARACTER*1 * Specifies the value to be returned in DLANSY as described * above. * * UPLO (input) CHARACTER*1 * Specifies whether the upper or lower triangular part of the * symmetric matrix A is to be referenced. * = 'U': Upper triangular part of A is referenced * = 'L': Lower triangular part of A is referenced * * N (input) INTEGER * The order of the matrix A. N >= 0. When N = 0, DLANSY is * set to zero. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The symmetric matrix A. If UPLO = 'U', the leading n by n * upper triangular part of A contains the upper triangular part * of the matrix A, and the strictly lower triangular part of A * is not referenced. If UPLO = 'L', the leading n by n lower * triangular part of A contains the lower triangular part of * the matrix A, and the strictly upper triangular part of A is * not referenced. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(N,1). * * WORK (workspace) DOUBLE PRECISION array, dimension (LWORK), * where LWORK >= N when NORM = 'I' or '1' or 'O'; otherwise, * WORK is not referenced. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J DOUBLE PRECISION ABSA, SCALE, SUM, VALUE * .. * .. External Subroutines .. EXTERNAL DLASSQ * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * IF( N.EQ.0 ) THEN VALUE = ZERO ELSE IF( LSAME( NORM, 'M' ) ) THEN * * Find max(abs(A(i,j))). * VALUE = ZERO IF( LSAME( UPLO, 'U' ) ) THEN DO 20 J = 1, N DO 10 I = 1, J VALUE = MAX( VALUE, ABS( A( I, J ) ) ) 10 CONTINUE 20 CONTINUE ELSE DO 40 J = 1, N DO 30 I = J, N VALUE = MAX( VALUE, ABS( A( I, J ) ) ) 30 CONTINUE 40 CONTINUE END IF ELSE IF( ( LSAME( NORM, 'I' ) ) .OR. ( LSAME( NORM, 'O' ) ) .OR. $ ( NORM.EQ.'1' ) ) THEN * * Find normI(A) ( = norm1(A), since A is symmetric). * VALUE = ZERO IF( LSAME( UPLO, 'U' ) ) THEN DO 60 J = 1, N SUM = ZERO DO 50 I = 1, J - 1 ABSA = ABS( A( I, J ) ) SUM = SUM + ABSA WORK( I ) = WORK( I ) + ABSA 50 CONTINUE WORK( J ) = SUM + ABS( A( J, J ) ) 60 CONTINUE DO 70 I = 1, N VALUE = MAX( VALUE, WORK( I ) ) 70 CONTINUE ELSE DO 80 I = 1, N WORK( I ) = ZERO 80 CONTINUE DO 100 J = 1, N SUM = WORK( J ) + ABS( A( J, J ) ) DO 90 I = J + 1, N ABSA = ABS( A( I, J ) ) SUM = SUM + ABSA WORK( I ) = WORK( I ) + ABSA 90 CONTINUE VALUE = MAX( VALUE, SUM ) 100 CONTINUE END IF ELSE IF( ( LSAME( NORM, 'F' ) ) .OR. ( LSAME( NORM, 'E' ) ) ) THEN * * Find normF(A). * SCALE = ZERO SUM = ONE IF( LSAME( UPLO, 'U' ) ) THEN DO 110 J = 2, N CALL DLASSQ( J-1, A( 1, J ), 1, SCALE, SUM ) 110 CONTINUE ELSE DO 120 J = 1, N - 1 CALL DLASSQ( N-J, A( J+1, J ), 1, SCALE, SUM ) 120 CONTINUE END IF SUM = 2*SUM CALL DLASSQ( N, A, LDA+1, SCALE, SUM ) VALUE = SCALE*SQRT( SUM ) END IF * DLANSY = VALUE RETURN * * End of DLANSY * END SUBROUTINE DLANV2( A, B, C, D, RT1R, RT1I, RT2R, RT2I, CS, SN ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. DOUBLE PRECISION A, B, C, CS, D, RT1I, RT1R, RT2I, RT2R, SN * .. * * Purpose * ======= * * DLANV2 computes the Schur factorization of a real 2-by-2 nonsymmetric * matrix in standard form: * * [ A B ] = [ CS -SN ] [ AA BB ] [ CS SN ] * [ C D ] [ SN CS ] [ CC DD ] [-SN CS ] * * where either * 1) CC = 0 so that AA and DD are real eigenvalues of the matrix, or * 2) AA = DD and BB*CC < 0, so that AA + or - sqrt(BB*CC) are complex * conjugate eigenvalues. * * Arguments * ========= * * A (input/output) DOUBLE PRECISION * B (input/output) DOUBLE PRECISION * C (input/output) DOUBLE PRECISION * D (input/output) DOUBLE PRECISION * On entry, the elements of the input matrix. * On exit, they are overwritten by the elements of the * standardised Schur form. * * RT1R (output) DOUBLE PRECISION * RT1I (output) DOUBLE PRECISION * RT2R (output) DOUBLE PRECISION * RT2I (output) DOUBLE PRECISION * The real and imaginary parts of the eigenvalues. If the * eigenvalues are a complex conjugate pair, RT1I > 0. * * CS (output) DOUBLE PRECISION * SN (output) DOUBLE PRECISION * Parameters of the rotation matrix. * * Further Details * =============== * * Modified by V. Sima, Research Institute for Informatics, Bucharest, * Romania, to reduce the risk of cancellation errors, * when computing real eigenvalues, and to ensure, if possible, that * abs(RT1R) >= abs(RT2R). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, HALF, ONE PARAMETER ( ZERO = 0.0D+0, HALF = 0.5D+0, ONE = 1.0D+0 ) DOUBLE PRECISION MULTPL PARAMETER ( MULTPL = 4.0D+0 ) * .. * .. Local Scalars .. DOUBLE PRECISION AA, BB, BCMAX, BCMIS, CC, CS1, DD, EPS, P, SAB, $ SAC, SCALE, SIGMA, SN1, TAU, TEMP, Z * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLAPY2 EXTERNAL DLAMCH, DLAPY2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SIGN, SQRT * .. * .. Executable Statements .. * EPS = DLAMCH( 'P' ) IF( C.EQ.ZERO ) THEN CS = ONE SN = ZERO GO TO 10 * ELSE IF( B.EQ.ZERO ) THEN * * Swap rows and columns * CS = ZERO SN = ONE TEMP = D D = A A = TEMP B = -C C = ZERO GO TO 10 ELSE IF( ( A-D ).EQ.ZERO .AND. SIGN( ONE, B ).NE.SIGN( ONE, C ) ) $ THEN CS = ONE SN = ZERO GO TO 10 ELSE * TEMP = A - D P = HALF*TEMP BCMAX = MAX( ABS( B ), ABS( C ) ) BCMIS = MIN( ABS( B ), ABS( C ) )*SIGN( ONE, B )*SIGN( ONE, C ) SCALE = MAX( ABS( P ), BCMAX ) Z = ( P / SCALE )*P + ( BCMAX / SCALE )*BCMIS * * If Z is of the order of the machine accuracy, postpone the * decision on the nature of eigenvalues * IF( Z.GE.MULTPL*EPS ) THEN * * Real eigenvalues. Compute A and D. * Z = P + SIGN( SQRT( SCALE )*SQRT( Z ), P ) A = D + Z D = D - ( BCMAX / Z )*BCMIS * * Compute B and the rotation matrix * TAU = DLAPY2( C, Z ) CS = Z / TAU SN = C / TAU B = B - C C = ZERO ELSE * * Complex eigenvalues, or real (almost) equal eigenvalues. * Make diagonal elements equal. * SIGMA = B + C TAU = DLAPY2( SIGMA, TEMP ) CS = SQRT( HALF*( ONE+ABS( SIGMA ) / TAU ) ) SN = -( P / ( TAU*CS ) )*SIGN( ONE, SIGMA ) * * Compute [ AA BB ] = [ A B ] [ CS -SN ] * [ CC DD ] [ C D ] [ SN CS ] * AA = A*CS + B*SN BB = -A*SN + B*CS CC = C*CS + D*SN DD = -C*SN + D*CS * * Compute [ A B ] = [ CS SN ] [ AA BB ] * [ C D ] [-SN CS ] [ CC DD ] * A = AA*CS + CC*SN B = BB*CS + DD*SN C = -AA*SN + CC*CS D = -BB*SN + DD*CS * TEMP = HALF*( A+D ) A = TEMP D = TEMP * IF( C.NE.ZERO ) THEN IF( B.NE.ZERO ) THEN IF( SIGN( ONE, B ).EQ.SIGN( ONE, C ) ) THEN * * Real eigenvalues: reduce to upper triangular form * SAB = SQRT( ABS( B ) ) SAC = SQRT( ABS( C ) ) P = SIGN( SAB*SAC, C ) TAU = ONE / SQRT( ABS( B+C ) ) A = TEMP + P D = TEMP - P B = B - C C = ZERO CS1 = SAB*TAU SN1 = SAC*TAU TEMP = CS*CS1 - SN*SN1 SN = CS*SN1 + SN*CS1 CS = TEMP END IF ELSE B = -C C = ZERO TEMP = CS CS = -SN SN = TEMP END IF END IF END IF * END IF * 10 CONTINUE * * Store eigenvalues in (RT1R,RT1I) and (RT2R,RT2I). * RT1R = A RT2R = D IF( C.EQ.ZERO ) THEN RT1I = ZERO RT2I = ZERO ELSE RT1I = SQRT( ABS( B ) )*SQRT( ABS( C ) ) RT2I = -RT1I END IF RETURN * * End of DLANV2 * END DOUBLE PRECISION FUNCTION DLAPY2( X, Y ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION X, Y * .. * * Purpose * ======= * * DLAPY2 returns sqrt(x**2+y**2), taking care not to cause unnecessary * overflow. * * Arguments * ========= * * X (input) DOUBLE PRECISION * Y (input) DOUBLE PRECISION * X and Y specify the values x and y. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) * .. * .. Local Scalars .. DOUBLE PRECISION W, XABS, YABS, Z * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Executable Statements .. * XABS = ABS( X ) YABS = ABS( Y ) W = MAX( XABS, YABS ) Z = MIN( XABS, YABS ) IF( Z.EQ.ZERO ) THEN DLAPY2 = W ELSE DLAPY2 = W*SQRT( ONE+( Z / W )**2 ) END IF RETURN * * End of DLAPY2 * END SUBROUTINE DLAQTR( LTRAN, LREAL, N, T, LDT, B, W, SCALE, X, WORK, $ INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. LOGICAL LREAL, LTRAN INTEGER INFO, LDT, N DOUBLE PRECISION SCALE, W * .. * .. Array Arguments .. DOUBLE PRECISION B( * ), T( LDT, * ), WORK( * ), X( * ) * .. * * Purpose * ======= * * DLAQTR solves the real quasi-triangular system * * op(T)*p = scale*c, if LREAL = .TRUE. * * or the complex quasi-triangular systems * * op(T + iB)*(p+iq) = scale*(c+id), if LREAL = .FALSE. * * in real arithmetic, where T is upper quasi-triangular. * If LREAL = .FALSE., then the first diagonal block of T must be * 1 by 1, B is the specially structured matrix * * B = [ b(1) b(2) ... b(n) ] * [ w ] * [ w ] * [ . ] * [ w ] * * op(A) = A or A', A' denotes the conjugate transpose of * matrix A. * * On input, X = [ c ]. On output, X = [ p ]. * [ d ] [ q ] * * This subroutine is designed for the condition number estimation * in routine DTRSNA. * * Arguments * ========= * * LTRAN (input) LOGICAL * On entry, LTRAN specifies the option of conjugate transpose: * = .FALSE., op(T+i*B) = T+i*B, * = .TRUE., op(T+i*B) = (T+i*B)'. * * LREAL (input) LOGICAL * On entry, LREAL specifies the input matrix structure: * = .FALSE., the input is complex * = .TRUE., the input is real * * N (input) INTEGER * On entry, N specifies the order of T+i*B. N >= 0. * * T (input) DOUBLE PRECISION array, dimension (LDT,N) * On entry, T contains a matrix in Schur canonical form. * If LREAL = .FALSE., then the first diagonal block of T mu * be 1 by 1. * * LDT (input) INTEGER * The leading dimension of the matrix T. LDT >= max(1,N). * * B (input) DOUBLE PRECISION array, dimension (N) * On entry, B contains the elements to form the matrix * B as described above. * If LREAL = .TRUE., B is not referenced. * * W (input) DOUBLE PRECISION * On entry, W is the diagonal element of the matrix B. * If LREAL = .TRUE., W is not referenced. * * SCALE (output) DOUBLE PRECISION * On exit, SCALE is the scale factor. * * X (input/output) DOUBLE PRECISION array, dimension (2*N) * On entry, X contains the right hand side of the system. * On exit, X is overwritten by the solution. * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * On exit, INFO is set to * 0: successful exit. * 1: the some diagonal 1 by 1 block has been perturbed by * a small number SMIN to keep nonsingularity. * 2: the some diagonal 2 by 2 block has been perturbed by * a small number in DLALN2 to keep nonsingularity. * NOTE: In the interests of speed, this routine does not * check the inputs for errors. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL NOTRAN INTEGER I, IERR, J, J1, J2, JNEXT, K, N1, N2 DOUBLE PRECISION BIGNUM, EPS, REC, SCALOC, SI, SMIN, SMINW, $ SMLNUM, SR, TJJ, TMP, XJ, XMAX, XNORM, Z * .. * .. Local Arrays .. DOUBLE PRECISION D( 2, 2 ), V( 2, 2 ) * .. * .. External Functions .. INTEGER IDAMAX DOUBLE PRECISION DASUM, DDOT, DLAMCH, DLANGE EXTERNAL IDAMAX, DASUM, DDOT, DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DAXPY, DLADIV, DLALN2, DSCAL * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Do not test the input parameters for errors * NOTRAN = .NOT.LTRAN INFO = 0 * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Set constants to control overflow * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) / EPS BIGNUM = ONE / SMLNUM * XNORM = DLANGE( 'M', N, N, T, LDT, D ) IF( .NOT.LREAL ) $ XNORM = MAX( XNORM, ABS( W ), DLANGE( 'M', N, 1, B, N, D ) ) SMIN = MAX( SMLNUM, EPS*XNORM ) * * Compute 1-norm of each column of strictly upper triangular * part of T to control overflow in triangular solver. * WORK( 1 ) = ZERO DO 10 J = 2, N WORK( J ) = DASUM( J-1, T( 1, J ), 1 ) 10 CONTINUE * IF( .NOT.LREAL ) THEN DO 20 I = 2, N WORK( I ) = WORK( I ) + ABS( B( I ) ) 20 CONTINUE END IF * N2 = 2*N N1 = N IF( .NOT.LREAL ) $ N1 = N2 K = IDAMAX( N1, X, 1 ) XMAX = ABS( X( K ) ) SCALE = ONE * IF( XMAX.GT.BIGNUM ) THEN SCALE = BIGNUM / XMAX CALL DSCAL( N1, SCALE, X, 1 ) XMAX = BIGNUM END IF * IF( LREAL ) THEN * IF( NOTRAN ) THEN * * Solve T*p = scale*c * JNEXT = N DO 30 J = N, 1, -1 IF( J.GT.JNEXT ) $ GO TO 30 J1 = J J2 = J JNEXT = J - 1 IF( J.GT.1 ) THEN IF( T( J, J-1 ).NE.ZERO ) THEN J1 = J - 1 JNEXT = J - 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * Meet 1 by 1 diagonal block * * Scale to avoid overflow when computing * x(j) = b(j)/T(j,j) * XJ = ABS( X( J1 ) ) TJJ = ABS( T( J1, J1 ) ) TMP = T( J1, J1 ) IF( TJJ.LT.SMIN ) THEN TMP = SMIN TJJ = SMIN INFO = 1 END IF * IF( XJ.EQ.ZERO ) $ GO TO 30 * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.BIGNUM*TJJ ) THEN REC = ONE / XJ CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF X( J1 ) = X( J1 ) / TMP XJ = ABS( X( J1 ) ) * * Scale x if necessary to avoid overflow when adding a * multiple of column j1 of T. * IF( XJ.GT.ONE ) THEN REC = ONE / XJ IF( WORK( J1 ).GT.( BIGNUM-XMAX )*REC ) THEN CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC END IF END IF IF( J1.GT.1 ) THEN CALL DAXPY( J1-1, -X( J1 ), T( 1, J1 ), 1, X, 1 ) K = IDAMAX( J1-1, X, 1 ) XMAX = ABS( X( K ) ) END IF * ELSE * * Meet 2 by 2 diagonal block * * Call 2 by 2 linear system solve, to take * care of possible overflow by scaling factor. * D( 1, 1 ) = X( J1 ) D( 2, 1 ) = X( J2 ) CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, T( J1, J1 ), $ LDT, ONE, ONE, D, 2, ZERO, ZERO, V, 2, $ SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 2 * IF( SCALOC.NE.ONE ) THEN CALL DSCAL( N, SCALOC, X, 1 ) SCALE = SCALE*SCALOC END IF X( J1 ) = V( 1, 1 ) X( J2 ) = V( 2, 1 ) * * Scale V(1,1) (= X(J1)) and/or V(2,1) (=X(J2)) * to avoid overflow in updating right-hand side. * XJ = MAX( ABS( V( 1, 1 ) ), ABS( V( 2, 1 ) ) ) IF( XJ.GT.ONE ) THEN REC = ONE / XJ IF( MAX( WORK( J1 ), WORK( J2 ) ).GT. $ ( BIGNUM-XMAX )*REC ) THEN CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC END IF END IF * * Update right-hand side * IF( J1.GT.1 ) THEN CALL DAXPY( J1-1, -X( J1 ), T( 1, J1 ), 1, X, 1 ) CALL DAXPY( J1-1, -X( J2 ), T( 1, J2 ), 1, X, 1 ) K = IDAMAX( J1-1, X, 1 ) XMAX = ABS( X( K ) ) END IF * END IF * 30 CONTINUE * ELSE * * Solve T'*p = scale*c * JNEXT = 1 DO 40 J = 1, N IF( J.LT.JNEXT ) $ GO TO 40 J1 = J J2 = J JNEXT = J + 1 IF( J.LT.N ) THEN IF( T( J+1, J ).NE.ZERO ) THEN J2 = J + 1 JNEXT = J + 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1 by 1 diagonal block * * Scale if necessary to avoid overflow in forming the * right-hand side element by inner product. * XJ = ABS( X( J1 ) ) IF( XMAX.GT.ONE ) THEN REC = ONE / XMAX IF( WORK( J1 ).GT.( BIGNUM-XJ )*REC ) THEN CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF * X( J1 ) = X( J1 ) - DDOT( J1-1, T( 1, J1 ), 1, X, 1 ) * XJ = ABS( X( J1 ) ) TJJ = ABS( T( J1, J1 ) ) TMP = T( J1, J1 ) IF( TJJ.LT.SMIN ) THEN TMP = SMIN TJJ = SMIN INFO = 1 END IF * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.BIGNUM*TJJ ) THEN REC = ONE / XJ CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF X( J1 ) = X( J1 ) / TMP XMAX = MAX( XMAX, ABS( X( J1 ) ) ) * ELSE * * 2 by 2 diagonal block * * Scale if necessary to avoid overflow in forming the * right-hand side elements by inner product. * XJ = MAX( ABS( X( J1 ) ), ABS( X( J2 ) ) ) IF( XMAX.GT.ONE ) THEN REC = ONE / XMAX IF( MAX( WORK( J2 ), WORK( J1 ) ).GT.( BIGNUM-XJ )* $ REC ) THEN CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF * D( 1, 1 ) = X( J1 ) - DDOT( J1-1, T( 1, J1 ), 1, X, $ 1 ) D( 2, 1 ) = X( J2 ) - DDOT( J1-1, T( 1, J2 ), 1, X, $ 1 ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, T( J1, J1 ), $ LDT, ONE, ONE, D, 2, ZERO, ZERO, V, 2, $ SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 2 * IF( SCALOC.NE.ONE ) THEN CALL DSCAL( N, SCALOC, X, 1 ) SCALE = SCALE*SCALOC END IF X( J1 ) = V( 1, 1 ) X( J2 ) = V( 2, 1 ) XMAX = MAX( ABS( X( J1 ) ), ABS( X( J2 ) ), XMAX ) * END IF 40 CONTINUE END IF * ELSE * SMINW = MAX( EPS*ABS( W ), SMIN ) IF( NOTRAN ) THEN * * Solve (T + iB)*(p+iq) = c+id * JNEXT = N DO 70 J = N, 1, -1 IF( J.GT.JNEXT ) $ GO TO 70 J1 = J J2 = J JNEXT = J - 1 IF( J.GT.1 ) THEN IF( T( J, J-1 ).NE.ZERO ) THEN J1 = J - 1 JNEXT = J - 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1 by 1 diagonal block * * Scale if necessary to avoid overflow in division * Z = W IF( J1.EQ.1 ) $ Z = B( 1 ) XJ = ABS( X( J1 ) ) + ABS( X( N+J1 ) ) TJJ = ABS( T( J1, J1 ) ) + ABS( Z ) TMP = T( J1, J1 ) IF( TJJ.LT.SMINW ) THEN TMP = SMINW TJJ = SMINW INFO = 1 END IF * IF( XJ.EQ.ZERO ) $ GO TO 70 * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.BIGNUM*TJJ ) THEN REC = ONE / XJ CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF CALL DLADIV( X( J1 ), X( N+J1 ), TMP, Z, SR, SI ) X( J1 ) = SR X( N+J1 ) = SI XJ = ABS( X( J1 ) ) + ABS( X( N+J1 ) ) * * Scale x if necessary to avoid overflow when adding a * multiple of column j1 of T. * IF( XJ.GT.ONE ) THEN REC = ONE / XJ IF( WORK( J1 ).GT.( BIGNUM-XMAX )*REC ) THEN CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC END IF END IF * IF( J1.GT.1 ) THEN CALL DAXPY( J1-1, -X( J1 ), T( 1, J1 ), 1, X, 1 ) CALL DAXPY( J1-1, -X( N+J1 ), T( 1, J1 ), 1, $ X( N+1 ), 1 ) * X( 1 ) = X( 1 ) + B( J1 )*X( N+J1 ) X( N+1 ) = X( N+1 ) - B( J1 )*X( J1 ) * XMAX = ZERO DO 50 K = 1, J1 - 1 XMAX = MAX( XMAX, ABS( X( K ) )+ $ ABS( X( K+N ) ) ) 50 CONTINUE END IF * ELSE * * Meet 2 by 2 diagonal block * D( 1, 1 ) = X( J1 ) D( 2, 1 ) = X( J2 ) D( 1, 2 ) = X( N+J1 ) D( 2, 2 ) = X( N+J2 ) CALL DLALN2( .FALSE., 2, 2, SMINW, ONE, T( J1, J1 ), $ LDT, ONE, ONE, D, 2, ZERO, -W, V, 2, $ SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 2 * IF( SCALOC.NE.ONE ) THEN CALL DSCAL( 2*N, SCALOC, X, 1 ) SCALE = SCALOC*SCALE END IF X( J1 ) = V( 1, 1 ) X( J2 ) = V( 2, 1 ) X( N+J1 ) = V( 1, 2 ) X( N+J2 ) = V( 2, 2 ) * * Scale X(J1), .... to avoid overflow in * updating right hand side. * XJ = MAX( ABS( V( 1, 1 ) )+ABS( V( 1, 2 ) ), $ ABS( V( 2, 1 ) )+ABS( V( 2, 2 ) ) ) IF( XJ.GT.ONE ) THEN REC = ONE / XJ IF( MAX( WORK( J1 ), WORK( J2 ) ).GT. $ ( BIGNUM-XMAX )*REC ) THEN CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC END IF END IF * * Update the right-hand side. * IF( J1.GT.1 ) THEN CALL DAXPY( J1-1, -X( J1 ), T( 1, J1 ), 1, X, 1 ) CALL DAXPY( J1-1, -X( J2 ), T( 1, J2 ), 1, X, 1 ) * CALL DAXPY( J1-1, -X( N+J1 ), T( 1, J1 ), 1, $ X( N+1 ), 1 ) CALL DAXPY( J1-1, -X( N+J2 ), T( 1, J2 ), 1, $ X( N+1 ), 1 ) * X( 1 ) = X( 1 ) + B( J1 )*X( N+J1 ) + $ B( J2 )*X( N+J2 ) X( N+1 ) = X( N+1 ) - B( J1 )*X( J1 ) - $ B( J2 )*X( J2 ) * XMAX = ZERO DO 60 K = 1, J1 - 1 XMAX = MAX( ABS( X( K ) )+ABS( X( K+N ) ), $ XMAX ) 60 CONTINUE END IF * END IF 70 CONTINUE * ELSE * * Solve (T + iB)'*(p+iq) = c+id * JNEXT = 1 DO 80 J = 1, N IF( J.LT.JNEXT ) $ GO TO 80 J1 = J J2 = J JNEXT = J + 1 IF( J.LT.N ) THEN IF( T( J+1, J ).NE.ZERO ) THEN J2 = J + 1 JNEXT = J + 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1 by 1 diagonal block * * Scale if necessary to avoid overflow in forming the * right-hand side element by inner product. * XJ = ABS( X( J1 ) ) + ABS( X( J1+N ) ) IF( XMAX.GT.ONE ) THEN REC = ONE / XMAX IF( WORK( J1 ).GT.( BIGNUM-XJ )*REC ) THEN CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF * X( J1 ) = X( J1 ) - DDOT( J1-1, T( 1, J1 ), 1, X, 1 ) X( N+J1 ) = X( N+J1 ) - DDOT( J1-1, T( 1, J1 ), 1, $ X( N+1 ), 1 ) IF( J1.GT.1 ) THEN X( J1 ) = X( J1 ) - B( J1 )*X( N+1 ) X( N+J1 ) = X( N+J1 ) + B( J1 )*X( 1 ) END IF XJ = ABS( X( J1 ) ) + ABS( X( J1+N ) ) * Z = W IF( J1.EQ.1 ) $ Z = B( 1 ) * * Scale if necessary to avoid overflow in * complex division * TJJ = ABS( T( J1, J1 ) ) + ABS( Z ) TMP = T( J1, J1 ) IF( TJJ.LT.SMINW ) THEN TMP = SMINW TJJ = SMINW INFO = 1 END IF * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.BIGNUM*TJJ ) THEN REC = ONE / XJ CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF CALL DLADIV( X( J1 ), X( N+J1 ), TMP, -Z, SR, SI ) X( J1 ) = SR X( J1+N ) = SI XMAX = MAX( ABS( X( J1 ) )+ABS( X( J1+N ) ), XMAX ) * ELSE * * 2 by 2 diagonal block * * Scale if necessary to avoid overflow in forming the * right-hand side element by inner product. * XJ = MAX( ABS( X( J1 ) )+ABS( X( N+J1 ) ), $ ABS( X( J2 ) )+ABS( X( N+J2 ) ) ) IF( XMAX.GT.ONE ) THEN REC = ONE / XMAX IF( MAX( WORK( J1 ), WORK( J2 ) ).GT. $ ( BIGNUM-XJ ) / XMAX ) THEN CALL DSCAL( N2, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF * D( 1, 1 ) = X( J1 ) - DDOT( J1-1, T( 1, J1 ), 1, X, $ 1 ) D( 2, 1 ) = X( J2 ) - DDOT( J1-1, T( 1, J2 ), 1, X, $ 1 ) D( 1, 2 ) = X( N+J1 ) - DDOT( J1-1, T( 1, J1 ), 1, $ X( N+1 ), 1 ) D( 2, 2 ) = X( N+J2 ) - DDOT( J1-1, T( 1, J2 ), 1, $ X( N+1 ), 1 ) D( 1, 1 ) = D( 1, 1 ) - B( J1 )*X( N+1 ) D( 2, 1 ) = D( 2, 1 ) - B( J2 )*X( N+1 ) D( 1, 2 ) = D( 1, 2 ) + B( J1 )*X( 1 ) D( 2, 2 ) = D( 2, 2 ) + B( J2 )*X( 1 ) * CALL DLALN2( .TRUE., 2, 2, SMINW, ONE, T( J1, J1 ), $ LDT, ONE, ONE, D, 2, ZERO, W, V, 2, $ SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 2 * IF( SCALOC.NE.ONE ) THEN CALL DSCAL( N2, SCALOC, X, 1 ) SCALE = SCALOC*SCALE END IF X( J1 ) = V( 1, 1 ) X( J2 ) = V( 2, 1 ) X( N+J1 ) = V( 1, 2 ) X( N+J2 ) = V( 2, 2 ) XMAX = MAX( ABS( X( J1 ) )+ABS( X( N+J1 ) ), $ ABS( X( J2 ) )+ABS( X( N+J2 ) ), XMAX ) * END IF * 80 CONTINUE * END IF * END IF * RETURN * * End of DLAQTR * END SUBROUTINE DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER SIDE INTEGER INCV, LDC, M, N DOUBLE PRECISION TAU * .. * .. Array Arguments .. DOUBLE PRECISION C( LDC, * ), V( * ), WORK( * ) * .. * * Purpose * ======= * * DLARF applies a real elementary reflector H to a real m by n matrix * C, from either the left or the right. H is represented in the form * * H = I - tau * v * v' * * where tau is a real scalar and v is a real vector. * * If tau = 0, then H is taken to be the unit matrix. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': form H * C * = 'R': form C * H * * M (input) INTEGER * The number of rows of the matrix C. * * N (input) INTEGER * The number of columns of the matrix C. * * V (input) DOUBLE PRECISION array, dimension * (1 + (M-1)*abs(INCV)) if SIDE = 'L' * or (1 + (N-1)*abs(INCV)) if SIDE = 'R' * The vector v in the representation of H. V is not used if * TAU = 0. * * INCV (input) INTEGER * The increment between elements of v. INCV <> 0. * * TAU (input) DOUBLE PRECISION * The value tau in the representation of H. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by the matrix H * C if SIDE = 'L', * or C * H if SIDE = 'R'. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension * (N) if SIDE = 'L' * or (M) if SIDE = 'R' * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. External Subroutines .. EXTERNAL DGEMV, DGER * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Executable Statements .. * IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C * IF( TAU.NE.ZERO ) THEN * * w := C' * v * CALL DGEMV( 'Transpose', M, N, ONE, C, LDC, V, INCV, ZERO, $ WORK, 1 ) * * C := C - v * w' * CALL DGER( M, N, -TAU, V, INCV, WORK, 1, C, LDC ) END IF ELSE * * Form C * H * IF( TAU.NE.ZERO ) THEN * * w := C * v * CALL DGEMV( 'No transpose', M, N, ONE, C, LDC, V, INCV, $ ZERO, WORK, 1 ) * * C := C - w * v' * CALL DGER( M, N, -TAU, WORK, 1, V, INCV, C, LDC ) END IF END IF RETURN * * End of DLARF * END SUBROUTINE DLARFB( SIDE, TRANS, DIRECT, STOREV, M, N, K, V, LDV, $ T, LDT, C, LDC, WORK, LDWORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER DIRECT, SIDE, STOREV, TRANS INTEGER K, LDC, LDT, LDV, LDWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION C( LDC, * ), T( LDT, * ), V( LDV, * ), $ WORK( LDWORK, * ) * .. * * Purpose * ======= * * DLARFB applies a real block reflector H or its transpose H' to a * real m by n matrix C, from either the left or the right. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply H or H' from the Left * = 'R': apply H or H' from the Right * * TRANS (input) CHARACTER*1 * = 'N': apply H (No transpose) * = 'T': apply H' (Transpose) * * DIRECT (input) CHARACTER*1 * Indicates how H is formed from a product of elementary * reflectors * = 'F': H = H(1) H(2) . . . H(k) (Forward) * = 'B': H = H(k) . . . H(2) H(1) (Backward) * * STOREV (input) CHARACTER*1 * Indicates how the vectors which define the elementary * reflectors are stored: * = 'C': Columnwise * = 'R': Rowwise * * M (input) INTEGER * The number of rows of the matrix C. * * N (input) INTEGER * The number of columns of the matrix C. * * K (input) INTEGER * The order of the matrix T (= the number of elementary * reflectors whose product defines the block reflector). * * V (input) DOUBLE PRECISION array, dimension * (LDV,K) if STOREV = 'C' * (LDV,M) if STOREV = 'R' and SIDE = 'L' * (LDV,N) if STOREV = 'R' and SIDE = 'R' * The matrix V. See further details. * * LDV (input) INTEGER * The leading dimension of the array V. * If STOREV = 'C' and SIDE = 'L', LDV >= max(1,M); * if STOREV = 'C' and SIDE = 'R', LDV >= max(1,N); * if STOREV = 'R', LDV >= K. * * T (input) DOUBLE PRECISION array, dimension (LDT,K) * The triangular k by k matrix T in the representation of the * block reflector. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= K. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by H*C or H'*C or C*H or C*H'. * * LDC (input) INTEGER * The leading dimension of the array C. LDA >= max(1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension (LDWORK,K) * * LDWORK (input) INTEGER * The leading dimension of the array WORK. * If SIDE = 'L', LDWORK >= max(1,N); * if SIDE = 'R', LDWORK >= max(1,M). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. CHARACTER TRANST INTEGER I, J * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMM, DTRMM * .. * .. Executable Statements .. * * Quick return if possible * IF( M.LE.0 .OR. N.LE.0 ) $ RETURN * IF( LSAME( TRANS, 'N' ) ) THEN TRANST = 'T' ELSE TRANST = 'N' END IF * IF( LSAME( STOREV, 'C' ) ) THEN * IF( LSAME( DIRECT, 'F' ) ) THEN * * Let V = ( V1 ) (first K rows) * ( V2 ) * where V1 is unit lower triangular. * IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C or H' * C where C = ( C1 ) * ( C2 ) * * W := C' * V = (C1'*V1 + C2'*V2) (stored in WORK) * * W := C1' * DO 10 J = 1, K CALL DCOPY( N, C( J, 1 ), LDC, WORK( 1, J ), 1 ) 10 CONTINUE * * W := W * V1 * CALL DTRMM( 'Right', 'Lower', 'No transpose', 'Unit', N, $ K, ONE, V, LDV, WORK, LDWORK ) IF( M.GT.K ) THEN * * W := W + C2'*V2 * CALL DGEMM( 'Transpose', 'No transpose', N, K, M-K, $ ONE, C( K+1, 1 ), LDC, V( K+1, 1 ), LDV, $ ONE, WORK, LDWORK ) END IF * * W := W * T' or W * T * CALL DTRMM( 'Right', 'Upper', TRANST, 'Non-unit', N, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - V * W' * IF( M.GT.K ) THEN * * C2 := C2 - V2 * W' * CALL DGEMM( 'No transpose', 'Transpose', M-K, N, K, $ -ONE, V( K+1, 1 ), LDV, WORK, LDWORK, ONE, $ C( K+1, 1 ), LDC ) END IF * * W := W * V1' * CALL DTRMM( 'Right', 'Lower', 'Transpose', 'Unit', N, K, $ ONE, V, LDV, WORK, LDWORK ) * * C1 := C1 - W' * DO 30 J = 1, K DO 20 I = 1, N C( J, I ) = C( J, I ) - WORK( I, J ) 20 CONTINUE 30 CONTINUE * ELSE IF( LSAME( SIDE, 'R' ) ) THEN * * Form C * H or C * H' where C = ( C1 C2 ) * * W := C * V = (C1*V1 + C2*V2) (stored in WORK) * * W := C1 * DO 40 J = 1, K CALL DCOPY( M, C( 1, J ), 1, WORK( 1, J ), 1 ) 40 CONTINUE * * W := W * V1 * CALL DTRMM( 'Right', 'Lower', 'No transpose', 'Unit', M, $ K, ONE, V, LDV, WORK, LDWORK ) IF( N.GT.K ) THEN * * W := W + C2 * V2 * CALL DGEMM( 'No transpose', 'No transpose', M, K, N-K, $ ONE, C( 1, K+1 ), LDC, V( K+1, 1 ), LDV, $ ONE, WORK, LDWORK ) END IF * * W := W * T or W * T' * CALL DTRMM( 'Right', 'Upper', TRANS, 'Non-unit', M, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - W * V' * IF( N.GT.K ) THEN * * C2 := C2 - W * V2' * CALL DGEMM( 'No transpose', 'Transpose', M, N-K, K, $ -ONE, WORK, LDWORK, V( K+1, 1 ), LDV, ONE, $ C( 1, K+1 ), LDC ) END IF * * W := W * V1' * CALL DTRMM( 'Right', 'Lower', 'Transpose', 'Unit', M, K, $ ONE, V, LDV, WORK, LDWORK ) * * C1 := C1 - W * DO 60 J = 1, K DO 50 I = 1, M C( I, J ) = C( I, J ) - WORK( I, J ) 50 CONTINUE 60 CONTINUE END IF * ELSE * * Let V = ( V1 ) * ( V2 ) (last K rows) * where V2 is unit upper triangular. * IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C or H' * C where C = ( C1 ) * ( C2 ) * * W := C' * V = (C1'*V1 + C2'*V2) (stored in WORK) * * W := C2' * DO 70 J = 1, K CALL DCOPY( N, C( M-K+J, 1 ), LDC, WORK( 1, J ), 1 ) 70 CONTINUE * * W := W * V2 * CALL DTRMM( 'Right', 'Upper', 'No transpose', 'Unit', N, $ K, ONE, V( M-K+1, 1 ), LDV, WORK, LDWORK ) IF( M.GT.K ) THEN * * W := W + C1'*V1 * CALL DGEMM( 'Transpose', 'No transpose', N, K, M-K, $ ONE, C, LDC, V, LDV, ONE, WORK, LDWORK ) END IF * * W := W * T' or W * T * CALL DTRMM( 'Right', 'Lower', TRANST, 'Non-unit', N, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - V * W' * IF( M.GT.K ) THEN * * C1 := C1 - V1 * W' * CALL DGEMM( 'No transpose', 'Transpose', M-K, N, K, $ -ONE, V, LDV, WORK, LDWORK, ONE, C, LDC ) END IF * * W := W * V2' * CALL DTRMM( 'Right', 'Upper', 'Transpose', 'Unit', N, K, $ ONE, V( M-K+1, 1 ), LDV, WORK, LDWORK ) * * C2 := C2 - W' * DO 90 J = 1, K DO 80 I = 1, N C( M-K+J, I ) = C( M-K+J, I ) - WORK( I, J ) 80 CONTINUE 90 CONTINUE * ELSE IF( LSAME( SIDE, 'R' ) ) THEN * * Form C * H or C * H' where C = ( C1 C2 ) * * W := C * V = (C1*V1 + C2*V2) (stored in WORK) * * W := C2 * DO 100 J = 1, K CALL DCOPY( M, C( 1, N-K+J ), 1, WORK( 1, J ), 1 ) 100 CONTINUE * * W := W * V2 * CALL DTRMM( 'Right', 'Upper', 'No transpose', 'Unit', M, $ K, ONE, V( N-K+1, 1 ), LDV, WORK, LDWORK ) IF( N.GT.K ) THEN * * W := W + C1 * V1 * CALL DGEMM( 'No transpose', 'No transpose', M, K, N-K, $ ONE, C, LDC, V, LDV, ONE, WORK, LDWORK ) END IF * * W := W * T or W * T' * CALL DTRMM( 'Right', 'Lower', TRANS, 'Non-unit', M, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - W * V' * IF( N.GT.K ) THEN * * C1 := C1 - W * V1' * CALL DGEMM( 'No transpose', 'Transpose', M, N-K, K, $ -ONE, WORK, LDWORK, V, LDV, ONE, C, LDC ) END IF * * W := W * V2' * CALL DTRMM( 'Right', 'Upper', 'Transpose', 'Unit', M, K, $ ONE, V( N-K+1, 1 ), LDV, WORK, LDWORK ) * * C2 := C2 - W * DO 120 J = 1, K DO 110 I = 1, M C( I, N-K+J ) = C( I, N-K+J ) - WORK( I, J ) 110 CONTINUE 120 CONTINUE END IF END IF * ELSE IF( LSAME( STOREV, 'R' ) ) THEN * IF( LSAME( DIRECT, 'F' ) ) THEN * * Let V = ( V1 V2 ) (V1: first K columns) * where V1 is unit upper triangular. * IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C or H' * C where C = ( C1 ) * ( C2 ) * * W := C' * V' = (C1'*V1' + C2'*V2') (stored in WORK) * * W := C1' * DO 130 J = 1, K CALL DCOPY( N, C( J, 1 ), LDC, WORK( 1, J ), 1 ) 130 CONTINUE * * W := W * V1' * CALL DTRMM( 'Right', 'Upper', 'Transpose', 'Unit', N, K, $ ONE, V, LDV, WORK, LDWORK ) IF( M.GT.K ) THEN * * W := W + C2'*V2' * CALL DGEMM( 'Transpose', 'Transpose', N, K, M-K, ONE, $ C( K+1, 1 ), LDC, V( 1, K+1 ), LDV, ONE, $ WORK, LDWORK ) END IF * * W := W * T' or W * T * CALL DTRMM( 'Right', 'Upper', TRANST, 'Non-unit', N, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - V' * W' * IF( M.GT.K ) THEN * * C2 := C2 - V2' * W' * CALL DGEMM( 'Transpose', 'Transpose', M-K, N, K, -ONE, $ V( 1, K+1 ), LDV, WORK, LDWORK, ONE, $ C( K+1, 1 ), LDC ) END IF * * W := W * V1 * CALL DTRMM( 'Right', 'Upper', 'No transpose', 'Unit', N, $ K, ONE, V, LDV, WORK, LDWORK ) * * C1 := C1 - W' * DO 150 J = 1, K DO 140 I = 1, N C( J, I ) = C( J, I ) - WORK( I, J ) 140 CONTINUE 150 CONTINUE * ELSE IF( LSAME( SIDE, 'R' ) ) THEN * * Form C * H or C * H' where C = ( C1 C2 ) * * W := C * V' = (C1*V1' + C2*V2') (stored in WORK) * * W := C1 * DO 160 J = 1, K CALL DCOPY( M, C( 1, J ), 1, WORK( 1, J ), 1 ) 160 CONTINUE * * W := W * V1' * CALL DTRMM( 'Right', 'Upper', 'Transpose', 'Unit', M, K, $ ONE, V, LDV, WORK, LDWORK ) IF( N.GT.K ) THEN * * W := W + C2 * V2' * CALL DGEMM( 'No transpose', 'Transpose', M, K, N-K, $ ONE, C( 1, K+1 ), LDC, V( 1, K+1 ), LDV, $ ONE, WORK, LDWORK ) END IF * * W := W * T or W * T' * CALL DTRMM( 'Right', 'Upper', TRANS, 'Non-unit', M, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - W * V * IF( N.GT.K ) THEN * * C2 := C2 - W * V2 * CALL DGEMM( 'No transpose', 'No transpose', M, N-K, K, $ -ONE, WORK, LDWORK, V( 1, K+1 ), LDV, ONE, $ C( 1, K+1 ), LDC ) END IF * * W := W * V1 * CALL DTRMM( 'Right', 'Upper', 'No transpose', 'Unit', M, $ K, ONE, V, LDV, WORK, LDWORK ) * * C1 := C1 - W * DO 180 J = 1, K DO 170 I = 1, M C( I, J ) = C( I, J ) - WORK( I, J ) 170 CONTINUE 180 CONTINUE * END IF * ELSE * * Let V = ( V1 V2 ) (V2: last K columns) * where V2 is unit lower triangular. * IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C or H' * C where C = ( C1 ) * ( C2 ) * * W := C' * V' = (C1'*V1' + C2'*V2') (stored in WORK) * * W := C2' * DO 190 J = 1, K CALL DCOPY( N, C( M-K+J, 1 ), LDC, WORK( 1, J ), 1 ) 190 CONTINUE * * W := W * V2' * CALL DTRMM( 'Right', 'Lower', 'Transpose', 'Unit', N, K, $ ONE, V( 1, M-K+1 ), LDV, WORK, LDWORK ) IF( M.GT.K ) THEN * * W := W + C1'*V1' * CALL DGEMM( 'Transpose', 'Transpose', N, K, M-K, ONE, $ C, LDC, V, LDV, ONE, WORK, LDWORK ) END IF * * W := W * T' or W * T * CALL DTRMM( 'Right', 'Lower', TRANST, 'Non-unit', N, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - V' * W' * IF( M.GT.K ) THEN * * C1 := C1 - V1' * W' * CALL DGEMM( 'Transpose', 'Transpose', M-K, N, K, -ONE, $ V, LDV, WORK, LDWORK, ONE, C, LDC ) END IF * * W := W * V2 * CALL DTRMM( 'Right', 'Lower', 'No transpose', 'Unit', N, $ K, ONE, V( 1, M-K+1 ), LDV, WORK, LDWORK ) * * C2 := C2 - W' * DO 210 J = 1, K DO 200 I = 1, N C( M-K+J, I ) = C( M-K+J, I ) - WORK( I, J ) 200 CONTINUE 210 CONTINUE * ELSE IF( LSAME( SIDE, 'R' ) ) THEN * * Form C * H or C * H' where C = ( C1 C2 ) * * W := C * V' = (C1*V1' + C2*V2') (stored in WORK) * * W := C2 * DO 220 J = 1, K CALL DCOPY( M, C( 1, N-K+J ), 1, WORK( 1, J ), 1 ) 220 CONTINUE * * W := W * V2' * CALL DTRMM( 'Right', 'Lower', 'Transpose', 'Unit', M, K, $ ONE, V( 1, N-K+1 ), LDV, WORK, LDWORK ) IF( N.GT.K ) THEN * * W := W + C1 * V1' * CALL DGEMM( 'No transpose', 'Transpose', M, K, N-K, $ ONE, C, LDC, V, LDV, ONE, WORK, LDWORK ) END IF * * W := W * T or W * T' * CALL DTRMM( 'Right', 'Lower', TRANS, 'Non-unit', M, K, $ ONE, T, LDT, WORK, LDWORK ) * * C := C - W * V * IF( N.GT.K ) THEN * * C1 := C1 - W * V1 * CALL DGEMM( 'No transpose', 'No transpose', M, N-K, K, $ -ONE, WORK, LDWORK, V, LDV, ONE, C, LDC ) END IF * * W := W * V2 * CALL DTRMM( 'Right', 'Lower', 'No transpose', 'Unit', M, $ K, ONE, V( 1, N-K+1 ), LDV, WORK, LDWORK ) * * C1 := C1 - W * DO 240 J = 1, K DO 230 I = 1, M C( I, N-K+J ) = C( I, N-K+J ) - WORK( I, J ) 230 CONTINUE 240 CONTINUE * END IF * END IF END IF * RETURN * * End of DLARFB * END SUBROUTINE DLARFG( N, ALPHA, X, INCX, TAU ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER INCX, N DOUBLE PRECISION ALPHA, TAU * .. * .. Array Arguments .. DOUBLE PRECISION X( * ) * .. * * Purpose * ======= * * DLARFG generates a real elementary reflector H of order n, such * that * * H * ( alpha ) = ( beta ), H' * H = I. * ( x ) ( 0 ) * * where alpha and beta are scalars, and x is an (n-1)-element real * vector. H is represented in the form * * H = I - tau * ( 1 ) * ( 1 v' ) , * ( v ) * * where tau is a real scalar and v is a real (n-1)-element * vector. * * If the elements of x are all zero, then tau = 0 and H is taken to be * the unit matrix. * * Otherwise 1 <= tau <= 2. * * Arguments * ========= * * N (input) INTEGER * The order of the elementary reflector. * * ALPHA (input/output) DOUBLE PRECISION * On entry, the value alpha. * On exit, it is overwritten with the value beta. * * X (input/output) DOUBLE PRECISION array, dimension * (1+(N-2)*abs(INCX)) * On entry, the vector x. * On exit, it is overwritten with the vector v. * * INCX (input) INTEGER * The increment between elements of X. INCX > 0. * * TAU (output) DOUBLE PRECISION * The value tau. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER J, KNT DOUBLE PRECISION BETA, RSAFMN, SAFMIN, XNORM * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLAPY2, DNRM2 EXTERNAL DLAMCH, DLAPY2, DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN * .. * .. External Subroutines .. EXTERNAL DSCAL * .. * .. Executable Statements .. * IF( N.LE.1 ) THEN TAU = ZERO RETURN END IF * XNORM = DNRM2( N-1, X, INCX ) * IF( XNORM.EQ.ZERO ) THEN * * H = I * TAU = ZERO ELSE * * general case * BETA = -SIGN( DLAPY2( ALPHA, XNORM ), ALPHA ) SAFMIN = DLAMCH( 'S' ) / DLAMCH( 'E' ) IF( ABS( BETA ).LT.SAFMIN ) THEN * * XNORM, BETA may be inaccurate; scale X and recompute them * RSAFMN = ONE / SAFMIN KNT = 0 10 CONTINUE KNT = KNT + 1 CALL DSCAL( N-1, RSAFMN, X, INCX ) BETA = BETA*RSAFMN ALPHA = ALPHA*RSAFMN IF( ABS( BETA ).LT.SAFMIN ) $ GO TO 10 * * New BETA is at most 1, at least SAFMIN * XNORM = DNRM2( N-1, X, INCX ) BETA = -SIGN( DLAPY2( ALPHA, XNORM ), ALPHA ) TAU = ( BETA-ALPHA ) / BETA CALL DSCAL( N-1, ONE / ( ALPHA-BETA ), X, INCX ) * * If ALPHA is subnormal, it may lose relative accuracy * ALPHA = BETA DO 20 J = 1, KNT ALPHA = ALPHA*SAFMIN 20 CONTINUE ELSE TAU = ( BETA-ALPHA ) / BETA CALL DSCAL( N-1, ONE / ( ALPHA-BETA ), X, INCX ) ALPHA = BETA END IF END IF * RETURN * * End of DLARFG * END SUBROUTINE DLARFT( DIRECT, STOREV, N, K, V, LDV, TAU, T, LDT ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER DIRECT, STOREV INTEGER K, LDT, LDV, N * .. * .. Array Arguments .. DOUBLE PRECISION T( LDT, * ), TAU( * ), V( LDV, * ) * .. * * Purpose * ======= * * DLARFT forms the triangular factor T of a real block reflector H * of order n, which is defined as a product of k elementary reflectors. * * If DIRECT = 'F', H = H(1) H(2) . . . H(k) and T is upper triangular; * * If DIRECT = 'B', H = H(k) . . . H(2) H(1) and T is lower triangular. * * If STOREV = 'C', the vector which defines the elementary reflector * H(i) is stored in the i-th column of the array V, and * * H = I - V * T * V' * * If STOREV = 'R', the vector which defines the elementary reflector * H(i) is stored in the i-th row of the array V, and * * H = I - V' * T * V * * Arguments * ========= * * DIRECT (input) CHARACTER*1 * Specifies the order in which the elementary reflectors are * multiplied to form the block reflector: * = 'F': H = H(1) H(2) . . . H(k) (Forward) * = 'B': H = H(k) . . . H(2) H(1) (Backward) * * STOREV (input) CHARACTER*1 * Specifies how the vectors which define the elementary * reflectors are stored (see also Further Details): * = 'C': columnwise * = 'R': rowwise * * N (input) INTEGER * The order of the block reflector H. N >= 0. * * K (input) INTEGER * The order of the triangular factor T (= the number of * elementary reflectors). K >= 1. * * V (input/output) DOUBLE PRECISION array, dimension * (LDV,K) if STOREV = 'C' * (LDV,N) if STOREV = 'R' * The matrix V. See further details. * * LDV (input) INTEGER * The leading dimension of the array V. * If STOREV = 'C', LDV >= max(1,N); if STOREV = 'R', LDV >= K. * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i). * * T (output) DOUBLE PRECISION array, dimension (LDT,K) * The k by k triangular factor T of the block reflector. * If DIRECT = 'F', T is upper triangular; if DIRECT = 'B', T is * lower triangular. The rest of the array is not used. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= K. * * Further Details * =============== * * The shape of the matrix V and the storage of the vectors which define * the H(i) is best illustrated by the following example with n = 5 and * k = 3. The elements equal to 1 are not stored; the corresponding * array elements are modified but restored on exit. The rest of the * array is not used. * * DIRECT = 'F' and STOREV = 'C': DIRECT = 'F' and STOREV = 'R': * * V = ( 1 ) V = ( 1 v1 v1 v1 v1 ) * ( v1 1 ) ( 1 v2 v2 v2 ) * ( v1 v2 1 ) ( 1 v3 v3 ) * ( v1 v2 v3 ) * ( v1 v2 v3 ) * * DIRECT = 'B' and STOREV = 'C': DIRECT = 'B' and STOREV = 'R': * * V = ( v1 v2 v3 ) V = ( v1 v1 1 ) * ( v1 v2 v3 ) ( v2 v2 v2 1 ) * ( 1 v2 v3 ) ( v3 v3 v3 v3 1 ) * ( 1 v3 ) * ( 1 ) * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J DOUBLE PRECISION VII * .. * .. External Subroutines .. EXTERNAL DGEMV, DTRMV * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Executable Statements .. * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( LSAME( DIRECT, 'F' ) ) THEN DO 20 I = 1, K IF( TAU( I ).EQ.ZERO ) THEN * * H(i) = I * DO 10 J = 1, I T( J, I ) = ZERO 10 CONTINUE ELSE * * general case * VII = V( I, I ) V( I, I ) = ONE IF( LSAME( STOREV, 'C' ) ) THEN * * T(1:i-1,i) := - tau(i) * V(i:n,1:i-1)' * V(i:n,i) * CALL DGEMV( 'Transpose', N-I+1, I-1, -TAU( I ), $ V( I, 1 ), LDV, V( I, I ), 1, ZERO, $ T( 1, I ), 1 ) ELSE * * T(1:i-1,i) := - tau(i) * V(1:i-1,i:n) * V(i,i:n)' * CALL DGEMV( 'No transpose', I-1, N-I+1, -TAU( I ), $ V( 1, I ), LDV, V( I, I ), LDV, ZERO, $ T( 1, I ), 1 ) END IF V( I, I ) = VII * * T(1:i-1,i) := T(1:i-1,1:i-1) * T(1:i-1,i) * CALL DTRMV( 'Upper', 'No transpose', 'Non-unit', I-1, T, $ LDT, T( 1, I ), 1 ) T( I, I ) = TAU( I ) END IF 20 CONTINUE ELSE DO 40 I = K, 1, -1 IF( TAU( I ).EQ.ZERO ) THEN * * H(i) = I * DO 30 J = I, K T( J, I ) = ZERO 30 CONTINUE ELSE * * general case * IF( I.LT.K ) THEN IF( LSAME( STOREV, 'C' ) ) THEN VII = V( N-K+I, I ) V( N-K+I, I ) = ONE * * T(i+1:k,i) := * - tau(i) * V(1:n-k+i,i+1:k)' * V(1:n-k+i,i) * CALL DGEMV( 'Transpose', N-K+I, K-I, -TAU( I ), $ V( 1, I+1 ), LDV, V( 1, I ), 1, ZERO, $ T( I+1, I ), 1 ) V( N-K+I, I ) = VII ELSE VII = V( I, N-K+I ) V( I, N-K+I ) = ONE * * T(i+1:k,i) := * - tau(i) * V(i+1:k,1:n-k+i) * V(i,1:n-k+i)' * CALL DGEMV( 'No transpose', K-I, N-K+I, -TAU( I ), $ V( I+1, 1 ), LDV, V( I, 1 ), LDV, ZERO, $ T( I+1, I ), 1 ) V( I, N-K+I ) = VII END IF * * T(i+1:k,i) := T(i+1:k,i+1:k) * T(i+1:k,i) * CALL DTRMV( 'Lower', 'No transpose', 'Non-unit', K-I, $ T( I+1, I+1 ), LDT, T( I+1, I ), 1 ) END IF T( I, I ) = TAU( I ) END IF 40 CONTINUE END IF RETURN * * End of DLARFT * END SUBROUTINE DLARFX( SIDE, M, N, V, TAU, C, LDC, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER SIDE INTEGER LDC, M, N DOUBLE PRECISION TAU * .. * .. Array Arguments .. DOUBLE PRECISION C( LDC, * ), V( * ), WORK( * ) * .. * * Purpose * ======= * * DLARFX applies a real elementary reflector H to a real m by n * matrix C, from either the left or the right. H is represented in the * form * * H = I - tau * v * v' * * where tau is a real scalar and v is a real vector. * * If tau = 0, then H is taken to be the unit matrix * * This version uses inline code if H has order < 11. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': form H * C * = 'R': form C * H * * M (input) INTEGER * The number of rows of the matrix C. * * N (input) INTEGER * The number of columns of the matrix C. * * V (input) DOUBLE PRECISION array, dimension (M) if SIDE = 'L' * or (N) if SIDE = 'R' * The vector v in the representation of H. * * TAU (input) DOUBLE PRECISION * The value tau in the representation of H. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by the matrix H * C if SIDE = 'L', * or C * H if SIDE = 'R'. * * LDC (input) INTEGER * The leading dimension of the array C. LDA >= (1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension * (N) if SIDE = 'L' * or (M) if SIDE = 'R' * WORK is not referenced if H has order < 11. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER J DOUBLE PRECISION SUM, T1, T10, T2, T3, T4, T5, T6, T7, T8, T9, $ V1, V10, V2, V3, V4, V5, V6, V7, V8, V9 * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DGEMV, DGER * .. * .. Executable Statements .. * IF( TAU.EQ.ZERO ) $ RETURN IF( LSAME( SIDE, 'L' ) ) THEN * * Form H * C, where H has order m. * GO TO ( 10, 30, 50, 70, 90, 110, 130, 150, $ 170, 190 )M * * Code for general M * * w := C'*v * CALL DGEMV( 'Transpose', M, N, ONE, C, LDC, V, 1, ZERO, WORK, $ 1 ) * * C := C - tau * v * w' * CALL DGER( M, N, -TAU, V, 1, WORK, 1, C, LDC ) GO TO 410 10 CONTINUE * * Special code for 1 x 1 Householder * T1 = ONE - TAU*V( 1 )*V( 1 ) DO 20 J = 1, N C( 1, J ) = T1*C( 1, J ) 20 CONTINUE GO TO 410 30 CONTINUE * * Special code for 2 x 2 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 DO 40 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 40 CONTINUE GO TO 410 50 CONTINUE * * Special code for 3 x 3 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 DO 60 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 60 CONTINUE GO TO 410 70 CONTINUE * * Special code for 4 x 4 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 DO 80 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 80 CONTINUE GO TO 410 90 CONTINUE * * Special code for 5 x 5 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 DO 100 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 100 CONTINUE GO TO 410 110 CONTINUE * * Special code for 6 x 6 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 DO 120 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) + V6*C( 6, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 C( 6, J ) = C( 6, J ) - SUM*T6 120 CONTINUE GO TO 410 130 CONTINUE * * Special code for 7 x 7 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 DO 140 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) + V6*C( 6, J ) + $ V7*C( 7, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 C( 6, J ) = C( 6, J ) - SUM*T6 C( 7, J ) = C( 7, J ) - SUM*T7 140 CONTINUE GO TO 410 150 CONTINUE * * Special code for 8 x 8 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 DO 160 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) + V6*C( 6, J ) + $ V7*C( 7, J ) + V8*C( 8, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 C( 6, J ) = C( 6, J ) - SUM*T6 C( 7, J ) = C( 7, J ) - SUM*T7 C( 8, J ) = C( 8, J ) - SUM*T8 160 CONTINUE GO TO 410 170 CONTINUE * * Special code for 9 x 9 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 V9 = V( 9 ) T9 = TAU*V9 DO 180 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) + V6*C( 6, J ) + $ V7*C( 7, J ) + V8*C( 8, J ) + V9*C( 9, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 C( 6, J ) = C( 6, J ) - SUM*T6 C( 7, J ) = C( 7, J ) - SUM*T7 C( 8, J ) = C( 8, J ) - SUM*T8 C( 9, J ) = C( 9, J ) - SUM*T9 180 CONTINUE GO TO 410 190 CONTINUE * * Special code for 10 x 10 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 V9 = V( 9 ) T9 = TAU*V9 V10 = V( 10 ) T10 = TAU*V10 DO 200 J = 1, N SUM = V1*C( 1, J ) + V2*C( 2, J ) + V3*C( 3, J ) + $ V4*C( 4, J ) + V5*C( 5, J ) + V6*C( 6, J ) + $ V7*C( 7, J ) + V8*C( 8, J ) + V9*C( 9, J ) + $ V10*C( 10, J ) C( 1, J ) = C( 1, J ) - SUM*T1 C( 2, J ) = C( 2, J ) - SUM*T2 C( 3, J ) = C( 3, J ) - SUM*T3 C( 4, J ) = C( 4, J ) - SUM*T4 C( 5, J ) = C( 5, J ) - SUM*T5 C( 6, J ) = C( 6, J ) - SUM*T6 C( 7, J ) = C( 7, J ) - SUM*T7 C( 8, J ) = C( 8, J ) - SUM*T8 C( 9, J ) = C( 9, J ) - SUM*T9 C( 10, J ) = C( 10, J ) - SUM*T10 200 CONTINUE GO TO 410 ELSE * * Form C * H, where H has order n. * GO TO ( 210, 230, 250, 270, 290, 310, 330, 350, $ 370, 390 )N * * Code for general N * * w := C * v * CALL DGEMV( 'No transpose', M, N, ONE, C, LDC, V, 1, ZERO, $ WORK, 1 ) * * C := C - tau * w * v' * CALL DGER( M, N, -TAU, WORK, 1, V, 1, C, LDC ) GO TO 410 210 CONTINUE * * Special code for 1 x 1 Householder * T1 = ONE - TAU*V( 1 )*V( 1 ) DO 220 J = 1, M C( J, 1 ) = T1*C( J, 1 ) 220 CONTINUE GO TO 410 230 CONTINUE * * Special code for 2 x 2 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 DO 240 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 240 CONTINUE GO TO 410 250 CONTINUE * * Special code for 3 x 3 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 DO 260 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 260 CONTINUE GO TO 410 270 CONTINUE * * Special code for 4 x 4 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 DO 280 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 280 CONTINUE GO TO 410 290 CONTINUE * * Special code for 5 x 5 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 DO 300 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 300 CONTINUE GO TO 410 310 CONTINUE * * Special code for 6 x 6 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 DO 320 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) + V6*C( J, 6 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 C( J, 6 ) = C( J, 6 ) - SUM*T6 320 CONTINUE GO TO 410 330 CONTINUE * * Special code for 7 x 7 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 DO 340 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) + V6*C( J, 6 ) + $ V7*C( J, 7 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 C( J, 6 ) = C( J, 6 ) - SUM*T6 C( J, 7 ) = C( J, 7 ) - SUM*T7 340 CONTINUE GO TO 410 350 CONTINUE * * Special code for 8 x 8 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 DO 360 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) + V6*C( J, 6 ) + $ V7*C( J, 7 ) + V8*C( J, 8 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 C( J, 6 ) = C( J, 6 ) - SUM*T6 C( J, 7 ) = C( J, 7 ) - SUM*T7 C( J, 8 ) = C( J, 8 ) - SUM*T8 360 CONTINUE GO TO 410 370 CONTINUE * * Special code for 9 x 9 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 V9 = V( 9 ) T9 = TAU*V9 DO 380 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) + V6*C( J, 6 ) + $ V7*C( J, 7 ) + V8*C( J, 8 ) + V9*C( J, 9 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 C( J, 6 ) = C( J, 6 ) - SUM*T6 C( J, 7 ) = C( J, 7 ) - SUM*T7 C( J, 8 ) = C( J, 8 ) - SUM*T8 C( J, 9 ) = C( J, 9 ) - SUM*T9 380 CONTINUE GO TO 410 390 CONTINUE * * Special code for 10 x 10 Householder * V1 = V( 1 ) T1 = TAU*V1 V2 = V( 2 ) T2 = TAU*V2 V3 = V( 3 ) T3 = TAU*V3 V4 = V( 4 ) T4 = TAU*V4 V5 = V( 5 ) T5 = TAU*V5 V6 = V( 6 ) T6 = TAU*V6 V7 = V( 7 ) T7 = TAU*V7 V8 = V( 8 ) T8 = TAU*V8 V9 = V( 9 ) T9 = TAU*V9 V10 = V( 10 ) T10 = TAU*V10 DO 400 J = 1, M SUM = V1*C( J, 1 ) + V2*C( J, 2 ) + V3*C( J, 3 ) + $ V4*C( J, 4 ) + V5*C( J, 5 ) + V6*C( J, 6 ) + $ V7*C( J, 7 ) + V8*C( J, 8 ) + V9*C( J, 9 ) + $ V10*C( J, 10 ) C( J, 1 ) = C( J, 1 ) - SUM*T1 C( J, 2 ) = C( J, 2 ) - SUM*T2 C( J, 3 ) = C( J, 3 ) - SUM*T3 C( J, 4 ) = C( J, 4 ) - SUM*T4 C( J, 5 ) = C( J, 5 ) - SUM*T5 C( J, 6 ) = C( J, 6 ) - SUM*T6 C( J, 7 ) = C( J, 7 ) - SUM*T7 C( J, 8 ) = C( J, 8 ) - SUM*T8 C( J, 9 ) = C( J, 9 ) - SUM*T9 C( J, 10 ) = C( J, 10 ) - SUM*T10 400 CONTINUE GO TO 410 END IF 410 CONTINUE RETURN * * End of DLARFX * END SUBROUTINE DLARTG( F, G, CS, SN, R ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. DOUBLE PRECISION CS, F, G, R, SN * .. * * Purpose * ======= * * DLARTG generate a plane rotation so that * * [ CS SN ] . [ F ] = [ R ] where CS**2 + SN**2 = 1. * [ -SN CS ] [ G ] [ 0 ] * * This is a slower, more accurate version of the BLAS1 routine DROTG, * with the following other differences: * F and G are unchanged on return. * If G=0, then CS=1 and SN=0. * If F=0 and (G .ne. 0), then CS=0 and SN=1 without doing any * floating point operations (saves work in DBDSQR when * there are zeros on the diagonal). * * If F exceeds G in magnitude, CS will be positive. * * Arguments * ========= * * F (input) DOUBLE PRECISION * The first component of vector to be rotated. * * G (input) DOUBLE PRECISION * The second component of vector to be rotated. * * CS (output) DOUBLE PRECISION * The cosine of the rotation. * * SN (output) DOUBLE PRECISION * The sine of the rotation. * * R (output) DOUBLE PRECISION * The nonzero component of the rotated vector. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) * .. * .. Local Scalars .. LOGICAL FIRST INTEGER COUNT, I DOUBLE PRECISION EPS, F1, G1, SAFMIN, SAFMN2, SAFMX2, SCALE * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, INT, LOG, MAX, SQRT * .. * .. Save statement .. SAVE FIRST, SAFMX2, SAFMIN, SAFMN2 * .. * .. Data statements .. DATA FIRST / .TRUE. / * .. * .. Executable Statements .. * IF( FIRST ) THEN FIRST = .FALSE. SAFMIN = DLAMCH( 'S' ) EPS = DLAMCH( 'E' ) SAFMN2 = DLAMCH( 'B' )**INT( LOG( SAFMIN / EPS ) / $ LOG( DLAMCH( 'B' ) ) / TWO ) SAFMX2 = ONE / SAFMN2 END IF IF( G.EQ.ZERO ) THEN CS = ONE SN = ZERO R = F ELSE IF( F.EQ.ZERO ) THEN CS = ZERO SN = ONE R = G ELSE F1 = F G1 = G SCALE = MAX( ABS( F1 ), ABS( G1 ) ) IF( SCALE.GE.SAFMX2 ) THEN COUNT = 0 10 CONTINUE COUNT = COUNT + 1 F1 = F1*SAFMN2 G1 = G1*SAFMN2 SCALE = MAX( ABS( F1 ), ABS( G1 ) ) IF( SCALE.GE.SAFMX2 ) $ GO TO 10 R = SQRT( F1**2+G1**2 ) CS = F1 / R SN = G1 / R DO 20 I = 1, COUNT R = R*SAFMX2 20 CONTINUE ELSE IF( SCALE.LE.SAFMN2 ) THEN COUNT = 0 30 CONTINUE COUNT = COUNT + 1 F1 = F1*SAFMX2 G1 = G1*SAFMX2 SCALE = MAX( ABS( F1 ), ABS( G1 ) ) IF( SCALE.LE.SAFMN2 ) $ GO TO 30 R = SQRT( F1**2+G1**2 ) CS = F1 / R SN = G1 / R DO 40 I = 1, COUNT R = R*SAFMN2 40 CONTINUE ELSE R = SQRT( F1**2+G1**2 ) CS = F1 / R SN = G1 / R END IF IF( ABS( F ).GT.ABS( G ) .AND. CS.LT.ZERO ) THEN CS = -CS SN = -SN R = -R END IF END IF RETURN * * End of DLARTG * END SUBROUTINE DLAS2( F, G, H, SSMIN, SSMAX ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. DOUBLE PRECISION F, G, H, SSMAX, SSMIN * .. * * Purpose * ======= * * DLAS2 computes the singular values of the 2-by-2 matrix * [ F G ] * [ 0 H ]. * On return, SSMIN is the smaller singular value and SSMAX is the * larger singular value. * * Arguments * ========= * * F (input) DOUBLE PRECISION * The (1,1) element of the 2-by-2 matrix. * * G (input) DOUBLE PRECISION * The (1,2) element of the 2-by-2 matrix. * * H (input) DOUBLE PRECISION * The (2,2) element of the 2-by-2 matrix. * * SSMIN (output) DOUBLE PRECISION * The smaller singular value. * * SSMAX (output) DOUBLE PRECISION * The larger singular value. * * Further Details * =============== * * Barring over/underflow, all output quantities are correct to within * a few units in the last place (ulps), even in the absence of a guard * digit in addition/subtraction. * * In IEEE arithmetic, the code works correctly if one matrix element is * infinite. * * Overflow will not occur unless the largest singular value itself * overflows, or is within a few ulps of overflow. (On machines with * partial overflow, like the Cray, overflow may occur if the largest * singular value is within a factor of 2 of overflow.) * * Underflow is harmless if underflow is gradual. Otherwise, results * may correspond to a matrix modified by perturbations of size near * the underflow threshold. * * ==================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) * .. * .. Local Scalars .. DOUBLE PRECISION AS, AT, AU, C, FA, FHMN, FHMX, GA, HA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Executable Statements .. * FA = ABS( F ) GA = ABS( G ) HA = ABS( H ) FHMN = MIN( FA, HA ) FHMX = MAX( FA, HA ) IF( FHMN.EQ.ZERO ) THEN SSMIN = ZERO IF( FHMX.EQ.ZERO ) THEN SSMAX = GA ELSE SSMAX = MAX( FHMX, GA )*SQRT( ONE+ $ ( MIN( FHMX, GA ) / MAX( FHMX, GA ) )**2 ) END IF ELSE IF( GA.LT.FHMX ) THEN AS = ONE + FHMN / FHMX AT = ( FHMX-FHMN ) / FHMX AU = ( GA / FHMX )**2 C = TWO / ( SQRT( AS*AS+AU )+SQRT( AT*AT+AU ) ) SSMIN = FHMN*C SSMAX = FHMX / C ELSE AU = FHMX / GA IF( AU.EQ.ZERO ) THEN * * Avoid possible harmful underflow if exponent range * asymmetric (true SSMIN may not underflow even if * AU underflows) * SSMIN = ( FHMN*FHMX ) / GA SSMAX = GA ELSE AS = ONE + FHMN / FHMX AT = ( FHMX-FHMN ) / FHMX C = ONE / ( SQRT( ONE+( AS*AU )**2 )+ $ SQRT( ONE+( AT*AU )**2 ) ) SSMIN = ( FHMN*C )*AU SSMIN = SSMIN + SSMIN SSMAX = GA / ( C+C ) END IF END IF END IF RETURN * * End of DLAS2 * END SUBROUTINE DLASCL( TYPE, KL, KU, CFROM, CTO, M, N, A, LDA, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER TYPE INTEGER INFO, KL, KU, LDA, M, N DOUBLE PRECISION CFROM, CTO * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ) * .. * * Purpose * ======= * * DLASCL multiplies the M by N real matrix A by the real scalar * CTO/CFROM. This is done without over/underflow as long as the final * result CTO*A(I,J)/CFROM does not over/underflow. TYPE specifies that * A may be full, upper triangular, lower triangular, upper Hessenberg, * or banded. * * Arguments * ========= * * TYPE (input) CHARACTER*1 * TYPE indices the storage type of the input matrix. * = 'G': A is a full matrix. * = 'L': A is a lower triangular matrix. * = 'U': A is an upper triangular matrix. * = 'H': A is an upper Hessenberg matrix. * = 'B': A is a symmetric band matrix with lower bandwidth KL * and upper bandwidth KU and with the only the lower * half stored. * = 'Q': A is a symmetric band matrix with lower bandwidth KL * and upper bandwidth KU and with the only the upper * half stored. * = 'Z': A is a band matrix with lower bandwidth KL and upper * bandwidth KU. * * KL (input) INTEGER * The lower bandwidth of A. Referenced only if TYPE = 'B', * 'Q' or 'Z'. * * KU (input) INTEGER * The upper bandwidth of A. Referenced only if TYPE = 'B', * 'Q' or 'Z'. * * CFROM (input) DOUBLE PRECISION * CTO (input) DOUBLE PRECISION * The matrix A is multiplied by CTO/CFROM. A(I,J) is computed * without over/underflow if the final result CTO*A(I,J)/CFROM * can be represented without over/underflow. CFROM must be * nonzero. * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,M) * The matrix to be multiplied by CTO/CFROM. See TYPE for the * storage type. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * INFO (output) INTEGER * 0 - successful exit * <0 - if INFO = -i, the i-th argument had an illegal value. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL DONE INTEGER I, ITYPE, J, K1, K2, K3, K4 DOUBLE PRECISION BIGNUM, CFROM1, CFROMC, CTO1, CTOC, MUL, SMLNUM * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH EXTERNAL LSAME, DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 * IF( LSAME( TYPE, 'G' ) ) THEN ITYPE = 0 ELSE IF( LSAME( TYPE, 'L' ) ) THEN ITYPE = 1 ELSE IF( LSAME( TYPE, 'U' ) ) THEN ITYPE = 2 ELSE IF( LSAME( TYPE, 'H' ) ) THEN ITYPE = 3 ELSE IF( LSAME( TYPE, 'B' ) ) THEN ITYPE = 4 ELSE IF( LSAME( TYPE, 'Q' ) ) THEN ITYPE = 5 ELSE IF( LSAME( TYPE, 'Z' ) ) THEN ITYPE = 6 ELSE ITYPE = -1 END IF * IF( ITYPE.EQ.-1 ) THEN INFO = -1 ELSE IF( CFROM.EQ.ZERO ) THEN INFO = -4 ELSE IF( M.LT.0 ) THEN INFO = -6 ELSE IF( N.LT.0 .OR. ( ITYPE.EQ.4 .AND. N.NE.M ) .OR. $ ( ITYPE.EQ.5 .AND. N.NE.M ) ) THEN INFO = -7 ELSE IF( ITYPE.LE.3 .AND. LDA.LT.MAX( 1, M ) ) THEN INFO = -9 ELSE IF( ITYPE.GE.4 ) THEN IF( KL.LT.0 .OR. KL.GT.MAX( M-1, 0 ) ) THEN INFO = -2 ELSE IF( KU.LT.0 .OR. KU.GT.MAX( N-1, 0 ) .OR. $ ( ( ITYPE.EQ.4 .OR. ITYPE.EQ.5 ) .AND. KL.NE.KU ) ) $ THEN INFO = -3 ELSE IF( ( ITYPE.EQ.4 .AND. LDA.LT.KL+1 ) .OR. $ ( ITYPE.EQ.5 .AND. LDA.LT.KU+1 ) .OR. $ ( ITYPE.EQ.6 .AND. LDA.LT.2*KL+KU+1 ) ) THEN INFO = -9 END IF END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASCL', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 .OR. M.EQ.0 ) $ RETURN * * Get machine parameters * SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM * CFROMC = CFROM CTOC = CTO * 10 CONTINUE CFROM1 = CFROMC*SMLNUM CTO1 = CTOC / BIGNUM IF( ABS( CFROM1 ).GT.ABS( CTOC ) .AND. CTOC.NE.ZERO ) THEN MUL = SMLNUM DONE = .FALSE. CFROMC = CFROM1 ELSE IF( ABS( CTO1 ).GT.ABS( CFROMC ) ) THEN MUL = BIGNUM DONE = .FALSE. CTOC = CTO1 ELSE MUL = CTOC / CFROMC DONE = .TRUE. END IF * IF( ITYPE.EQ.0 ) THEN * * Full matrix * DO 30 J = 1, N DO 20 I = 1, M A( I, J ) = A( I, J )*MUL 20 CONTINUE 30 CONTINUE * ELSE IF( ITYPE.EQ.1 ) THEN * * Lower triangular matrix * DO 50 J = 1, N DO 40 I = J, M A( I, J ) = A( I, J )*MUL 40 CONTINUE 50 CONTINUE * ELSE IF( ITYPE.EQ.2 ) THEN * * Upper triangular matrix * DO 70 J = 1, N DO 60 I = 1, MIN( J, M ) A( I, J ) = A( I, J )*MUL 60 CONTINUE 70 CONTINUE * ELSE IF( ITYPE.EQ.3 ) THEN * * Upper Hessenberg matrix * DO 90 J = 1, N DO 80 I = 1, MIN( J+1, M ) A( I, J ) = A( I, J )*MUL 80 CONTINUE 90 CONTINUE * ELSE IF( ITYPE.EQ.4 ) THEN * * Lower half of a symmetric band matrix * K3 = KL + 1 K4 = N + 1 DO 110 J = 1, N DO 100 I = 1, MIN( K3, K4-J ) A( I, J ) = A( I, J )*MUL 100 CONTINUE 110 CONTINUE * ELSE IF( ITYPE.EQ.5 ) THEN * * Upper half of a symmetric band matrix * K1 = KU + 2 K3 = KU + 1 DO 130 J = 1, N DO 120 I = MAX( K1-J, 1 ), K3 A( I, J ) = A( I, J )*MUL 120 CONTINUE 130 CONTINUE * ELSE IF( ITYPE.EQ.6 ) THEN * * Band matrix * K1 = KL + KU + 2 K2 = KL + 1 K3 = 2*KL + KU + 1 K4 = KL + KU + 1 + M DO 150 J = 1, N DO 140 I = MAX( K1-J, K2 ), MIN( K3, K4-J ) A( I, J ) = A( I, J )*MUL 140 CONTINUE 150 CONTINUE * END IF * IF( .NOT.DONE ) $ GO TO 10 * RETURN * * End of DLASCL * END SUBROUTINE DLASET( UPLO, M, N, ALPHA, BETA, A, LDA ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER LDA, M, N DOUBLE PRECISION ALPHA, BETA * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ) * .. * * Purpose * ======= * * DLASET initializes an m-by-n matrix A to BETA on the diagonal and * ALPHA on the offdiagonals. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * Specifies the part of the matrix A to be set. * = 'U': Upper triangular part is set; the strictly lower * triangular part of A is not changed. * = 'L': Lower triangular part is set; the strictly upper * triangular part of A is not changed. * Otherwise: All of the matrix A is set. * * M (input) INTEGER * The number of rows of the matrix A. M >= 0. * * N (input) INTEGER * The number of columns of the matrix A. N >= 0. * * ALPHA (input) DOUBLE PRECISION * The constant to which the offdiagonal elements are to be set. * * BETA (input) DOUBLE PRECISION * The constant to which the diagonal elements are to be set. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On exit, the leading m-by-n submatrix of A is set as follows: * * if UPLO = 'U', A(i,j) = ALPHA, 1<=i<=j-1, 1<=j<=n, * if UPLO = 'L', A(i,j) = ALPHA, j+1<=i<=m, 1<=j<=n, * otherwise, A(i,j) = ALPHA, 1<=i<=m, 1<=j<=n, i.ne.j, * * and, for all UPLO, A(i,i) = BETA, 1<=i<=min(m,n). * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * ===================================================================== * * .. Local Scalars .. INTEGER I, J * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * IF( LSAME( UPLO, 'U' ) ) THEN * * Set the strictly upper triangular or trapezoidal part of the * array to ALPHA. * DO 20 J = 2, N DO 10 I = 1, MIN( J-1, M ) A( I, J ) = ALPHA 10 CONTINUE 20 CONTINUE * ELSE IF( LSAME( UPLO, 'L' ) ) THEN * * Set the strictly lower triangular or trapezoidal part of the * array to ALPHA. * DO 40 J = 1, MIN( M, N ) DO 30 I = J + 1, M A( I, J ) = ALPHA 30 CONTINUE 40 CONTINUE * ELSE * * Set the leading m-by-n submatrix to ALPHA. * DO 60 J = 1, N DO 50 I = 1, M A( I, J ) = ALPHA 50 CONTINUE 60 CONTINUE END IF * * Set the first min(M,N) diagonal elements to BETA. * DO 70 I = 1, MIN( M, N ) A( I, I ) = BETA 70 CONTINUE * RETURN * * End of DLASET * END SUBROUTINE DLASQ1( N, D, E, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ), WORK( * ) * .. * * Purpose * ======= * * DLASQ1 computes the singular values of a real N-by-N bidiagonal * matrix with diagonal D and off-diagonal E. The singular values * are computed to high relative accuracy, in the absence of * denormalization, underflow and overflow. The algorithm was first * presented in * * "Accurate singular values and differential qd algorithms" by K. V. * Fernando and B. N. Parlett, Numer. Math., Vol-67, No. 2, pp. 191-230, * 1994, * * and the present implementation is described in "An implementation of * dqds", LAPACK technical report. * * Note : DLASQ1 works only on machines which follow ieee-754 * floating-point standard in their handling of infinities and NaNs. * Normal execution of DLASQ1 may create NaNs and infinities and hence * may abort due to a floating point exception in environments which * do not conform to the ieee standard. * * Arguments * ========= * * N (input) INTEGER * The number of rows and columns in the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, D contains the diagonal elements of the * bidiagonal matrix whose SVD is desired. On normal exit, * D contains the singular values in decreasing order. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, elements E(1:N-1) contain the off-diagonal elements * of the bidiagonal matrix whose SVD is desired. * On exit, E is overwritten. * * WORK (workspace) DOUBLE PRECISION array, dimension (4*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: the algorithm failed * = 1, a split was marked by a positive value in E * = 2, current block of Z not diagonalized after 30*N * iterations (in inner while loop) * = 3, termination criterion of outer while loop not met * (program created more than N unreduced blocks) * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) * .. * .. Local Scalars .. INTEGER I, IINFO DOUBLE PRECISION EPS, SCALE, SFMIN, SIGMN, SIGMX * .. * .. External Subroutines .. EXTERNAL DCOPY, DLAS2, DLASCL, DLASQ2, DLASRT, XERBLA * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * INFO = 0 IF( N.LT.0 ) THEN INFO = -2 CALL XERBLA( 'DLASQ1', -INFO ) RETURN ELSE IF( N.EQ.0 ) THEN RETURN ELSE IF( N.EQ.1 ) THEN D( 1 ) = ABS( D( 1 ) ) RETURN ELSE IF( N.EQ.2 ) THEN CALL DLAS2( D( 1 ), E( 1 ), D( 2 ), SIGMN, SIGMX ) D( 1 ) = SIGMX D( 2 ) = SIGMN RETURN END IF * * Estimate the largest singular value. * SIGMX = ZERO DO 10 I = 1, N - 1 D( I ) = ABS( D( I ) ) SIGMX = MAX( SIGMX, ABS( E( I ) ) ) 10 CONTINUE D( N ) = ABS( D( N ) ) * * Early return if SIGMX is zero (matrix is already diagonal). * IF( SIGMX.EQ.ZERO ) THEN CALL DLASRT( 'D', N, D, IINFO ) GO TO 50 END IF * DO 20 I = 1, N SIGMX = MAX( SIGMX, D( I ) ) 20 CONTINUE * * Copy D and E into WORK (in the Z format) and scale (squaring the * input data makes scaling by a power of the radix pointless). * EPS = DLAMCH( 'Precision' ) SFMIN = DLAMCH( 'Safe minimum' ) SCALE = SQRT( EPS / SFMIN ) CALL DCOPY( N, D, 1, WORK( 1 ), 2 ) CALL DCOPY( N-1, E, 1, WORK( 2 ), 2 ) CALL DLASCL( 'G', 0, 0, SIGMX, SCALE, 2*N-1, 1, WORK, 2*N-1, $ IINFO ) * * Compute the q's and e's. * DO 30 I = 1, 2*N - 1 WORK( I ) = WORK( I )**2 30 CONTINUE WORK( 2*N ) = ZERO * CALL DLASQ2( N, WORK, INFO ) * IF( INFO.EQ.0 ) THEN DO 40 I = 1, N D( I ) = SQRT( WORK( I ) ) 40 CONTINUE CALL DLASCL( 'G', 0, 0, SCALE, SIGMX, N, 1, D, N, IINFO ) END IF * 50 CONTINUE RETURN * * End of DLASQ1 * END SUBROUTINE DLASQ2( N, Z, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, N * .. * .. Array Arguments .. DOUBLE PRECISION Z( * ) * .. * * Purpose * ======= * * DLASQ2 computes all the eigenvalues of the symmetric positive * definite tridiagonal matrix associated with the qd array Z to high * relative accuracy are computed to high relative accuracy, in the * absence of denormalization, underflow and overflow. * * To see the relation of Z to the tridiagonal matrix, let L be a * unit lower bidiagonal matrix with subdiagonals Z(2,4,6,,..) and * let U be an upper bidiagonal matrix with 1's above and diagonal * Z(1,3,5,,..). The tridiagonal is L*U or, if you prefer, the * symmetric tridiagonal to which it is similar. * * Note : DLASQ2 works only on machines which follow ieee-754 * floating-point standard in their handling of infinities and NaNs. * Normal execution of DLASQ2 may create NaNs and infinities and hence * may abort due to a floating point exception in environments which * do not conform to the ieee standard. * * Arguments * ========= * * N (input) INTEGER * The number of rows and columns in the matrix. N >= 0. * * Z (workspace) DOUBLE PRECISION array, dimension ( 4*N ) * On entry Z holds the qd array. On exit, entries 1 to N hold * the eigenvalues in decreasing order, Z( 2*N+1 ) holds the * trace, Z( 2*N+2 ) holds the sum of the eigenvalues, Z( 2*N+3 ) * holds the iteration count, Z( 2*N+4 ) holds NDIVS/NIN^2, and * Z( 2*N+5 ) holds the percentage of shifts that failed. * * INFO (output) INTEGER * = 0: successful exit * < 0: if the i-th argument is a scalar and had an illegal * value, then INFO = -i, if the i-th argument is an * array and the j-entry had an illegal value, then * INFO = -(i*100+j) * > 0: the algorithm failed * = 1, a split was marked by a positive value in E * = 2, current block of Z not diagonalized after 30*N * iterations (in inner while loop) * = 3, termination criterion of outer while loop not met * (program created more than N unreduced blocks) * * Further Details * =============== * Local Variables: I0:N0 defines a current unreduced segment of Z. * The shifts are accumulated in SIGMA. Iteration count is in ITER. * Ping-pong is controlled by PP (alternates between 0 and 1). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION CBIAS PARAMETER ( CBIAS = 1.50D0 ) DOUBLE PRECISION ZERO, HALF, ONE, TWO, FOUR, TEN, HNDRD PARAMETER ( ZERO = 0.0D0, HALF = 0.5D0, ONE = 1.0D0, $ TWO = 2.0D0, FOUR = 4.0D0, TEN = 10.0D0, $ HNDRD = 100.0D0 ) * .. * .. Local Scalars .. INTEGER I0, I4, IINFO, IPN4, ITER, IWHILA, IWHILB, K, $ N0, NBIG, NDIV, NFAIL, PP, SPLT DOUBLE PRECISION D, DESIG, DMIN, DMIN1, DMIN2, DN, DN1, DN2, E, $ EMAX, EMIN, EPS, EPS2, OLDEMN, QMAX, QMIN, S, $ SIGMA, T, TAU, TEMP, TRACE, ZMAX * .. * .. External Subroutines .. EXTERNAL DLASQ3, DLASQ5, DLASRT, XERBLA * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments. * (in case DLASQ2 is not called by DLASQ1) * INFO = 0 EPS = DLAMCH( 'Precision' )*TEN EPS2 = EPS**2 * IF( N.LT.0 ) THEN INFO = -1 CALL XERBLA( 'DLASQ2', 1 ) RETURN ELSE IF( N.EQ.0 ) THEN RETURN ELSE IF( N.EQ.1 ) THEN * * 1-by-1 case. * IF( Z( 1 ).LT.ZERO ) THEN INFO = -201 CALL XERBLA( 'DLASQ2', 2 ) END IF RETURN ELSE IF( N.EQ.2 ) THEN * * 2-by-2 case. * IF( Z( 2 ).LT.ZERO .OR. Z( 3 ).LT.ZERO ) THEN INFO = -2 CALL XERBLA( 'DLASQ2', 2 ) RETURN ELSE IF( Z( 3 ).GT.Z( 1 ) ) THEN D = Z( 3 ) Z( 3 ) = Z( 1 ) Z( 1 ) = D END IF Z( 5 ) = Z( 1 ) + Z( 2 ) + Z( 3 ) IF( Z( 2 ).GT.Z( 3 )*EPS2 ) THEN T = HALF*( ( Z( 1 )-Z( 3 ) )+Z( 2 ) ) S = Z( 3 )*( Z( 2 ) / T ) IF( S.LE.T ) THEN S = Z( 3 )*( Z( 2 ) / ( T*( ONE+SQRT( ONE+S / T ) ) ) ) ELSE S = Z( 3 )*( Z( 2 ) / ( T+SQRT( T )*SQRT( T+S ) ) ) END IF T = Z( 1 ) + ( S+Z( 2 ) ) Z( 3 ) = Z( 3 )*( Z( 1 ) / T ) Z( 1 ) = T END IF Z( 2 ) = Z( 3 ) Z( 6 ) = Z( 2 ) + Z( 1 ) Z( 7 ) = ZERO Z( 8 ) = ZERO Z( 9 ) = ZERO RETURN END IF * * Check for negative data and compute sums of q's and e's. * Z( 2*N ) = ZERO EMIN = Z( 2 ) QMAX = ZERO D = ZERO E = ZERO * DO 10 K = 1, N IF( Z( K ).LT.ZERO ) THEN INFO = -( 200+K ) CALL XERBLA( 'DLASQ2', 2 ) RETURN ELSE IF( Z( N+K ).LT.ZERO ) THEN INFO = -( 200+N+K ) CALL XERBLA( 'DLASQ2', 2 ) RETURN END IF D = D + Z( K ) E = E + Z( N+K ) QMAX = MAX( QMAX, Z( K ) ) 10 CONTINUE ZMAX = QMAX DO 20 K = 1, N - 1 EMIN = MIN( EMIN, Z( N+K ) ) ZMAX = MAX( ZMAX, Z( N+K ) ) 20 CONTINUE * * Check for diagonality. * IF( E.EQ.ZERO ) THEN CALL DLASRT( 'D', N, Z, IINFO ) Z( 2*N-1 ) = D RETURN END IF * TRACE = D + E I0 = 1 N0 = N * * Check for zero data. * IF( TRACE.EQ.ZERO ) THEN Z( 2*N-1 ) = ZERO RETURN END IF * * Rearrange data for locality: Z=(q1,qq1,e1,ee1,q2,qq2,e2,ee2,...). * DO 30 K = 2*N, 2, -2 Z( 2*K ) = ZERO Z( 2*K-1 ) = Z( K ) Z( 2*K-2 ) = ZERO Z( 2*K-3 ) = Z( K-1 ) 30 CONTINUE * * Reverse the qd-array, if warranted. * IF( CBIAS*Z( 4*I0-3 ).LT.Z( 4*N0-3 ) ) THEN IPN4 = 4*( I0+N0 ) DO 40 I4 = 4*I0, 2*( I0+N0-1 ), 4 TEMP = Z( I4-3 ) Z( I4-3 ) = Z( IPN4-I4-3 ) Z( IPN4-I4-3 ) = TEMP TEMP = Z( I4-1 ) Z( I4-1 ) = Z( IPN4-I4-5 ) Z( IPN4-I4-5 ) = TEMP 40 CONTINUE END IF * * Initial split checking via dqd and Li's test. * PP = 0 * DO 80 K = 1, 2 * IF( EMIN.LE.EPS2*QMAX ) THEN * * Li's reverse test. * D = Z( 4*N0+PP-3 ) DO 50 I4 = 4*( N0-1 ) + PP, 4*I0 + PP, -4 IF( Z( I4-1 ).LE.EPS2*D ) THEN Z( I4-1 ) = -ZERO D = Z( I4-3 ) ELSE D = Z( I4-3 )*( D / ( D+Z( I4-1 ) ) ) END IF 50 CONTINUE * * dqd maps Z to ZZ plus Li's test. * EMIN = Z( 4*I0+PP+1 ) D = Z( 4*I0+PP-3 ) DO 60 I4 = 4*I0 + PP, 4*( N0-1 ) + PP, 4 IF( Z( I4-1 ).LE.EPS2*D ) THEN Z( I4-1 ) = -ZERO Z( I4-2*PP-2 ) = D Z( I4-2*PP ) = ZERO D = Z( I4+1 ) EMIN = ZERO ELSE Z( I4-2*PP-2 ) = D + Z( I4-1 ) Z( I4-2*PP ) = Z( I4+1 )*( Z( I4-1 ) / $ Z( I4-2*PP-2 ) ) D = Z( I4+1 )*( D / Z( I4-2*PP-2 ) ) EMIN = MIN( EMIN, Z( I4-2*PP ) ) END IF 60 CONTINUE Z( 4*N0-PP-2 ) = D ELSE TAU = ZERO CALL DLASQ5( I0, N0, Z, PP, TAU, DMIN, DMIN1, DMIN2, DN, $ DN1, DN2 ) * EMIN = Z( 4*N0 ) END IF * * Now find qmax. * QMAX = Z( 4*I0-PP-2 ) DO 70 I4 = 4*I0 - PP + 2, 4*N0 - PP - 2, 4 QMAX = MAX( QMAX, Z( I4 ) ) 70 CONTINUE * * Prepare for the next iteration on K. * PP = 1 - PP 80 CONTINUE * ITER = 2 NFAIL = 0 NDIV = 2*( N0-I0 ) * DO 140 IWHILA = 1, N + 1 IF( N0.LT.1 ) $ GO TO 150 * * While array unfinished do * * E(N0) holds the value of SIGMA when submatrix in I0:N0 * splits from the rest of the array, but is negated. * DESIG = ZERO IF( N0.EQ.N ) THEN SIGMA = ZERO ELSE SIGMA = -Z( 4*N0-1 ) END IF IF( SIGMA.LT.ZERO ) THEN INFO = 1 RETURN END IF * * Find last unreduced submatrix's top index I0, find QMAX and * EMIN. Find Gershgorin-type bound if Q's much greater than E's. * EMAX = ZERO IF( N0.GT.I0 ) THEN EMIN = ABS( Z( 4*N0-5 ) ) ELSE EMIN = ZERO END IF QMIN = Z( 4*N0-3 ) QMAX = QMIN DO 90 I4 = 4*N0, 8, -4 IF( Z( I4-5 ).LE.ZERO ) $ GO TO 100 IF( QMIN.GE.FOUR*EMAX ) THEN QMIN = MIN( QMIN, Z( I4-3 ) ) EMAX = MAX( EMAX, Z( I4-5 ) ) END IF QMAX = MAX( QMAX, Z( I4-7 )+Z( I4-5 ) ) EMIN = MIN( EMIN, Z( I4-5 ) ) 90 CONTINUE I4 = 4 * 100 CONTINUE I0 = I4 / 4 * * Store EMIN for passing to DLASQ3. * Z( 4*N0-1 ) = EMIN * * Put -(initial shift) into DMIN. * DMIN = -MAX( ZERO, QMIN-TWO*SQRT( QMIN )*SQRT( EMAX ) ) * * Now I0:N0 is unreduced. PP = 0 for ping, PP = 1 for pong. * PP = 0 * NBIG = 30*( N0-I0+1 ) DO 120 IWHILB = 1, NBIG IF( I0.GT.N0 ) $ GO TO 130 * * While submatrix unfinished take a good dqds step. * CALL DLASQ3( I0, N0, Z, PP, DMIN, SIGMA, DESIG, QMAX, NFAIL, $ ITER, NDIV ) * PP = 1 - PP * * When EMIN is very small check for splits. * IF( PP.EQ.0 .AND. N0-I0.GE.3 ) THEN IF( Z( 4*N0 ).LE.EPS2*QMAX .OR. Z( 4*N0-1 ).LE.EPS2* $ SIGMA ) THEN SPLT = I0 - 1 QMAX = Z( 4*I0-3 ) EMIN = Z( 4*I0-1 ) OLDEMN = Z( 4*I0 ) DO 110 I4 = 4*I0, 4*( N0-3 ), 4 IF( Z( I4 ).LE.EPS2*Z( I4-3 ) .OR. Z( I4-1 ).LE. $ EPS2*SIGMA ) THEN Z( I4-1 ) = -SIGMA SPLT = I4 / 4 QMAX = ZERO EMIN = Z( I4+3 ) OLDEMN = Z( I4+4 ) ELSE QMAX = MAX( QMAX, Z( I4+1 ) ) EMIN = MIN( EMIN, Z( I4-1 ) ) OLDEMN = MIN( OLDEMN, Z( I4 ) ) END IF 110 CONTINUE Z( 4*N0-1 ) = EMIN Z( 4*N0 ) = OLDEMN I0 = SPLT + 1 END IF END IF * 120 CONTINUE * INFO = 2 RETURN * * end IWHILB * 130 CONTINUE * 140 CONTINUE * INFO = 3 RETURN * * end IWHILA * 150 CONTINUE * * Move q's to the front. * DO 160 K = 2, N Z( K ) = Z( 4*K-3 ) 160 CONTINUE * * Sort and compute sum of eigenvalues. * CALL DLASRT( 'D', N, Z, IINFO ) * E = ZERO DO 170 K = N, 1, -1 E = E + Z( K ) 170 CONTINUE * * Store trace, sum(eigenvalues) and information on performance. * Z( 2*N+1 ) = TRACE Z( 2*N+2 ) = E Z( 2*N+3 ) = DBLE( ITER ) Z( 2*N+4 ) = DBLE( NDIV ) / DBLE( N**2 ) Z( 2*N+5 ) = HNDRD*NFAIL / DBLE( ITER ) RETURN * * End of DLASQ2 * END SUBROUTINE DLASQ3( I0, N0, Z, PP, DMIN, SIGMA, DESIG, QMAX, NFAIL, $ ITER, NDIV ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER I0, ITER, N0, NDIV, NFAIL, PP DOUBLE PRECISION DESIG, DMIN, QMAX, SIGMA * .. * .. Array Arguments .. DOUBLE PRECISION Z( * ) * .. * * Purpose * ======= * DLASQ3 checks for deflation, computes a shift (TAU) and calls dqds. * In case of failure it changes shifts, and tries again until output * is positive. * * Arguments * ========= * * I0 (input) INTEGER * First index. * * N0 (input) INTEGER * Last index. * * Z (input) DOUBLE PRECISION array, dimension ( 4*N ) * Z holds the qd array. * * PP (input) INTEGER * PP=0 for ping, PP=1 for pong. * * DMIN (output) DOUBLE PRECISION * Minimum value of d. * * SIGMA (output) DOUBLE PRECISION * Sum of shifts used in current segment. * * DESIG (input/output) DOUBLE PRECISION * Lower order part of SIGMA * * QMAX (input) DOUBLE PRECISION * Maximum value of q. * * NFAIL (output) INTEGER * Number of times shift was too big. * * ITER (output) INTEGER * Number of iterations. * * NDIV (output) INTEGER * Number of divisions. * * TTYPE (output) INTEGER * Shift type. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION CBIAS PARAMETER ( CBIAS = 1.50D0 ) DOUBLE PRECISION ZERO, QURTR, HALF, ONE, TWO, TEN PARAMETER ( ZERO = 0.0D0, QURTR = 0.250D0, HALF = 0.5D0, $ ONE = 1.0D0, TWO = 2.0D0, TEN = 10.0D0 ) * .. * .. Local Scalars .. INTEGER IPN4, J4, N0IN, NN, TTYPE DOUBLE PRECISION DMIN1, DMIN2, DN, DN1, DN2, EPS, EPS2, S, $ SFMIN, T, TAU, TEMP * .. * .. External Subroutines .. EXTERNAL DLASQ4, DLASQ5, DLASQ6 * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Save statement .. SAVE TTYPE, DMIN1, DMIN2, DN, DN1, DN2, TAU * .. * .. Data statements .. DATA TTYPE / 0 / DATA DMIN1 / ZERO / , DMIN2 / ZERO / , DN / ZERO / , $ DN1 / ZERO / , DN2 / ZERO / , TAU / ZERO / * .. * .. Executable Statements .. * N0IN = N0 EPS = DLAMCH( 'Precision' )*TEN SFMIN = DLAMCH( 'Safe minimum' ) EPS2 = EPS**2 * * Check for deflation. * 10 CONTINUE * IF( N0.LT.I0 ) $ RETURN IF( N0.EQ.I0 ) $ GO TO 20 NN = 4*N0 + PP IF( N0.EQ.( I0+1 ) ) $ GO TO 40 * * Check whether E(N0-1) is negligible, 1-by-1 case. * IF( Z( NN-5 ).GT.EPS2*( SIGMA+Z( NN-3 ) ) .AND. Z( NN-2*PP-4 ).GT. $ EPS2*Z( NN-7 ) )GO TO 30 * 20 CONTINUE * Z( 4*N0-3 ) = Z( 4*N0+PP-3 ) + SIGMA N0 = N0 - 1 GO TO 10 * * Check whether E(N0-2) is negligible, 2-by-2 case. * 30 CONTINUE * IF( Z( NN-9 ).GT.EPS2*SIGMA .AND. Z( NN-2*PP-8 ).GT.EPS2* $ Z( NN-11 ) )GO TO 50 * 40 CONTINUE * IF( Z( NN-3 ).GT.Z( NN-7 ) ) THEN S = Z( NN-3 ) Z( NN-3 ) = Z( NN-7 ) Z( NN-7 ) = S END IF IF( Z( NN-5 ).GT.Z( NN-3 )*EPS2 ) THEN T = HALF*( ( Z( NN-7 )-Z( NN-3 ) )+Z( NN-5 ) ) S = Z( NN-3 )*( Z( NN-5 ) / T ) IF( S.LE.T ) THEN S = Z( NN-3 )*( Z( NN-5 ) / ( T*( ONE+SQRT( ONE+S / $ T ) ) ) ) ELSE S = Z( NN-3 )*( Z( NN-5 ) / ( T+SQRT( T )*SQRT( T+S ) ) ) END IF T = Z( NN-7 ) + ( S+Z( NN-5 ) ) Z( NN-3 ) = Z( NN-3 )*( Z( NN-7 ) / T ) Z( NN-7 ) = T END IF Z( 4*N0-7 ) = Z( NN-7 ) + SIGMA Z( 4*N0-3 ) = Z( NN-3 ) + SIGMA N0 = N0 - 2 GO TO 10 * 50 CONTINUE * * Reverse the qd-array, if warranted. * IF( DMIN.LE.ZERO .OR. N0.LT.N0IN ) THEN IF( CBIAS*Z( 4*I0+PP-3 ).LT.Z( 4*N0+PP-3 ) ) THEN IPN4 = 4*( I0+N0 ) DO 60 J4 = 4*I0, 2*( I0+N0-1 ), 4 TEMP = Z( J4-3 ) Z( J4-3 ) = Z( IPN4-J4-3 ) Z( IPN4-J4-3 ) = TEMP TEMP = Z( J4-2 ) Z( J4-2 ) = Z( IPN4-J4-2 ) Z( IPN4-J4-2 ) = TEMP TEMP = Z( J4-1 ) Z( J4-1 ) = Z( IPN4-J4-5 ) Z( IPN4-J4-5 ) = TEMP TEMP = Z( J4 ) Z( J4 ) = Z( IPN4-J4-4 ) Z( IPN4-J4-4 ) = TEMP 60 CONTINUE IF( N0-I0.LE.4 ) THEN Z( 4*N0+PP-1 ) = Z( 4*I0+PP-1 ) Z( 4*N0-PP ) = Z( 4*I0-PP ) END IF DMIN2 = MIN( DMIN2, Z( 4*N0+PP-1 ) ) Z( 4*N0+PP-1 ) = MIN( Z( 4*N0+PP-1 ), Z( 4*I0+PP-1 ), $ Z( 4*I0+PP+3 ) ) Z( 4*I0-PP ) = MIN( Z( 4*N0-PP ), Z( 4*I0-PP ), $ Z( 4*I0-PP+4 ) ) QMAX = MAX( QMAX, Z( 4*I0+PP-3 ), Z( 4*I0+PP+1 ) ) DMIN = -ZERO END IF END IF * 70 CONTINUE * IF( DMIN.LT.ZERO .OR. SFMIN*QMAX.LE. $ MIN( Z( 4*N0+PP-1 ), Z( 4*N0+PP-9 ), DMIN2+Z( 4*N0-PP ) ) ) $ THEN * * Choose a shift. * CALL DLASQ4( I0, N0, Z, PP, N0IN, DMIN, DMIN1, DMIN2, DN, DN1, $ DN2, TAU, TTYPE ) * * Call dqds until DMIN > 0. * 80 CONTINUE * CALL DLASQ5( I0, N0, Z, PP, TAU, DMIN, DMIN1, DMIN2, DN, DN1, $ DN2 ) * ITER = ITER + 1 NDIV = NDIV + ( N0-I0+2 ) * * Check for NaN: "DMIN.NE.DMIN" * IF( DMIN.NE.DMIN ) THEN Z( 4*N0+PP-1 ) = ZERO TAU = ZERO GO TO 70 END IF * * Check for convergence hidden by negative DN. * IF( DMIN.LT.ZERO .AND. DMIN1.GT.ZERO .AND. $ Z( 4*( N0-1 )-PP ).LT.EPS*( SIGMA+DN1 ) .AND. ABS( DN ).LT. $ EPS*SIGMA ) THEN Z( 4*( N0-1 )-PP+2 ) = ZERO DMIN = ABS( DMIN ) END IF * IF( DMIN.LT.ZERO ) THEN * * Failure. Select new TAU and try again. * NFAIL = NFAIL + 1 * * Failed twice. Play it safe. * IF( TTYPE.LT.-22 ) THEN TAU = ZERO GO TO 80 END IF * IF( DMIN1.GT.ZERO ) THEN * * Late failure. Gives excellent shift. * TAU = ( TAU+DMIN )*( ONE-TWO*EPS ) TTYPE = TTYPE - 11 ELSE * * Early failure. Divide by 4. * TAU = QURTR*TAU TTYPE = TTYPE - 12 END IF GO TO 80 END IF ELSE CALL DLASQ6( I0, N0, Z, PP, DMIN, DMIN1, DMIN2, DN, DN1, DN2 ) ITER = ITER + 1 NDIV = NDIV + ( N0-I0 ) TAU = ZERO END IF * IF( TAU.LT.SIGMA ) THEN DESIG = DESIG + TAU T = SIGMA + DESIG DESIG = DESIG - ( T-SIGMA ) ELSE T = SIGMA + TAU DESIG = SIGMA - ( T-TAU ) + DESIG END IF SIGMA = T * RETURN * * End of DLASQ3 * END SUBROUTINE DLASQ4( I0, N0, Z, PP, N0IN, DMIN, DMIN1, DMIN2, DN, $ DN1, DN2, TAU, TTYPE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER I0, N0, N0IN, PP, TTYPE DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DN1, DN2, TAU * .. * .. Array Arguments .. DOUBLE PRECISION Z( * ) * .. * * Purpose * ======= * DLASQ4 computes an approximation TAU to the smallest eigenvalue * using values of d from the previous transform. * * I0 (input) INTEGER * First index. * * N0 (input) INTEGER * Last index. * * Z (input) DOUBLE PRECISION array, dimension ( 4*N ) * Z holds the qd array. * * PP (input) INTEGER * PP=0 for ping, PP=1 for pong. * * NOIN (input) INTEGER * The value of N0 at start of EIGTEST. * * DMIN (input) DOUBLE PRECISION * Minimum value of d. * * DMIN1 (input) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ). * * DMIN2 (input) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ) and D( N0-1 ). * * DN (input) DOUBLE PRECISION * d(N) * * DN1 (input) DOUBLE PRECISION * d(N-1) * * DN2 (input) DOUBLE PRECISION * d(N-2) * * TAU (output) DOUBLE PRECISION * This is the shift. * * TTYPE (output) INTEGER * Shift type. * * Further Details * =============== * CNST1 = 9/16 * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION CNST1, CNST2, CNST3 PARAMETER ( CNST1 = 0.5630D0, CNST2 = 1.010D0, $ CNST3 = 1.050D0 ) DOUBLE PRECISION QURTR, THIRD, HALF, ZERO, ONE, TWO, HNDRD PARAMETER ( QURTR = 0.250D0, THIRD = 0.3330D0, $ HALF = 0.50D0, ZERO = 0.0D0, ONE = 1.0D0, $ TWO = 2.0D0, HNDRD = 100.0D0 ) * .. * .. Local Scalars .. INTEGER I4, NN, NP DOUBLE PRECISION A2, B1, B2, G, GAM, GAP1, GAP2, S * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Save statement .. SAVE G * .. * .. Data statements .. DATA G / ZERO / * .. * .. Executable Statements .. * * A negative DMIN forces the shift to take that absolute value * TTYPE records the type of shift. * IF( DMIN.LE.ZERO ) THEN TAU = -DMIN TTYPE = -1 RETURN END IF * NN = 4*N0 + PP IF( N0IN.EQ.N0 ) THEN * * No eigenvalues deflated. * IF( DMIN.EQ.DN .OR. DMIN.EQ.DN1 ) THEN * B1 = SQRT( Z( NN-3 ) )*SQRT( Z( NN-5 ) ) B2 = SQRT( Z( NN-7 ) )*SQRT( Z( NN-9 ) ) A2 = Z( NN-7 ) + Z( NN-5 ) * * Cases 2 and 3. * IF( DMIN.EQ.DN .AND. DMIN1.EQ.DN1 ) THEN GAP2 = DMIN2 - A2 - DMIN2*QURTR IF( GAP2.GT.ZERO .AND. GAP2.GT.B2 ) THEN GAP1 = A2 - DN - ( B2 / GAP2 )*B2 ELSE GAP1 = A2 - DN - ( B1+B2 ) END IF IF( GAP1.GT.ZERO .AND. GAP1.GT.B1 ) THEN S = MAX( DN-( B1 / GAP1 )*B1, HALF*DMIN ) TTYPE = -2 ELSE S = ZERO IF( DN.GT.B1 ) $ S = DN - B1 IF( A2.GT.( B1+B2 ) ) $ S = MIN( S, A2-( B1+B2 ) ) S = MAX( S, THIRD*DMIN ) TTYPE = -3 END IF ELSE * * Case 4. * IF( DMIN.EQ.DN ) THEN GAM = DN A2 = ZERO B2 = Z( NN-5 ) / Z( NN-7 ) NP = NN - 9 ELSE NP = NN - 2*PP B2 = Z( NP-2 ) GAM = DN1 A2 = Z( NP-4 ) / Z( NP-2 ) B2 = Z( NN-9 ) / Z( NN-11 ) NP = NN - 13 END IF * * Approximate contribution to norm squared from I < NN-1. * IF( B2.EQ.ZERO ) $ GO TO 20 A2 = A2 + B2 DO 10 I4 = NP, 4*I0 - 1 + PP, -4 B1 = B2 B2 = B2*( Z( I4 ) / Z( I4-2 ) ) A2 = A2 + B2 IF( HNDRD*MAX( B2, B1 ).LT.A2 .OR. CNST1.LT.A2 ) $ GO TO 20 10 CONTINUE 20 CONTINUE A2 = CNST3*A2 * * Rayleigh quotient residual bound. * IF( A2.LT.CNST1 ) THEN S = GAM*( ONE-SQRT( A2 ) ) / ( ONE+A2 ) ELSE S = QURTR*GAM END IF TTYPE = -4 END IF ELSE IF( DMIN.EQ.DN2 ) THEN * * Case 5. * * Compute contribution to norm squared from I > NN-2. * NP = NN - 2*PP B1 = Z( NP-2 ) B2 = Z( NP-6 ) GAM = DN2 A2 = ( Z( NP-8 ) / B2 )*( ONE+Z( NP-4 ) / B1 ) * * Approximate contribution to norm squared from I < NN-2. * IF( N0-I0.GT.2 ) THEN B2 = Z( NN-13 ) / Z( NN-15 ) IF( B2.EQ.ZERO ) $ GO TO 40 A2 = A2 + B2 DO 30 I4 = NN - 17, 4*I0 - 1 + PP, -4 B1 = B2 B2 = B2*( Z( I4 ) / Z( I4-2 ) ) A2 = A2 + B2 IF( HNDRD*MAX( B2, B1 ).LT.A2 .OR. CNST1.LT.A2 ) $ GO TO 40 30 CONTINUE 40 CONTINUE A2 = CNST3*A2 END IF * IF( A2.LT.CNST1 ) THEN S = GAM*( ONE-SQRT( A2 ) ) / ( ONE+A2 ) ELSE S = QURTR*GAM / ( ONE+A2 ) END IF TTYPE = -5 ELSE * * Case 6, no information to guide us. * IF( TTYPE.EQ.-6 ) THEN G = G + THIRD*( ONE-G ) ELSE IF( TTYPE.EQ.-18 ) THEN G = QURTR*THIRD ELSE G = QURTR END IF S = G*DMIN TTYPE = -6 END IF * ELSE IF( N0IN.EQ.( N0+1 ) ) THEN * * One eigenvalue just deflated. Use DMIN1, DN1 for DMIN and DN. * IF( DMIN1.EQ.DN1 .AND. DMIN2.EQ.DN2 ) THEN * * Cases 7 and 8. * B1 = Z( NN-5 ) / Z( NN-7 ) B2 = B1 IF( B2.EQ.ZERO ) $ GO TO 60 DO 50 I4 = 4*N0 - 9 + PP, 4*I0 - 1 + PP, -4 A2 = B1 B1 = B1*( Z( I4 ) / Z( I4-2 ) ) B2 = B2 + B1 IF( HNDRD*MAX( B1, A2 ).LT.B2 ) $ GO TO 60 50 CONTINUE 60 CONTINUE B2 = SQRT( CNST3*B2 ) A2 = DMIN1 / ( ONE+B2**2 ) GAP2 = HALF*DMIN2 - A2 IF( GAP2.GT.ZERO .AND. GAP2.GT.B2*A2 ) THEN S = MAX( A2*( ONE-CNST2*A2*( B2 / GAP2 )*B2 ), $ THIRD*DMIN1 ) TTYPE = -7 ELSE S = MAX( A2*( ONE-CNST2*B2 ), THIRD*DMIN1 ) TTYPE = -8 END IF ELSE * * Case 9. * S = QURTR*DMIN1 IF( DMIN1.EQ.DN1 ) $ S = HALF*DMIN1 TTYPE = -9 END IF * ELSE IF( N0IN.EQ.( N0+2 ) ) THEN * * Two eigenvalues deflated. Use DMIN2, DN2 for DMIN and DN. * * Cases 10 and 11. * IF( DMIN2.EQ.DN2 .AND. TWO*Z( NN-5 ).LT.Z( NN-7 ) ) THEN B1 = Z( NN-5 ) / Z( NN-7 ) B2 = B1 IF( B2.EQ.ZERO ) $ GO TO 80 DO 70 I4 = 4*N0 - 9 + PP, 4*I0 - 1 + PP, -4 B1 = B1*( Z( I4 ) / Z( I4-2 ) ) B2 = B2 + B1 IF( HNDRD*B1.LT.B2 ) $ GO TO 80 70 CONTINUE 80 CONTINUE B2 = SQRT( CNST3*B2 ) A2 = DMIN2 / ( ONE+B2**2 ) GAP2 = Z( NN-7 ) + Z( NN-9 ) - $ SQRT( Z( NN-11 ) )*SQRT( Z( NN-9 ) ) - A2 IF( GAP2.GT.ZERO .AND. GAP2.GT.B2*A2 ) THEN S = MAX( A2*( ONE-CNST2*A2*( B2 / GAP2 )*B2 ), $ THIRD*DMIN2 ) ELSE S = MAX( A2*( ONE-CNST2*B2 ), THIRD*DMIN2 ) END IF TTYPE = -10 ELSE S = QURTR*DMIN2 TTYPE = -11 END IF ELSE IF( N0IN.GT.( N0+2 ) ) THEN * * Case 12, more than two eigenvalues deflated. No information. * S = ZERO TTYPE = -12 END IF * TAU = S RETURN * * End of DLASQ4 * END SUBROUTINE DLASQ5( I0, N0, Z, PP, TAU, DMIN, DMIN1, DMIN2, DN, $ DNM1, DNM2 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER I0, N0, PP DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DNM1, DNM2, TAU * .. * .. Array Arguments .. DOUBLE PRECISION Z( * ) * .. * * Purpose * ======= * DLASQ5 computes one dqds transform in ping-pong form. * * Arguments * ========= * * I0 (input) INTEGER * First index. * * N0 (input) INTEGER * Last index. * * Z (input) DOUBLE PRECISION array, dimension ( 4*N ) * Z holds the qd array. EMIN is stored in Z(4*N0) to avoid * an extra argument. * * PP (input) INTEGER * PP=0 for ping, PP=1 for pong. * * TAU (input) DOUBLE PRECISION * This is the shift. * * DMIN (output) DOUBLE PRECISION * Minimum value of d. * * DMIN1 (output) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ). * * DMIN2 (output) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ) and D( N0-1 ). * * DN (output) DOUBLE PRECISION * d(N0), the last value of d. * * DNM1 (output) DOUBLE PRECISION * d(N0-1). * * DNM2 (output) DOUBLE PRECISION * d(N0-2). * * ===================================================================== * * .. Local Scalars .. INTEGER J4, J4P2 DOUBLE PRECISION D, EMIN, TEMP * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * IF( ( N0-I0-1 ).LE.0 ) $ RETURN * J4 = 4*I0 + PP - 3 EMIN = Z( J4+4 ) D = Z( J4 ) - TAU DMIN = D * IF( PP.EQ.0 ) THEN DO 10 J4 = 4*I0, 4*( N0-3 ), 4 Z( J4-2 ) = D + Z( J4-1 ) TEMP = Z( J4+1 ) / Z( J4-2 ) D = D*TEMP - TAU DMIN = MIN( DMIN, D ) Z( J4 ) = Z( J4-1 )*TEMP EMIN = MIN( Z( J4 ), EMIN ) 10 CONTINUE ELSE DO 20 J4 = 4*I0, 4*( N0-3 ), 4 Z( J4-3 ) = D + Z( J4 ) TEMP = Z( J4+2 ) / Z( J4-3 ) D = D*TEMP - TAU DMIN = MIN( DMIN, D ) Z( J4-1 ) = Z( J4 )*TEMP EMIN = MIN( Z( J4-1 ), EMIN ) 20 CONTINUE END IF * * Unroll last two steps. * DNM2 = D DMIN2 = DMIN J4 = 4*( N0-2 ) - PP J4P2 = J4 + 2*PP - 1 Z( J4-2 ) = DNM2 + Z( J4P2 ) Z( J4 ) = Z( J4P2+2 )*( Z( J4P2 ) / Z( J4-2 ) ) DNM1 = Z( J4P2+2 )*( DNM2 / Z( J4-2 ) ) - TAU DMIN = MIN( DMIN, DNM1 ) * DMIN1 = DMIN J4 = J4 + 4 J4P2 = J4 + 2*PP - 1 Z( J4-2 ) = DNM1 + Z( J4P2 ) Z( J4 ) = Z( J4P2+2 )*( Z( J4P2 ) / Z( J4-2 ) ) DN = Z( J4P2+2 )*( DNM1 / Z( J4-2 ) ) - TAU DMIN = MIN( DMIN, DN ) * Z( J4+2 ) = DN Z( 4*N0-PP ) = EMIN RETURN * * End of DLASQ5 * END SUBROUTINE DLASQ6( I0, N0, Z, PP, DMIN, DMIN1, DMIN2, DN, DNM1, $ DNM2 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER I0, N0, PP DOUBLE PRECISION DMIN, DMIN1, DMIN2, DN, DNM1, DNM2 * .. * .. Array Arguments .. DOUBLE PRECISION Z( * ) * .. * * Purpose * ======= * DLASQ6 computes one dqds transform in ping-pong form. * * Arguments * ========= * * I0 (input) INTEGER * First index. * * N0 (input) INTEGER * Last index. * * Z (input) DOUBLE PRECISION array, dimension ( 4*N ) * Z holds the qd array. EMIN is stored in Z(4*N0) to avoid * an extra argument. * * PP (input) INTEGER * PP=0 for ping, PP=1 for pong. * * DMIN (output) DOUBLE PRECISION * Minimum value of d. * * DMIN1 (output) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ). * * DMIN2 (output) DOUBLE PRECISION * Minimum value of d, excluding D( N0 ) and D( N0-1 ). * * DN (output) DOUBLE PRECISION * d(N0), the last value of d. * * DNM1 (output) DOUBLE PRECISION * d(N0-1). * * DNM2 (output) DOUBLE PRECISION * d(N0-2). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) * .. * .. Local Scalars .. INTEGER J4, J4P2 DOUBLE PRECISION D, EMIN, SFMIN, TEMP * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * IF( ( N0-I0-1 ).LE.0 ) $ RETURN * SFMIN = DLAMCH( 'Safe minimum' ) J4 = 4*I0 + PP - 3 EMIN = Z( J4+4 ) D = Z( J4 ) DMIN = D * DO 10 J4 = 4*I0 - PP, 4*( N0-3 ) - PP, 4 J4P2 = J4 + 2*PP - 1 Z( J4-2 ) = D + Z( J4P2 ) IF( Z( J4-2 ).EQ.ZERO ) THEN Z( J4 ) = ZERO D = Z( J4P2+2 ) DMIN = D EMIN = ZERO ELSE IF( SFMIN*Z( J4P2+2 ).LT.Z( J4-2 ) ) THEN TEMP = Z( J4P2+2 ) / Z( J4-2 ) Z( J4 ) = Z( J4P2 )*TEMP D = D*TEMP ELSE Z( J4 ) = Z( J4P2+2 )*( Z( J4P2 ) / Z( J4-2 ) ) D = Z( J4P2+2 )*( D / Z( J4-2 ) ) END IF DMIN = MIN( DMIN, D ) EMIN = MIN( EMIN, Z( J4 ) ) 10 CONTINUE * * Unroll last two steps. * DNM2 = D DMIN2 = DMIN J4 = 4*( N0-2 ) - PP J4P2 = J4 + 2*PP - 1 Z( J4-2 ) = DNM2 + Z( J4P2 ) IF( Z( J4-2 ).EQ.ZERO ) THEN Z( J4 ) = ZERO DNM1 = Z( J4P2+2 ) DMIN = DNM1 EMIN = ZERO ELSE IF( SFMIN*Z( J4P2+2 ).LT.Z( J4-2 ) ) THEN TEMP = Z( J4P2+2 ) / Z( J4-2 ) Z( J4 ) = Z( J4P2 )*TEMP DNM1 = DNM2*TEMP ELSE Z( J4 ) = Z( J4P2+2 )*( Z( J4P2 ) / Z( J4-2 ) ) DNM1 = Z( J4P2+2 )*( DNM2 / Z( J4-2 ) ) END IF DMIN = MIN( DMIN, DNM1 ) * DMIN1 = DMIN J4 = J4 + 4 J4P2 = J4 + 2*PP - 1 Z( J4-2 ) = DNM1 + Z( J4P2 ) IF( Z( J4-2 ).EQ.ZERO ) THEN Z( J4 ) = ZERO DN = Z( J4P2+2 ) DMIN = DN EMIN = ZERO ELSE IF( SFMIN*Z( J4P2+2 ).LT.Z( J4-2 ) ) THEN TEMP = Z( J4P2+2 ) / Z( J4-2 ) Z( J4 ) = Z( J4P2 )*TEMP DN = DNM1*TEMP ELSE Z( J4 ) = Z( J4P2+2 )*( Z( J4P2 ) / Z( J4-2 ) ) DN = Z( J4P2+2 )*( DNM1 / Z( J4-2 ) ) END IF DMIN = MIN( DMIN, DN ) * Z( J4+2 ) = DN Z( 4*N0-PP ) = EMIN RETURN * * End of DLASQ6 * END SUBROUTINE DLASR( SIDE, PIVOT, DIRECT, M, N, C, S, A, LDA ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER DIRECT, PIVOT, SIDE INTEGER LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( * ), S( * ) * .. * * Purpose * ======= * * DLASR performs the transformation * * A := P*A, when SIDE = 'L' or 'l' ( Left-hand side ) * * A := A*P', when SIDE = 'R' or 'r' ( Right-hand side ) * * where A is an m by n real matrix and P is an orthogonal matrix, * consisting of a sequence of plane rotations determined by the * parameters PIVOT and DIRECT as follows ( z = m when SIDE = 'L' or 'l' * and z = n when SIDE = 'R' or 'r' ): * * When DIRECT = 'F' or 'f' ( Forward sequence ) then * * P = P( z - 1 )*...*P( 2 )*P( 1 ), * * and when DIRECT = 'B' or 'b' ( Backward sequence ) then * * P = P( 1 )*P( 2 )*...*P( z - 1 ), * * where P( k ) is a plane rotation matrix for the following planes: * * when PIVOT = 'V' or 'v' ( Variable pivot ), * the plane ( k, k + 1 ) * * when PIVOT = 'T' or 't' ( Top pivot ), * the plane ( 1, k + 1 ) * * when PIVOT = 'B' or 'b' ( Bottom pivot ), * the plane ( k, z ) * * c( k ) and s( k ) must contain the cosine and sine that define the * matrix P( k ). The two by two plane rotation part of the matrix * P( k ), R( k ), is assumed to be of the form * * R( k ) = ( c( k ) s( k ) ). * ( -s( k ) c( k ) ) * * This version vectorises across rows of the array A when SIDE = 'L'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * Specifies whether the plane rotation matrix P is applied to * A on the left or the right. * = 'L': Left, compute A := P*A * = 'R': Right, compute A:= A*P' * * DIRECT (input) CHARACTER*1 * Specifies whether P is a forward or backward sequence of * plane rotations. * = 'F': Forward, P = P( z - 1 )*...*P( 2 )*P( 1 ) * = 'B': Backward, P = P( 1 )*P( 2 )*...*P( z - 1 ) * * PIVOT (input) CHARACTER*1 * Specifies the plane for which P(k) is a plane rotation * matrix. * = 'V': Variable pivot, the plane (k,k+1) * = 'T': Top pivot, the plane (1,k+1) * = 'B': Bottom pivot, the plane (k,z) * * M (input) INTEGER * The number of rows of the matrix A. If m <= 1, an immediate * return is effected. * * N (input) INTEGER * The number of columns of the matrix A. If n <= 1, an * immediate return is effected. * * C, S (input) DOUBLE PRECISION arrays, dimension * (M-1) if SIDE = 'L' * (N-1) if SIDE = 'R' * c(k) and s(k) contain the cosine and sine that define the * matrix P(k). The two by two plane rotation part of the * matrix P(k), R(k), is assumed to be of the form * R( k ) = ( c( k ) s( k ) ). * ( -s( k ) c( k ) ) * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * The m by n matrix A. On exit, A is overwritten by P*A if * SIDE = 'R' or by A*P' if SIDE = 'L'. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, INFO, J DOUBLE PRECISION CTEMP, STEMP, TEMP * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 IF( .NOT.( LSAME( SIDE, 'L' ) .OR. LSAME( SIDE, 'R' ) ) ) THEN INFO = 1 ELSE IF( .NOT.( LSAME( PIVOT, 'V' ) .OR. LSAME( PIVOT, $ 'T' ) .OR. LSAME( PIVOT, 'B' ) ) ) THEN INFO = 2 ELSE IF( .NOT.( LSAME( DIRECT, 'F' ) .OR. LSAME( DIRECT, 'B' ) ) ) $ THEN INFO = 3 ELSE IF( M.LT.0 ) THEN INFO = 4 ELSE IF( N.LT.0 ) THEN INFO = 5 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = 9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASR ', INFO ) RETURN END IF * * Quick return if possible * IF( ( M.EQ.0 ) .OR. ( N.EQ.0 ) ) $ RETURN IF( LSAME( SIDE, 'L' ) ) THEN * * Form P * A * IF( LSAME( PIVOT, 'V' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 20 J = 1, M - 1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 10 I = 1, N TEMP = A( J+1, I ) A( J+1, I ) = CTEMP*TEMP - STEMP*A( J, I ) A( J, I ) = STEMP*TEMP + CTEMP*A( J, I ) 10 CONTINUE END IF 20 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 40 J = M - 1, 1, -1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 30 I = 1, N TEMP = A( J+1, I ) A( J+1, I ) = CTEMP*TEMP - STEMP*A( J, I ) A( J, I ) = STEMP*TEMP + CTEMP*A( J, I ) 30 CONTINUE END IF 40 CONTINUE END IF ELSE IF( LSAME( PIVOT, 'T' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 60 J = 2, M CTEMP = C( J-1 ) STEMP = S( J-1 ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 50 I = 1, N TEMP = A( J, I ) A( J, I ) = CTEMP*TEMP - STEMP*A( 1, I ) A( 1, I ) = STEMP*TEMP + CTEMP*A( 1, I ) 50 CONTINUE END IF 60 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 80 J = M, 2, -1 CTEMP = C( J-1 ) STEMP = S( J-1 ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 70 I = 1, N TEMP = A( J, I ) A( J, I ) = CTEMP*TEMP - STEMP*A( 1, I ) A( 1, I ) = STEMP*TEMP + CTEMP*A( 1, I ) 70 CONTINUE END IF 80 CONTINUE END IF ELSE IF( LSAME( PIVOT, 'B' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 100 J = 1, M - 1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 90 I = 1, N TEMP = A( J, I ) A( J, I ) = STEMP*A( M, I ) + CTEMP*TEMP A( M, I ) = CTEMP*A( M, I ) - STEMP*TEMP 90 CONTINUE END IF 100 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 120 J = M - 1, 1, -1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 110 I = 1, N TEMP = A( J, I ) A( J, I ) = STEMP*A( M, I ) + CTEMP*TEMP A( M, I ) = CTEMP*A( M, I ) - STEMP*TEMP 110 CONTINUE END IF 120 CONTINUE END IF END IF ELSE IF( LSAME( SIDE, 'R' ) ) THEN * * Form A * P' * IF( LSAME( PIVOT, 'V' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 140 J = 1, N - 1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 130 I = 1, M TEMP = A( I, J+1 ) A( I, J+1 ) = CTEMP*TEMP - STEMP*A( I, J ) A( I, J ) = STEMP*TEMP + CTEMP*A( I, J ) 130 CONTINUE END IF 140 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 160 J = N - 1, 1, -1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 150 I = 1, M TEMP = A( I, J+1 ) A( I, J+1 ) = CTEMP*TEMP - STEMP*A( I, J ) A( I, J ) = STEMP*TEMP + CTEMP*A( I, J ) 150 CONTINUE END IF 160 CONTINUE END IF ELSE IF( LSAME( PIVOT, 'T' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 180 J = 2, N CTEMP = C( J-1 ) STEMP = S( J-1 ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 170 I = 1, M TEMP = A( I, J ) A( I, J ) = CTEMP*TEMP - STEMP*A( I, 1 ) A( I, 1 ) = STEMP*TEMP + CTEMP*A( I, 1 ) 170 CONTINUE END IF 180 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 200 J = N, 2, -1 CTEMP = C( J-1 ) STEMP = S( J-1 ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 190 I = 1, M TEMP = A( I, J ) A( I, J ) = CTEMP*TEMP - STEMP*A( I, 1 ) A( I, 1 ) = STEMP*TEMP + CTEMP*A( I, 1 ) 190 CONTINUE END IF 200 CONTINUE END IF ELSE IF( LSAME( PIVOT, 'B' ) ) THEN IF( LSAME( DIRECT, 'F' ) ) THEN DO 220 J = 1, N - 1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 210 I = 1, M TEMP = A( I, J ) A( I, J ) = STEMP*A( I, N ) + CTEMP*TEMP A( I, N ) = CTEMP*A( I, N ) - STEMP*TEMP 210 CONTINUE END IF 220 CONTINUE ELSE IF( LSAME( DIRECT, 'B' ) ) THEN DO 240 J = N - 1, 1, -1 CTEMP = C( J ) STEMP = S( J ) IF( ( CTEMP.NE.ONE ) .OR. ( STEMP.NE.ZERO ) ) THEN DO 230 I = 1, M TEMP = A( I, J ) A( I, J ) = STEMP*A( I, N ) + CTEMP*TEMP A( I, N ) = CTEMP*A( I, N ) - STEMP*TEMP 230 CONTINUE END IF 240 CONTINUE END IF END IF END IF * RETURN * * End of DLASR * END SUBROUTINE DLASRT( ID, N, D, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER ID INTEGER INFO, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ) * .. * * Purpose * ======= * * Sort the numbers in D in increasing order (if ID = 'I') or * in decreasing order (if ID = 'D' ). * * Use Quick Sort, reverting to Insertion sort on arrays of * size <= 20. Dimension of STACK limits N to about 2**32. * * Arguments * ========= * * ID (input) CHARACTER*1 * = 'I': sort D in increasing order; * = 'D': sort D in decreasing order. * * N (input) INTEGER * The length of the array D. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the array to be sorted. * On exit, D has been sorted into increasing order * (D(1) <= ... <= D(N) ) or into decreasing order * (D(1) >= ... >= D(N) ), depending on ID. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. INTEGER SELECT PARAMETER ( SELECT = 20 ) * .. * .. Local Scalars .. INTEGER DIR, ENDD, I, J, START, STKPNT DOUBLE PRECISION D1, D2, D3, DMNMX, TMP * .. * .. Local Arrays .. INTEGER STACK( 2, 32 ) * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. Executable Statements .. * * Test the input paramters. * INFO = 0 DIR = -1 IF( LSAME( ID, 'D' ) ) THEN DIR = 0 ELSE IF( LSAME( ID, 'I' ) ) THEN DIR = 1 END IF IF( DIR.EQ.-1 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASRT', -INFO ) RETURN END IF * * Quick return if possible * IF( N.LE.1 ) $ RETURN * STKPNT = 1 STACK( 1, 1 ) = 1 STACK( 2, 1 ) = N 10 CONTINUE START = STACK( 1, STKPNT ) ENDD = STACK( 2, STKPNT ) STKPNT = STKPNT - 1 IF( ENDD-START.LE.SELECT .AND. ENDD-START.GT.0 ) THEN * * Do Insertion sort on D( START:ENDD ) * IF( DIR.EQ.0 ) THEN * * Sort into decreasing order * DO 30 I = START + 1, ENDD DO 20 J = I, START + 1, -1 IF( D( J ).GT.D( J-1 ) ) THEN DMNMX = D( J ) D( J ) = D( J-1 ) D( J-1 ) = DMNMX ELSE GO TO 30 END IF 20 CONTINUE 30 CONTINUE * ELSE * * Sort into increasing order * DO 50 I = START + 1, ENDD DO 40 J = I, START + 1, -1 IF( D( J ).LT.D( J-1 ) ) THEN DMNMX = D( J ) D( J ) = D( J-1 ) D( J-1 ) = DMNMX ELSE GO TO 50 END IF 40 CONTINUE 50 CONTINUE * END IF * ELSE IF( ENDD-START.GT.SELECT ) THEN * * Partition D( START:ENDD ) and stack parts, largest one first * * Choose partition entry as median of 3 * D1 = D( START ) D2 = D( ENDD ) I = ( START+ENDD ) / 2 D3 = D( I ) IF( D1.LT.D2 ) THEN IF( D3.LT.D1 ) THEN DMNMX = D1 ELSE IF( D3.LT.D2 ) THEN DMNMX = D3 ELSE DMNMX = D2 END IF ELSE IF( D3.LT.D2 ) THEN DMNMX = D2 ELSE IF( D3.LT.D1 ) THEN DMNMX = D3 ELSE DMNMX = D1 END IF END IF * IF( DIR.EQ.0 ) THEN * * Sort into decreasing order * I = START - 1 J = ENDD + 1 60 CONTINUE 70 CONTINUE J = J - 1 IF( D( J ).LT.DMNMX ) $ GO TO 70 80 CONTINUE I = I + 1 IF( D( I ).GT.DMNMX ) $ GO TO 80 IF( I.LT.J ) THEN TMP = D( I ) D( I ) = D( J ) D( J ) = TMP GO TO 60 END IF IF( J-START.GT.ENDD-J-1 ) THEN STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = START STACK( 2, STKPNT ) = J STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = J + 1 STACK( 2, STKPNT ) = ENDD ELSE STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = J + 1 STACK( 2, STKPNT ) = ENDD STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = START STACK( 2, STKPNT ) = J END IF ELSE * * Sort into increasing order * I = START - 1 J = ENDD + 1 90 CONTINUE 100 CONTINUE J = J - 1 IF( D( J ).GT.DMNMX ) $ GO TO 100 110 CONTINUE I = I + 1 IF( D( I ).LT.DMNMX ) $ GO TO 110 IF( I.LT.J ) THEN TMP = D( I ) D( I ) = D( J ) D( J ) = TMP GO TO 90 END IF IF( J-START.GT.ENDD-J-1 ) THEN STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = START STACK( 2, STKPNT ) = J STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = J + 1 STACK( 2, STKPNT ) = ENDD ELSE STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = J + 1 STACK( 2, STKPNT ) = ENDD STKPNT = STKPNT + 1 STACK( 1, STKPNT ) = START STACK( 2, STKPNT ) = J END IF END IF END IF IF( STKPNT.GT.0 ) $ GO TO 10 RETURN * * End of DLASRT * END SUBROUTINE DLASSQ( N, X, INCX, SCALE, SUMSQ ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INCX, N DOUBLE PRECISION SCALE, SUMSQ * .. * .. Array Arguments .. DOUBLE PRECISION X( * ) * .. * * Purpose * ======= * * DLASSQ returns the values scl and smsq such that * * ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq, * * where x( i ) = X( 1 + ( i - 1 )*INCX ). The value of sumsq is * assumed to be non-negative and scl returns the value * * scl = max( scale, abs( x( i ) ) ). * * scale and sumsq must be supplied in SCALE and SUMSQ and * scl and smsq are overwritten on SCALE and SUMSQ respectively. * * The routine makes only one pass through the vector x. * * Arguments * ========= * * N (input) INTEGER * The number of elements to be used from the vector X. * * X (input) DOUBLE PRECISION array, dimension (N) * The vector for which a scaled sum of squares is computed. * x( i ) = X( 1 + ( i - 1 )*INCX ), 1 <= i <= n. * * INCX (input) INTEGER * The increment between successive values of the vector X. * INCX > 0. * * SCALE (input/output) DOUBLE PRECISION * On entry, the value scale in the equation above. * On exit, SCALE is overwritten with scl , the scaling factor * for the sum of squares. * * SUMSQ (input/output) DOUBLE PRECISION * On entry, the value sumsq in the equation above. * On exit, SUMSQ is overwritten with smsq , the basic sum of * squares from which scl has been factored out. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER IX DOUBLE PRECISION ABSXI * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * IF( N.GT.0 ) THEN DO 10 IX = 1, 1 + ( N-1 )*INCX, INCX IF( X( IX ).NE.ZERO ) THEN ABSXI = ABS( X( IX ) ) IF( SCALE.LT.ABSXI ) THEN SUMSQ = 1 + SUMSQ*( SCALE / ABSXI )**2 SCALE = ABSXI ELSE SUMSQ = SUMSQ + ( ABSXI / SCALE )**2 END IF END IF 10 CONTINUE END IF RETURN * * End of DLASSQ * END SUBROUTINE DLASV2( F, G, H, SSMIN, SSMAX, SNR, CSR, SNL, CSL ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. DOUBLE PRECISION CSL, CSR, F, G, H, SNL, SNR, SSMAX, SSMIN * .. * * Purpose * ======= * * DLASV2 computes the singular value decomposition of a 2-by-2 * triangular matrix * [ F G ] * [ 0 H ]. * On return, abs(SSMAX) is the larger singular value, abs(SSMIN) is the * smaller singular value, and (CSL,SNL) and (CSR,SNR) are the left and * right singular vectors for abs(SSMAX), giving the decomposition * * [ CSL SNL ] [ F G ] [ CSR -SNR ] = [ SSMAX 0 ] * [-SNL CSL ] [ 0 H ] [ SNR CSR ] [ 0 SSMIN ]. * * Arguments * ========= * * F (input) DOUBLE PRECISION * The (1,1) element of the 2-by-2 matrix. * * G (input) DOUBLE PRECISION * The (1,2) element of the 2-by-2 matrix. * * H (input) DOUBLE PRECISION * The (2,2) element of the 2-by-2 matrix. * * SSMIN (output) DOUBLE PRECISION * abs(SSMIN) is the smaller singular value. * * SSMAX (output) DOUBLE PRECISION * abs(SSMAX) is the larger singular value. * * SNL (output) DOUBLE PRECISION * CSL (output) DOUBLE PRECISION * The vector (CSL, SNL) is a unit left singular vector for the * singular value abs(SSMAX). * * SNR (output) DOUBLE PRECISION * CSR (output) DOUBLE PRECISION * The vector (CSR, SNR) is a unit right singular vector for the * singular value abs(SSMAX). * * Further Details * =============== * * Any input parameter may be aliased with any output parameter. * * Barring over/underflow and assuming a guard digit in subtraction, all * output quantities are correct to within a few units in the last * place (ulps). * * In IEEE arithmetic, the code works correctly if one matrix element is * infinite. * * Overflow will not occur unless the largest singular value itself * overflows or is within a few ulps of overflow. (On machines with * partial overflow, like the Cray, overflow may occur if the largest * singular value is within a factor of 2 of overflow.) * * Underflow is harmless if underflow is gradual. Otherwise, results * may correspond to a matrix modified by perturbations of size near * the underflow threshold. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D0 ) DOUBLE PRECISION HALF PARAMETER ( HALF = 0.5D0 ) DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D0 ) DOUBLE PRECISION FOUR PARAMETER ( FOUR = 4.0D0 ) * .. * .. Local Scalars .. LOGICAL GASMAL, SWAP INTEGER PMAX DOUBLE PRECISION A, CLT, CRT, D, FA, FT, GA, GT, HA, HT, L, M, $ MM, R, S, SLT, SRT, T, TEMP, TSIGN, TT * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Executable Statements .. * FT = F FA = ABS( FT ) HT = H HA = ABS( H ) * * PMAX points to the maximum absolute element of matrix * PMAX = 1 if F largest in absolute values * PMAX = 2 if G largest in absolute values * PMAX = 3 if H largest in absolute values * PMAX = 1 SWAP = ( HA.GT.FA ) IF( SWAP ) THEN PMAX = 3 TEMP = FT FT = HT HT = TEMP TEMP = FA FA = HA HA = TEMP * * Now FA .ge. HA * END IF GT = G GA = ABS( GT ) IF( GA.EQ.ZERO ) THEN * * Diagonal matrix * SSMIN = HA SSMAX = FA CLT = ONE CRT = ONE SLT = ZERO SRT = ZERO ELSE GASMAL = .TRUE. IF( GA.GT.FA ) THEN PMAX = 2 IF( ( FA / GA ).LT.DLAMCH( 'EPS' ) ) THEN * * Case of very large GA * GASMAL = .FALSE. SSMAX = GA IF( HA.GT.ONE ) THEN SSMIN = FA / ( GA / HA ) ELSE SSMIN = ( FA / GA )*HA END IF CLT = ONE SLT = HT / GT SRT = ONE CRT = FT / GT END IF END IF IF( GASMAL ) THEN * * Normal case * D = FA - HA IF( D.EQ.FA ) THEN * * Copes with infinite F or H * L = ONE ELSE L = D / FA END IF * * Note that 0 .le. L .le. 1 * M = GT / FT * * Note that abs(M) .le. 1/macheps * T = TWO - L * * Note that T .ge. 1 * MM = M*M TT = T*T S = SQRT( TT+MM ) * * Note that 1 .le. S .le. 1 + 1/macheps * IF( L.EQ.ZERO ) THEN R = ABS( M ) ELSE R = SQRT( L*L+MM ) END IF * * Note that 0 .le. R .le. 1 + 1/macheps * A = HALF*( S+R ) * * Note that 1 .le. A .le. 1 + abs(M) * SSMIN = HA / A SSMAX = FA*A IF( MM.EQ.ZERO ) THEN * * Note that M is very tiny * IF( L.EQ.ZERO ) THEN T = SIGN( TWO, FT )*SIGN( ONE, GT ) ELSE T = GT / SIGN( D, FT ) + M / T END IF ELSE T = ( M / ( S+T )+M / ( R+L ) )*( ONE+A ) END IF L = SQRT( T*T+FOUR ) CRT = TWO / L SRT = T / L CLT = ( CRT+SRT*M ) / A SLT = ( HT / FT )*SRT / A END IF END IF IF( SWAP ) THEN CSL = SRT SNL = CRT CSR = SLT SNR = CLT ELSE CSL = CLT SNL = SLT CSR = CRT SNR = SRT END IF * * Correct signs of SSMAX and SSMIN * IF( PMAX.EQ.1 ) $ TSIGN = SIGN( ONE, CSR )*SIGN( ONE, CSL )*SIGN( ONE, F ) IF( PMAX.EQ.2 ) $ TSIGN = SIGN( ONE, SNR )*SIGN( ONE, CSL )*SIGN( ONE, G ) IF( PMAX.EQ.3 ) $ TSIGN = SIGN( ONE, SNR )*SIGN( ONE, SNL )*SIGN( ONE, H ) SSMAX = SIGN( SSMAX, TSIGN ) SSMIN = SIGN( SSMIN, TSIGN*SIGN( ONE, F )*SIGN( ONE, H ) ) RETURN * * End of DLASV2 * END SUBROUTINE DLASWP( N, A, LDA, K1, K2, IPIV, INCX ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INCX, K1, K2, LDA, N * .. * .. Array Arguments .. INTEGER IPIV( * ) DOUBLE PRECISION A( LDA, * ) * .. * * Purpose * ======= * * DLASWP performs a series of row interchanges on the matrix A. * One row interchange is initiated for each of rows K1 through K2 of A. * * Arguments * ========= * * N (input) INTEGER * The number of columns of the matrix A. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the matrix of column dimension N to which the row * interchanges will be applied. * On exit, the permuted matrix. * * LDA (input) INTEGER * The leading dimension of the array A. * * K1 (input) INTEGER * The first element of IPIV for which a row interchange will * be done. * * K2 (input) INTEGER * The last element of IPIV for which a row interchange will * be done. * * IPIV (input) INTEGER array, dimension (M*abs(INCX)) * The vector of pivot indices. Only the elements in positions * K1 through K2 of IPIV are accessed. * IPIV(K) = L implies rows K and L are to be interchanged. * * INCX (input) INTEGER * The increment between successive values of IPIV. If IPIV * is negative, the pivots are applied in reverse order. * * Further Details * =============== * * Modified by * R. C. Whaley, Computer Science Dept., Univ. of Tenn., Knoxville, USA * * ===================================================================== * * .. Local Scalars .. INTEGER I, I1, I2, INC, IP, IX, IX0, J, K, N32 DOUBLE PRECISION TEMP * .. * .. Executable Statements .. * * Interchange row I with row IPIV(I) for each of rows K1 through K2. * IF( INCX.GT.0 ) THEN IX0 = K1 I1 = K1 I2 = K2 INC = 1 ELSE IF( INCX.LT.0 ) THEN IX0 = 1 + ( 1-K2 )*INCX I1 = K2 I2 = K1 INC = -1 ELSE RETURN END IF * N32 = ( N / 32 )*32 IF( N32.NE.0 ) THEN DO 30 J = 1, N32, 32 IX = IX0 DO 20 I = I1, I2, INC IP = IPIV( IX ) IF( IP.NE.I ) THEN DO 10 K = J, J + 31 TEMP = A( I, K ) A( I, K ) = A( IP, K ) A( IP, K ) = TEMP 10 CONTINUE END IF IX = IX + INCX 20 CONTINUE 30 CONTINUE END IF IF( N32.NE.N ) THEN N32 = N32 + 1 IX = IX0 DO 50 I = I1, I2, INC IP = IPIV( IX ) IF( IP.NE.I ) THEN DO 40 K = N32, N TEMP = A( I, K ) A( I, K ) = A( IP, K ) A( IP, K ) = TEMP 40 CONTINUE END IF IX = IX + INCX 50 CONTINUE END IF * RETURN * * End of DLASWP * END SUBROUTINE DLASY2( LTRANL, LTRANR, ISGN, N1, N2, TL, LDTL, TR, $ LDTR, B, LDB, SCALE, X, LDX, XNORM, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. LOGICAL LTRANL, LTRANR INTEGER INFO, ISGN, LDB, LDTL, LDTR, LDX, N1, N2 DOUBLE PRECISION SCALE, XNORM * .. * .. Array Arguments .. DOUBLE PRECISION B( LDB, * ), TL( LDTL, * ), TR( LDTR, * ), $ X( LDX, * ) * .. * * Purpose * ======= * * DLASY2 solves for the N1 by N2 matrix X, 1 <= N1,N2 <= 2, in * * op(TL)*X + ISGN*X*op(TR) = SCALE*B, * * where TL is N1 by N1, TR is N2 by N2, B is N1 by N2, and ISGN = 1 or * -1. op(T) = T or T', where T' denotes the transpose of T. * * Arguments * ========= * * LTRANL (input) LOGICAL * On entry, LTRANL specifies the op(TL): * = .FALSE., op(TL) = TL, * = .TRUE., op(TL) = TL'. * * LTRANR (input) LOGICAL * On entry, LTRANR specifies the op(TR): * = .FALSE., op(TR) = TR, * = .TRUE., op(TR) = TR'. * * ISGN (input) INTEGER * On entry, ISGN specifies the sign of the equation * as described before. ISGN may only be 1 or -1. * * N1 (input) INTEGER * On entry, N1 specifies the order of matrix TL. * N1 may only be 0, 1 or 2. * * N2 (input) INTEGER * On entry, N2 specifies the order of matrix TR. * N2 may only be 0, 1 or 2. * * TL (input) DOUBLE PRECISION array, dimension (LDTL,2) * On entry, TL contains an N1 by N1 matrix. * * LDTL (input) INTEGER * The leading dimension of the matrix TL. LDTL >= max(1,N1). * * TR (input) DOUBLE PRECISION array, dimension (LDTR,2) * On entry, TR contains an N2 by N2 matrix. * * LDTR (input) INTEGER * The leading dimension of the matrix TR. LDTR >= max(1,N2). * * B (input) DOUBLE PRECISION array, dimension (LDB,2) * On entry, the N1 by N2 matrix B contains the right-hand * side of the equation. * * LDB (input) INTEGER * The leading dimension of the matrix B. LDB >= max(1,N1). * * SCALE (output) DOUBLE PRECISION * On exit, SCALE contains the scale factor. SCALE is chosen * less than or equal to 1 to prevent the solution overflowing. * * X (output) DOUBLE PRECISION array, dimension (LDX,2) * On exit, X contains the N1 by N2 solution. * * LDX (input) INTEGER * The leading dimension of the matrix X. LDX >= max(1,N1). * * XNORM (output) DOUBLE PRECISION * On exit, XNORM is the infinity-norm of the solution. * * INFO (output) INTEGER * On exit, INFO is set to * 0: successful exit. * 1: TL and TR have too close eigenvalues, so TL or * TR is perturbed to get a nonsingular equation. * NOTE: In the interests of speed, this routine does not * check the inputs for errors. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) DOUBLE PRECISION TWO, HALF, EIGHT PARAMETER ( TWO = 2.0D+0, HALF = 0.5D+0, EIGHT = 8.0D+0 ) * .. * .. Local Scalars .. LOGICAL BSWAP, XSWAP INTEGER I, IP, IPIV, IPSV, J, JP, JPSV, K DOUBLE PRECISION BET, EPS, GAM, L21, SGN, SMIN, SMLNUM, TAU1, $ TEMP, U11, U12, U22, XMAX * .. * .. Local Arrays .. LOGICAL BSWPIV( 4 ), XSWPIV( 4 ) INTEGER JPIV( 4 ), LOCL21( 4 ), LOCU12( 4 ), $ LOCU22( 4 ) DOUBLE PRECISION BTMP( 4 ), T16( 4, 4 ), TMP( 4 ), X2( 2 ) * .. * .. External Functions .. INTEGER IDAMAX DOUBLE PRECISION DLAMCH EXTERNAL IDAMAX, DLAMCH * .. * .. External Subroutines .. EXTERNAL DCOPY, DSWAP * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Data statements .. DATA LOCU12 / 3, 4, 1, 2 / , LOCL21 / 2, 1, 4, 3 / , $ LOCU22 / 4, 3, 2, 1 / DATA XSWPIV / .FALSE., .FALSE., .TRUE., .TRUE. / DATA BSWPIV / .FALSE., .TRUE., .FALSE., .TRUE. / * .. * .. Executable Statements .. * * Do not check the input parameters for errors * INFO = 0 * * Quick return if possible * IF( N1.EQ.0 .OR. N2.EQ.0 ) $ RETURN * * Set constants to control overflow * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) / EPS SGN = ISGN * K = N1 + N1 + N2 - 2 GO TO ( 10, 20, 30, 50 )K * * 1 by 1: TL11*X + SGN*X*TR11 = B11 * 10 CONTINUE TAU1 = TL( 1, 1 ) + SGN*TR( 1, 1 ) BET = ABS( TAU1 ) IF( BET.LE.SMLNUM ) THEN TAU1 = SMLNUM BET = SMLNUM INFO = 1 END IF * SCALE = ONE GAM = ABS( B( 1, 1 ) ) IF( SMLNUM*GAM.GT.BET ) $ SCALE = ONE / GAM * X( 1, 1 ) = ( B( 1, 1 )*SCALE ) / TAU1 XNORM = ABS( X( 1, 1 ) ) RETURN * * 1 by 2: * TL11*[X11 X12] + ISGN*[X11 X12]*op[TR11 TR12] = [B11 B12] * [TR21 TR22] * 20 CONTINUE * SMIN = MAX( EPS*MAX( ABS( TL( 1, 1 ) ), ABS( TR( 1, 1 ) ), $ ABS( TR( 1, 2 ) ), ABS( TR( 2, 1 ) ), ABS( TR( 2, 2 ) ) ), $ SMLNUM ) TMP( 1 ) = TL( 1, 1 ) + SGN*TR( 1, 1 ) TMP( 4 ) = TL( 1, 1 ) + SGN*TR( 2, 2 ) IF( LTRANR ) THEN TMP( 2 ) = SGN*TR( 2, 1 ) TMP( 3 ) = SGN*TR( 1, 2 ) ELSE TMP( 2 ) = SGN*TR( 1, 2 ) TMP( 3 ) = SGN*TR( 2, 1 ) END IF BTMP( 1 ) = B( 1, 1 ) BTMP( 2 ) = B( 1, 2 ) GO TO 40 * * 2 by 1: * op[TL11 TL12]*[X11] + ISGN* [X11]*TR11 = [B11] * [TL21 TL22] [X21] [X21] [B21] * 30 CONTINUE SMIN = MAX( EPS*MAX( ABS( TR( 1, 1 ) ), ABS( TL( 1, 1 ) ), $ ABS( TL( 1, 2 ) ), ABS( TL( 2, 1 ) ), ABS( TL( 2, 2 ) ) ), $ SMLNUM ) TMP( 1 ) = TL( 1, 1 ) + SGN*TR( 1, 1 ) TMP( 4 ) = TL( 2, 2 ) + SGN*TR( 1, 1 ) IF( LTRANL ) THEN TMP( 2 ) = TL( 1, 2 ) TMP( 3 ) = TL( 2, 1 ) ELSE TMP( 2 ) = TL( 2, 1 ) TMP( 3 ) = TL( 1, 2 ) END IF BTMP( 1 ) = B( 1, 1 ) BTMP( 2 ) = B( 2, 1 ) 40 CONTINUE * * Solve 2 by 2 system using complete pivoting. * Set pivots less than SMIN to SMIN. * IPIV = IDAMAX( 4, TMP, 1 ) U11 = TMP( IPIV ) IF( ABS( U11 ).LE.SMIN ) THEN INFO = 1 U11 = SMIN END IF U12 = TMP( LOCU12( IPIV ) ) L21 = TMP( LOCL21( IPIV ) ) / U11 U22 = TMP( LOCU22( IPIV ) ) - U12*L21 XSWAP = XSWPIV( IPIV ) BSWAP = BSWPIV( IPIV ) IF( ABS( U22 ).LE.SMIN ) THEN INFO = 1 U22 = SMIN END IF IF( BSWAP ) THEN TEMP = BTMP( 2 ) BTMP( 2 ) = BTMP( 1 ) - L21*TEMP BTMP( 1 ) = TEMP ELSE BTMP( 2 ) = BTMP( 2 ) - L21*BTMP( 1 ) END IF SCALE = ONE IF( ( TWO*SMLNUM )*ABS( BTMP( 2 ) ).GT.ABS( U22 ) .OR. $ ( TWO*SMLNUM )*ABS( BTMP( 1 ) ).GT.ABS( U11 ) ) THEN SCALE = HALF / MAX( ABS( BTMP( 1 ) ), ABS( BTMP( 2 ) ) ) BTMP( 1 ) = BTMP( 1 )*SCALE BTMP( 2 ) = BTMP( 2 )*SCALE END IF X2( 2 ) = BTMP( 2 ) / U22 X2( 1 ) = BTMP( 1 ) / U11 - ( U12 / U11 )*X2( 2 ) IF( XSWAP ) THEN TEMP = X2( 2 ) X2( 2 ) = X2( 1 ) X2( 1 ) = TEMP END IF X( 1, 1 ) = X2( 1 ) IF( N1.EQ.1 ) THEN X( 1, 2 ) = X2( 2 ) XNORM = ABS( X( 1, 1 ) ) + ABS( X( 1, 2 ) ) ELSE X( 2, 1 ) = X2( 2 ) XNORM = MAX( ABS( X( 1, 1 ) ), ABS( X( 2, 1 ) ) ) END IF RETURN * * 2 by 2: * op[TL11 TL12]*[X11 X12] +ISGN* [X11 X12]*op[TR11 TR12] = [B11 B12] * [TL21 TL22] [X21 X22] [X21 X22] [TR21 TR22] [B21 B22] * * Solve equivalent 4 by 4 system using complete pivoting. * Set pivots less than SMIN to SMIN. * 50 CONTINUE SMIN = MAX( ABS( TR( 1, 1 ) ), ABS( TR( 1, 2 ) ), $ ABS( TR( 2, 1 ) ), ABS( TR( 2, 2 ) ) ) SMIN = MAX( SMIN, ABS( TL( 1, 1 ) ), ABS( TL( 1, 2 ) ), $ ABS( TL( 2, 1 ) ), ABS( TL( 2, 2 ) ) ) SMIN = MAX( EPS*SMIN, SMLNUM ) BTMP( 1 ) = ZERO CALL DCOPY( 16, BTMP, 0, T16, 1 ) T16( 1, 1 ) = TL( 1, 1 ) + SGN*TR( 1, 1 ) T16( 2, 2 ) = TL( 2, 2 ) + SGN*TR( 1, 1 ) T16( 3, 3 ) = TL( 1, 1 ) + SGN*TR( 2, 2 ) T16( 4, 4 ) = TL( 2, 2 ) + SGN*TR( 2, 2 ) IF( LTRANL ) THEN T16( 1, 2 ) = TL( 2, 1 ) T16( 2, 1 ) = TL( 1, 2 ) T16( 3, 4 ) = TL( 2, 1 ) T16( 4, 3 ) = TL( 1, 2 ) ELSE T16( 1, 2 ) = TL( 1, 2 ) T16( 2, 1 ) = TL( 2, 1 ) T16( 3, 4 ) = TL( 1, 2 ) T16( 4, 3 ) = TL( 2, 1 ) END IF IF( LTRANR ) THEN T16( 1, 3 ) = SGN*TR( 1, 2 ) T16( 2, 4 ) = SGN*TR( 1, 2 ) T16( 3, 1 ) = SGN*TR( 2, 1 ) T16( 4, 2 ) = SGN*TR( 2, 1 ) ELSE T16( 1, 3 ) = SGN*TR( 2, 1 ) T16( 2, 4 ) = SGN*TR( 2, 1 ) T16( 3, 1 ) = SGN*TR( 1, 2 ) T16( 4, 2 ) = SGN*TR( 1, 2 ) END IF BTMP( 1 ) = B( 1, 1 ) BTMP( 2 ) = B( 2, 1 ) BTMP( 3 ) = B( 1, 2 ) BTMP( 4 ) = B( 2, 2 ) * * Perform elimination * DO 100 I = 1, 3 XMAX = ZERO DO 70 IP = I, 4 DO 60 JP = I, 4 IF( ABS( T16( IP, JP ) ).GE.XMAX ) THEN XMAX = ABS( T16( IP, JP ) ) IPSV = IP JPSV = JP END IF 60 CONTINUE 70 CONTINUE IF( IPSV.NE.I ) THEN CALL DSWAP( 4, T16( IPSV, 1 ), 4, T16( I, 1 ), 4 ) TEMP = BTMP( I ) BTMP( I ) = BTMP( IPSV ) BTMP( IPSV ) = TEMP END IF IF( JPSV.NE.I ) $ CALL DSWAP( 4, T16( 1, JPSV ), 1, T16( 1, I ), 1 ) JPIV( I ) = JPSV IF( ABS( T16( I, I ) ).LT.SMIN ) THEN INFO = 1 T16( I, I ) = SMIN END IF DO 90 J = I + 1, 4 T16( J, I ) = T16( J, I ) / T16( I, I ) BTMP( J ) = BTMP( J ) - T16( J, I )*BTMP( I ) DO 80 K = I + 1, 4 T16( J, K ) = T16( J, K ) - T16( J, I )*T16( I, K ) 80 CONTINUE 90 CONTINUE 100 CONTINUE IF( ABS( T16( 4, 4 ) ).LT.SMIN ) $ T16( 4, 4 ) = SMIN SCALE = ONE IF( ( EIGHT*SMLNUM )*ABS( BTMP( 1 ) ).GT.ABS( T16( 1, 1 ) ) .OR. $ ( EIGHT*SMLNUM )*ABS( BTMP( 2 ) ).GT.ABS( T16( 2, 2 ) ) .OR. $ ( EIGHT*SMLNUM )*ABS( BTMP( 3 ) ).GT.ABS( T16( 3, 3 ) ) .OR. $ ( EIGHT*SMLNUM )*ABS( BTMP( 4 ) ).GT.ABS( T16( 4, 4 ) ) ) THEN SCALE = ( ONE / EIGHT ) / MAX( ABS( BTMP( 1 ) ), $ ABS( BTMP( 2 ) ), ABS( BTMP( 3 ) ), ABS( BTMP( 4 ) ) ) BTMP( 1 ) = BTMP( 1 )*SCALE BTMP( 2 ) = BTMP( 2 )*SCALE BTMP( 3 ) = BTMP( 3 )*SCALE BTMP( 4 ) = BTMP( 4 )*SCALE END IF DO 120 I = 1, 4 K = 5 - I TEMP = ONE / T16( K, K ) TMP( K ) = BTMP( K )*TEMP DO 110 J = K + 1, 4 TMP( K ) = TMP( K ) - ( TEMP*T16( K, J ) )*TMP( J ) 110 CONTINUE 120 CONTINUE DO 130 I = 1, 3 IF( JPIV( 4-I ).NE.4-I ) THEN TEMP = TMP( 4-I ) TMP( 4-I ) = TMP( JPIV( 4-I ) ) TMP( JPIV( 4-I ) ) = TEMP END IF 130 CONTINUE X( 1, 1 ) = TMP( 1 ) X( 2, 1 ) = TMP( 2 ) X( 1, 2 ) = TMP( 3 ) X( 2, 2 ) = TMP( 4 ) XNORM = MAX( ABS( TMP( 1 ) )+ABS( TMP( 3 ) ), $ ABS( TMP( 2 ) )+ABS( TMP( 4 ) ) ) RETURN * * End of DLASY2 * END SUBROUTINE DLATDF( IJOB, N, Z, LDZ, RHS, RDSUM, RDSCAL, IPIV, $ JPIV ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IJOB, LDZ, N DOUBLE PRECISION RDSCAL, RDSUM * .. * .. Array Arguments .. INTEGER IPIV( * ), JPIV( * ) DOUBLE PRECISION RHS( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DLATDF uses the LU factorization of the n-by-n matrix Z computed by * DGETC2 and computes a contribution to the reciprocal Dif-estimate * by solving Z * x = b for x, and choosing the r.h.s. b such that * the norm of x is as large as possible. On entry RHS = b holds the * contribution from earlier solved sub-systems, and on return RHS = x. * * The factorization of Z returned by DGETC2 has the form Z = P*L*U*Q, * where P and Q are permutation matrices. L is lower triangular with * unit diagonal elements and U is upper triangular. * * Arguments * ========= * * IJOB (input) INTEGER * IJOB = 2: First compute an approximative null-vector e * of Z using DGECON, e is normalized and solve for * Zx = +-e - f with the sign giving the greater value * of 2-norm(x). About 5 times as expensive as Default. * IJOB .ne. 2: Local look ahead strategy where all entries of * the r.h.s. b is choosen as either +1 or -1 (Default). * * N (input) INTEGER * The number of columns of the matrix Z. * * Z (input) DOUBLE PRECISION array, dimension (LDZ, N) * On entry, the LU part of the factorization of the n-by-n * matrix Z computed by DGETC2: Z = P * L * U * Q * * LDZ (input) INTEGER * The leading dimension of the array Z. LDA >= max(1, N). * * RHS (input/output) DOUBLE PRECISION array, dimension N. * On entry, RHS contains contributions from other subsystems. * On exit, RHS contains the solution of the subsystem with * entries acoording to the value of IJOB (see above). * * RDSUM (input/output) DOUBLE PRECISION * On entry, the sum of squares of computed contributions to * the Dif-estimate under computation by DTGSYL, where the * scaling factor RDSCAL (see below) has been factored out. * On exit, the corresponding sum of squares updated with the * contributions from the current sub-system. * If TRANS = 'T' RDSUM is not touched. * NOTE: RDSUM only makes sense when DTGSY2 is called by STGSYL. * * RDSCAL (input/output) DOUBLE PRECISION * On entry, scaling factor used to prevent overflow in RDSUM. * On exit, RDSCAL is updated w.r.t. the current contributions * in RDSUM. * If TRANS = 'T', RDSCAL is not touched. * NOTE: RDSCAL only makes sense when DTGSY2 is called by * DTGSYL. * * IPIV (input) INTEGER array, dimension (N). * The pivot indices; for 1 <= i <= N, row i of the * matrix has been interchanged with row IPIV(i). * * JPIV (input) INTEGER array, dimension (N). * The pivot indices; for 1 <= j <= N, column j of the * matrix has been interchanged with column JPIV(j). * * Further Details * =============== * * Based on contributions by * Bo Kagstrom and Peter Poromaa, Department of Computing Science, * Umea University, S-901 87 Umea, Sweden. * * This routine is a further developed implementation of algorithm * BSOLVE in [1] using complete pivoting in the LU factorization. * * [1] Bo Kagstrom and Lars Westin, * Generalized Schur Methods with Condition Estimators for * Solving the Generalized Sylvester Equation, IEEE Transactions * on Automatic Control, Vol. 34, No. 7, July 1989, pp 745-751. * * [2] Peter Poromaa, * On Efficient and Robust Estimators for the Separation * between two Regular Matrix Pairs with Applications in * Condition Estimation. Report IMINF-95.05, Departement of * Computing Science, Umea University, S-901 87 Umea, Sweden, 1995. * * ===================================================================== * * .. Parameters .. INTEGER MAXDIM PARAMETER ( MAXDIM = 8 ) DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I, INFO, J, K DOUBLE PRECISION BM, BP, PMONE, SMINU, SPLUS, TEMP * .. * .. Local Arrays .. INTEGER IWORK( MAXDIM ) DOUBLE PRECISION WORK( 4*MAXDIM ), XM( MAXDIM ), XP( MAXDIM ) * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DGECON, DGESC2, DLASSQ, DLASWP, $ DSCAL * .. * .. External Functions .. DOUBLE PRECISION DASUM, DDOT EXTERNAL DASUM, DDOT * .. * .. Intrinsic Functions .. INTRINSIC ABS, SQRT * .. * .. Executable Statements .. * IF( IJOB.NE.2 ) THEN * * Apply permutations IPIV to RHS * CALL DLASWP( 1, RHS, LDZ, 1, N-1, IPIV, 1 ) * * Solve for L-part choosing RHS either to +1 or -1. * PMONE = -ONE * DO 10 J = 1, N - 1 BP = RHS( J ) + ONE BM = RHS( J ) - ONE SPLUS = ONE * * Look-ahead for L-part RHS(1:N-1) = + or -1, SPLUS and * SMIN computed more efficiently than in BSOLVE [1]. * SPLUS = SPLUS + DDOT( N-J, Z( J+1, J ), 1, Z( J+1, J ), 1 ) SMINU = DDOT( N-J, Z( J+1, J ), 1, RHS( J+1 ), 1 ) SPLUS = SPLUS*RHS( J ) IF( SPLUS.GT.SMINU ) THEN RHS( J ) = BP ELSE IF( SMINU.GT.SPLUS ) THEN RHS( J ) = BM ELSE * * In this case the updating sums are equal and we can * choose RHS(J) +1 or -1. The first time this happens * we choose -1, thereafter +1. This is a simple way to * get good estimates of matrices like Byers well-known * example (see [1]). (Not done in BSOLVE.) * RHS( J ) = RHS( J ) + PMONE PMONE = ONE END IF * * Compute the remaining r.h.s. * TEMP = -RHS( J ) CALL DAXPY( N-J, TEMP, Z( J+1, J ), 1, RHS( J+1 ), 1 ) * 10 CONTINUE * * Solve for U-part, look-ahead for RHS(N) = +-1. This is not done * in BSOLVE and will hopefully give us a better estimate because * any ill-conditioning of the original matrix is transfered to U * and not to L. U(N, N) is an approximation to sigma_min(LU). * CALL DCOPY( N-1, RHS, 1, XP, 1 ) XP( N ) = RHS( N ) + ONE RHS( N ) = RHS( N ) - ONE SPLUS = ZERO SMINU = ZERO DO 30 I = N, 1, -1 TEMP = ONE / Z( I, I ) XP( I ) = XP( I )*TEMP RHS( I ) = RHS( I )*TEMP DO 20 K = I + 1, N XP( I ) = XP( I ) - XP( K )*( Z( I, K )*TEMP ) RHS( I ) = RHS( I ) - RHS( K )*( Z( I, K )*TEMP ) 20 CONTINUE SPLUS = SPLUS + ABS( XP( I ) ) SMINU = SMINU + ABS( RHS( I ) ) 30 CONTINUE IF( SPLUS.GT.SMINU ) $ CALL DCOPY( N, XP, 1, RHS, 1 ) * * Apply the permutations JPIV to the computed solution (RHS) * CALL DLASWP( 1, RHS, LDZ, 1, N-1, JPIV, -1 ) * * Compute the sum of squares * CALL DLASSQ( N, RHS, 1, RDSCAL, RDSUM ) * ELSE * * IJOB = 2, Compute approximate nullvector XM of Z * CALL DGECON( 'I', N, Z, LDZ, ONE, TEMP, WORK, IWORK, INFO ) CALL DCOPY( N, WORK( N+1 ), 1, XM, 1 ) * * Compute RHS * CALL DLASWP( 1, XM, LDZ, 1, N-1, IPIV, -1 ) TEMP = ONE / SQRT( DDOT( N, XM, 1, XM, 1 ) ) CALL DSCAL( N, TEMP, XM, 1 ) CALL DCOPY( N, XM, 1, XP, 1 ) CALL DAXPY( N, ONE, RHS, 1, XP, 1 ) CALL DAXPY( N, -ONE, XM, 1, RHS, 1 ) CALL DGESC2( N, Z, LDZ, RHS, IPIV, JPIV, TEMP ) CALL DGESC2( N, Z, LDZ, XP, IPIV, JPIV, TEMP ) IF( DASUM( N, XP, 1 ).GT.DASUM( N, RHS, 1 ) ) $ CALL DCOPY( N, XP, 1, RHS, 1 ) * * Compute the sum of squares * CALL DLASSQ( N, RHS, 1, RDSCAL, RDSUM ) * END IF * RETURN * * End of DLATDF * END SUBROUTINE DLATRD( UPLO, N, NB, A, LDA, E, TAU, W, LDW ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER LDA, LDW, N, NB * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), E( * ), TAU( * ), W( LDW, * ) * .. * * Purpose * ======= * * DLATRD reduces NB rows and columns of a real symmetric matrix A to * symmetric tridiagonal form by an orthogonal similarity * transformation Q' * A * Q, and returns the matrices V and W which are * needed to apply the transformation to the unreduced part of A. * * If UPLO = 'U', DLATRD reduces the last NB rows and columns of a * matrix, of which the upper triangle is supplied; * if UPLO = 'L', DLATRD reduces the first NB rows and columns of a * matrix, of which the lower triangle is supplied. * * This is an auxiliary routine called by DSYTRD. * * Arguments * ========= * * UPLO (input) CHARACTER * Specifies whether the upper or lower triangular part of the * symmetric matrix A is stored: * = 'U': Upper triangular * = 'L': Lower triangular * * N (input) INTEGER * The order of the matrix A. * * NB (input) INTEGER * The number of rows and columns to be reduced. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A. If UPLO = 'U', the leading * n-by-n upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading n-by-n lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. * On exit: * if UPLO = 'U', the last NB columns have been reduced to * tridiagonal form, with the diagonal elements overwriting * the diagonal elements of A; the elements above the diagonal * with the array TAU, represent the orthogonal matrix Q as a * product of elementary reflectors; * if UPLO = 'L', the first NB columns have been reduced to * tridiagonal form, with the diagonal elements overwriting * the diagonal elements of A; the elements below the diagonal * with the array TAU, represent the orthogonal matrix Q as a * product of elementary reflectors. * See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= (1,N). * * E (output) DOUBLE PRECISION array, dimension (N-1) * If UPLO = 'U', E(n-nb:n-1) contains the superdiagonal * elements of the last NB columns of the reduced matrix; * if UPLO = 'L', E(1:nb) contains the subdiagonal elements of * the first NB columns of the reduced matrix. * * TAU (output) DOUBLE PRECISION array, dimension (N-1) * The scalar factors of the elementary reflectors, stored in * TAU(n-nb:n-1) if UPLO = 'U', and in TAU(1:nb) if UPLO = 'L'. * See Further Details. * * W (output) DOUBLE PRECISION array, dimension (LDW,NB) * The n-by-nb matrix W required to update the unreduced part * of A. * * LDW (input) INTEGER * The leading dimension of the array W. LDW >= max(1,N). * * Further Details * =============== * * If UPLO = 'U', the matrix Q is represented as a product of elementary * reflectors * * Q = H(n) H(n-1) . . . H(n-nb+1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(i:n) = 0 and v(i-1) = 1; v(1:i-1) is stored on exit in A(1:i-1,i), * and tau in TAU(i-1). * * If UPLO = 'L', the matrix Q is represented as a product of elementary * reflectors * * Q = H(1) H(2) . . . H(nb). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i) = 0 and v(i+1) = 1; v(i+1:n) is stored on exit in A(i+1:n,i), * and tau in TAU(i). * * The elements of the vectors v together form the n-by-nb matrix V * which is needed, with W, to apply the transformation to the unreduced * part of the matrix, using a symmetric rank-2k update of the form: * A := A - V*W' - W*V'. * * The contents of A on exit are illustrated by the following examples * with n = 5 and nb = 2: * * if UPLO = 'U': if UPLO = 'L': * * ( a a a v4 v5 ) ( d ) * ( a a v4 v5 ) ( 1 d ) * ( a 1 v5 ) ( v1 1 a ) * ( d 1 ) ( v1 v2 a a ) * ( d ) ( v1 v2 a a a ) * * where d denotes a diagonal element of the reduced matrix, a denotes * an element of the original matrix that is unchanged, and vi denotes * an element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, HALF PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, HALF = 0.5D+0 ) * .. * .. Local Scalars .. INTEGER I, IW DOUBLE PRECISION ALPHA * .. * .. External Subroutines .. EXTERNAL DAXPY, DGEMV, DLARFG, DSCAL, DSYMV * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DDOT EXTERNAL LSAME, DDOT * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * * Quick return if possible * IF( N.LE.0 ) $ RETURN * IF( LSAME( UPLO, 'U' ) ) THEN * * Reduce last NB columns of upper triangle * DO 10 I = N, N - NB + 1, -1 IW = I - N + NB IF( I.LT.N ) THEN * * Update A(1:i,i) * CALL DGEMV( 'No transpose', I, N-I, -ONE, A( 1, I+1 ), $ LDA, W( I, IW+1 ), LDW, ONE, A( 1, I ), 1 ) CALL DGEMV( 'No transpose', I, N-I, -ONE, W( 1, IW+1 ), $ LDW, A( I, I+1 ), LDA, ONE, A( 1, I ), 1 ) END IF IF( I.GT.1 ) THEN * * Generate elementary reflector H(i) to annihilate * A(1:i-2,i) * CALL DLARFG( I-1, A( I-1, I ), A( 1, I ), 1, TAU( I-1 ) ) E( I-1 ) = A( I-1, I ) A( I-1, I ) = ONE * * Compute W(1:i-1,i) * CALL DSYMV( 'Upper', I-1, ONE, A, LDA, A( 1, I ), 1, $ ZERO, W( 1, IW ), 1 ) IF( I.LT.N ) THEN CALL DGEMV( 'Transpose', I-1, N-I, ONE, W( 1, IW+1 ), $ LDW, A( 1, I ), 1, ZERO, W( I+1, IW ), 1 ) CALL DGEMV( 'No transpose', I-1, N-I, -ONE, $ A( 1, I+1 ), LDA, W( I+1, IW ), 1, ONE, $ W( 1, IW ), 1 ) CALL DGEMV( 'Transpose', I-1, N-I, ONE, A( 1, I+1 ), $ LDA, A( 1, I ), 1, ZERO, W( I+1, IW ), 1 ) CALL DGEMV( 'No transpose', I-1, N-I, -ONE, $ W( 1, IW+1 ), LDW, W( I+1, IW ), 1, ONE, $ W( 1, IW ), 1 ) END IF CALL DSCAL( I-1, TAU( I-1 ), W( 1, IW ), 1 ) ALPHA = -HALF*TAU( I-1 )*DDOT( I-1, W( 1, IW ), 1, $ A( 1, I ), 1 ) CALL DAXPY( I-1, ALPHA, A( 1, I ), 1, W( 1, IW ), 1 ) END IF * 10 CONTINUE ELSE * * Reduce first NB columns of lower triangle * DO 20 I = 1, NB * * Update A(i:n,i) * CALL DGEMV( 'No transpose', N-I+1, I-1, -ONE, A( I, 1 ), $ LDA, W( I, 1 ), LDW, ONE, A( I, I ), 1 ) CALL DGEMV( 'No transpose', N-I+1, I-1, -ONE, W( I, 1 ), $ LDW, A( I, 1 ), LDA, ONE, A( I, I ), 1 ) IF( I.LT.N ) THEN * * Generate elementary reflector H(i) to annihilate * A(i+2:n,i) * CALL DLARFG( N-I, A( I+1, I ), A( MIN( I+2, N ), I ), 1, $ TAU( I ) ) E( I ) = A( I+1, I ) A( I+1, I ) = ONE * * Compute W(i+1:n,i) * CALL DSYMV( 'Lower', N-I, ONE, A( I+1, I+1 ), LDA, $ A( I+1, I ), 1, ZERO, W( I+1, I ), 1 ) CALL DGEMV( 'Transpose', N-I, I-1, ONE, W( I+1, 1 ), LDW, $ A( I+1, I ), 1, ZERO, W( 1, I ), 1 ) CALL DGEMV( 'No transpose', N-I, I-1, -ONE, A( I+1, 1 ), $ LDA, W( 1, I ), 1, ONE, W( I+1, I ), 1 ) CALL DGEMV( 'Transpose', N-I, I-1, ONE, A( I+1, 1 ), LDA, $ A( I+1, I ), 1, ZERO, W( 1, I ), 1 ) CALL DGEMV( 'No transpose', N-I, I-1, -ONE, W( I+1, 1 ), $ LDW, W( 1, I ), 1, ONE, W( I+1, I ), 1 ) CALL DSCAL( N-I, TAU( I ), W( I+1, I ), 1 ) ALPHA = -HALF*TAU( I )*DDOT( N-I, W( I+1, I ), 1, $ A( I+1, I ), 1 ) CALL DAXPY( N-I, ALPHA, A( I+1, I ), 1, W( I+1, I ), 1 ) END IF * 20 CONTINUE END IF * RETURN * * End of DLATRD * END SUBROUTINE DLATRS( UPLO, TRANS, DIAG, NORMIN, N, A, LDA, X, SCALE, $ CNORM, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1992 * * .. Scalar Arguments .. CHARACTER DIAG, NORMIN, TRANS, UPLO INTEGER INFO, LDA, N DOUBLE PRECISION SCALE * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), CNORM( * ), X( * ) * .. * * Purpose * ======= * * DLATRS solves one of the triangular systems * * A *x = s*b or A'*x = s*b * * with scaling to prevent overflow. Here A is an upper or lower * triangular matrix, A' denotes the transpose of A, x and b are * n-element vectors, and s is a scaling factor, usually less than * or equal to 1, chosen so that the components of x will be less than * the overflow threshold. If the unscaled problem will not cause * overflow, the Level 2 BLAS routine DTRSV is called. If the matrix A * is singular (A(j,j) = 0 for some j), then s is set to 0 and a * non-trivial solution to A*x = 0 is returned. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * Specifies whether the matrix A is upper or lower triangular. * = 'U': Upper triangular * = 'L': Lower triangular * * TRANS (input) CHARACTER*1 * Specifies the operation applied to A. * = 'N': Solve A * x = s*b (No transpose) * = 'T': Solve A'* x = s*b (Transpose) * = 'C': Solve A'* x = s*b (Conjugate transpose = Transpose) * * DIAG (input) CHARACTER*1 * Specifies whether or not the matrix A is unit triangular. * = 'N': Non-unit triangular * = 'U': Unit triangular * * NORMIN (input) CHARACTER*1 * Specifies whether CNORM has been set or not. * = 'Y': CNORM contains the column norms on entry * = 'N': CNORM is not set on entry. On exit, the norms will * be computed and stored in CNORM. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,N) * The triangular matrix A. If UPLO = 'U', the leading n by n * upper triangular part of the array A contains the upper * triangular matrix, and the strictly lower triangular part of * A is not referenced. If UPLO = 'L', the leading n by n lower * triangular part of the array A contains the lower triangular * matrix, and the strictly upper triangular part of A is not * referenced. If DIAG = 'U', the diagonal elements of A are * also not referenced and are assumed to be 1. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max (1,N). * * X (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the right hand side b of the triangular system. * On exit, X is overwritten by the solution vector x. * * SCALE (output) DOUBLE PRECISION * The scaling factor s for the triangular system * A * x = s*b or A'* x = s*b. * If SCALE = 0, the matrix A is singular or badly scaled, and * the vector x is an exact or approximate solution to A*x = 0. * * CNORM (input or output) DOUBLE PRECISION array, dimension (N) * * If NORMIN = 'Y', CNORM is an input argument and CNORM(j) * contains the norm of the off-diagonal part of the j-th column * of A. If TRANS = 'N', CNORM(j) must be greater than or equal * to the infinity-norm, and if TRANS = 'T' or 'C', CNORM(j) * must be greater than or equal to the 1-norm. * * If NORMIN = 'N', CNORM is an output argument and CNORM(j) * returns the 1-norm of the offdiagonal part of the j-th column * of A. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -k, the k-th argument had an illegal value * * Further Details * ======= ======= * * A rough bound on x is computed; if that is less than overflow, DTRSV * is called, otherwise, specific code is used which checks for possible * overflow or divide-by-zero at every operation. * * A columnwise scheme is used for solving A*x = b. The basic algorithm * if A is lower triangular is * * x[1:n] := b[1:n] * for j = 1, ..., n * x(j) := x(j) / A(j,j) * x[j+1:n] := x[j+1:n] - x(j) * A[j+1:n,j] * end * * Define bounds on the components of x after j iterations of the loop: * M(j) = bound on x[1:j] * G(j) = bound on x[j+1:n] * Initially, let M(0) = 0 and G(0) = max{x(i), i=1,...,n}. * * Then for iteration j+1 we have * M(j+1) <= G(j) / | A(j+1,j+1) | * G(j+1) <= G(j) + M(j+1) * | A[j+2:n,j+1] | * <= G(j) ( 1 + CNORM(j+1) / | A(j+1,j+1) | ) * * where CNORM(j+1) is greater than or equal to the infinity-norm of * column j+1 of A, not counting the diagonal. Hence * * G(j) <= G(0) product ( 1 + CNORM(i) / | A(i,i) | ) * 1<=i<=j * and * * |x(j)| <= ( G(0) / |A(j,j)| ) product ( 1 + CNORM(i) / |A(i,i)| ) * 1<=i< j * * Since |x(j)| <= M(j), we use the Level 2 BLAS routine DTRSV if the * reciprocal of the largest M(j), j=1,..,n, is larger than * max(underflow, 1/overflow). * * The bound on x(j) is also used to determine when a step in the * columnwise method can be performed without fear of overflow. If * the computed bound is greater than a large constant, x is scaled to * prevent overflow, but if the bound overflows, x is set to 0, x(j) to * 1, and scale to 0, and a non-trivial solution to A*x = 0 is found. * * Similarly, a row-wise scheme is used to solve A'*x = b. The basic * algorithm for A upper triangular is * * for j = 1, ..., n * x(j) := ( b(j) - A[1:j-1,j]' * x[1:j-1] ) / A(j,j) * end * * We simultaneously compute two bounds * G(j) = bound on ( b(i) - A[1:i-1,i]' * x[1:i-1] ), 1<=i<=j * M(j) = bound on x(i), 1<=i<=j * * The initial values are G(0) = 0, M(0) = max{b(i), i=1,..,n}, and we * add the constraint G(j) >= G(j-1) and M(j) >= M(j-1) for j >= 1. * Then the bound on x(j) is * * M(j) <= M(j-1) * ( 1 + CNORM(j) ) / | A(j,j) | * * <= M(0) * product ( ( 1 + CNORM(i) ) / |A(i,i)| ) * 1<=i<=j * * and we can safely call DTRSV if 1/M(n) and 1/G(n) are both greater * than max(underflow, 1/overflow). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, HALF, ONE PARAMETER ( ZERO = 0.0D+0, HALF = 0.5D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL NOTRAN, NOUNIT, UPPER INTEGER I, IMAX, J, JFIRST, JINC, JLAST DOUBLE PRECISION BIGNUM, GROW, REC, SMLNUM, SUMJ, TJJ, TJJS, $ TMAX, TSCAL, USCAL, XBND, XJ, XMAX * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX DOUBLE PRECISION DASUM, DDOT, DLAMCH EXTERNAL LSAME, IDAMAX, DASUM, DDOT, DLAMCH * .. * .. External Subroutines .. EXTERNAL DAXPY, DSCAL, DTRSV, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * INFO = 0 UPPER = LSAME( UPLO, 'U' ) NOTRAN = LSAME( TRANS, 'N' ) NOUNIT = LSAME( DIAG, 'N' ) * * Test the input parameters. * IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) .AND. .NOT. $ LSAME( TRANS, 'C' ) ) THEN INFO = -2 ELSE IF( .NOT.NOUNIT .AND. .NOT.LSAME( DIAG, 'U' ) ) THEN INFO = -3 ELSE IF( .NOT.LSAME( NORMIN, 'Y' ) .AND. .NOT. $ LSAME( NORMIN, 'N' ) ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -7 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLATRS', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * * Determine machine dependent parameters to control overflow. * SMLNUM = DLAMCH( 'Safe minimum' ) / DLAMCH( 'Precision' ) BIGNUM = ONE / SMLNUM SCALE = ONE * IF( LSAME( NORMIN, 'N' ) ) THEN * * Compute the 1-norm of each column, not including the diagonal. * IF( UPPER ) THEN * * A is upper triangular. * DO 10 J = 1, N CNORM( J ) = DASUM( J-1, A( 1, J ), 1 ) 10 CONTINUE ELSE * * A is lower triangular. * DO 20 J = 1, N - 1 CNORM( J ) = DASUM( N-J, A( J+1, J ), 1 ) 20 CONTINUE CNORM( N ) = ZERO END IF END IF * * Scale the column norms by TSCAL if the maximum element in CNORM is * greater than BIGNUM. * IMAX = IDAMAX( N, CNORM, 1 ) TMAX = CNORM( IMAX ) IF( TMAX.LE.BIGNUM ) THEN TSCAL = ONE ELSE TSCAL = ONE / ( SMLNUM*TMAX ) CALL DSCAL( N, TSCAL, CNORM, 1 ) END IF * * Compute a bound on the computed solution vector to see if the * Level 2 BLAS routine DTRSV can be used. * J = IDAMAX( N, X, 1 ) XMAX = ABS( X( J ) ) XBND = XMAX IF( NOTRAN ) THEN * * Compute the growth in A * x = b. * IF( UPPER ) THEN JFIRST = N JLAST = 1 JINC = -1 ELSE JFIRST = 1 JLAST = N JINC = 1 END IF * IF( TSCAL.NE.ONE ) THEN GROW = ZERO GO TO 50 END IF * IF( NOUNIT ) THEN * * A is non-unit triangular. * * Compute GROW = 1/G(j) and XBND = 1/M(j). * Initially, G(0) = max{x(i), i=1,...,n}. * GROW = ONE / MAX( XBND, SMLNUM ) XBND = GROW DO 30 J = JFIRST, JLAST, JINC * * Exit the loop if the growth factor is too small. * IF( GROW.LE.SMLNUM ) $ GO TO 50 * * M(j) = G(j-1) / abs(A(j,j)) * TJJ = ABS( A( J, J ) ) XBND = MIN( XBND, MIN( ONE, TJJ )*GROW ) IF( TJJ+CNORM( J ).GE.SMLNUM ) THEN * * G(j) = G(j-1)*( 1 + CNORM(j) / abs(A(j,j)) ) * GROW = GROW*( TJJ / ( TJJ+CNORM( J ) ) ) ELSE * * G(j) could overflow, set GROW to 0. * GROW = ZERO END IF 30 CONTINUE GROW = XBND ELSE * * A is unit triangular. * * Compute GROW = 1/G(j), where G(0) = max{x(i), i=1,...,n}. * GROW = MIN( ONE, ONE / MAX( XBND, SMLNUM ) ) DO 40 J = JFIRST, JLAST, JINC * * Exit the loop if the growth factor is too small. * IF( GROW.LE.SMLNUM ) $ GO TO 50 * * G(j) = G(j-1)*( 1 + CNORM(j) ) * GROW = GROW*( ONE / ( ONE+CNORM( J ) ) ) 40 CONTINUE END IF 50 CONTINUE * ELSE * * Compute the growth in A' * x = b. * IF( UPPER ) THEN JFIRST = 1 JLAST = N JINC = 1 ELSE JFIRST = N JLAST = 1 JINC = -1 END IF * IF( TSCAL.NE.ONE ) THEN GROW = ZERO GO TO 80 END IF * IF( NOUNIT ) THEN * * A is non-unit triangular. * * Compute GROW = 1/G(j) and XBND = 1/M(j). * Initially, M(0) = max{x(i), i=1,...,n}. * GROW = ONE / MAX( XBND, SMLNUM ) XBND = GROW DO 60 J = JFIRST, JLAST, JINC * * Exit the loop if the growth factor is too small. * IF( GROW.LE.SMLNUM ) $ GO TO 80 * * G(j) = max( G(j-1), M(j-1)*( 1 + CNORM(j) ) ) * XJ = ONE + CNORM( J ) GROW = MIN( GROW, XBND / XJ ) * * M(j) = M(j-1)*( 1 + CNORM(j) ) / abs(A(j,j)) * TJJ = ABS( A( J, J ) ) IF( XJ.GT.TJJ ) $ XBND = XBND*( TJJ / XJ ) 60 CONTINUE GROW = MIN( GROW, XBND ) ELSE * * A is unit triangular. * * Compute GROW = 1/G(j), where G(0) = max{x(i), i=1,...,n}. * GROW = MIN( ONE, ONE / MAX( XBND, SMLNUM ) ) DO 70 J = JFIRST, JLAST, JINC * * Exit the loop if the growth factor is too small. * IF( GROW.LE.SMLNUM ) $ GO TO 80 * * G(j) = ( 1 + CNORM(j) )*G(j-1) * XJ = ONE + CNORM( J ) GROW = GROW / XJ 70 CONTINUE END IF 80 CONTINUE END IF * IF( ( GROW*TSCAL ).GT.SMLNUM ) THEN * * Use the Level 2 BLAS solve if the reciprocal of the bound on * elements of X is not too small. * CALL DTRSV( UPLO, TRANS, DIAG, N, A, LDA, X, 1 ) ELSE * * Use a Level 1 BLAS solve, scaling intermediate results. * IF( XMAX.GT.BIGNUM ) THEN * * Scale X so that its components are less than or equal to * BIGNUM in absolute value. * SCALE = BIGNUM / XMAX CALL DSCAL( N, SCALE, X, 1 ) XMAX = BIGNUM END IF * IF( NOTRAN ) THEN * * Solve A * x = b * DO 110 J = JFIRST, JLAST, JINC * * Compute x(j) = b(j) / A(j,j), scaling x if necessary. * XJ = ABS( X( J ) ) IF( NOUNIT ) THEN TJJS = A( J, J )*TSCAL ELSE TJJS = TSCAL IF( TSCAL.EQ.ONE ) $ GO TO 100 END IF TJJ = ABS( TJJS ) IF( TJJ.GT.SMLNUM ) THEN * * abs(A(j,j)) > SMLNUM: * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.TJJ*BIGNUM ) THEN * * Scale x by 1/b(j). * REC = ONE / XJ CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF X( J ) = X( J ) / TJJS XJ = ABS( X( J ) ) ELSE IF( TJJ.GT.ZERO ) THEN * * 0 < abs(A(j,j)) <= SMLNUM: * IF( XJ.GT.TJJ*BIGNUM ) THEN * * Scale x by (1/abs(x(j)))*abs(A(j,j))*BIGNUM * to avoid overflow when dividing by A(j,j). * REC = ( TJJ*BIGNUM ) / XJ IF( CNORM( J ).GT.ONE ) THEN * * Scale by 1/CNORM(j) to avoid overflow when * multiplying x(j) times column j. * REC = REC / CNORM( J ) END IF CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF X( J ) = X( J ) / TJJS XJ = ABS( X( J ) ) ELSE * * A(j,j) = 0: Set x(1:n) = 0, x(j) = 1, and * scale = 0, and compute a solution to A*x = 0. * DO 90 I = 1, N X( I ) = ZERO 90 CONTINUE X( J ) = ONE XJ = ONE SCALE = ZERO XMAX = ZERO END IF 100 CONTINUE * * Scale x if necessary to avoid overflow when adding a * multiple of column j of A. * IF( XJ.GT.ONE ) THEN REC = ONE / XJ IF( CNORM( J ).GT.( BIGNUM-XMAX )*REC ) THEN * * Scale x by 1/(2*abs(x(j))). * REC = REC*HALF CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC END IF ELSE IF( XJ*CNORM( J ).GT.( BIGNUM-XMAX ) ) THEN * * Scale x by 1/2. * CALL DSCAL( N, HALF, X, 1 ) SCALE = SCALE*HALF END IF * IF( UPPER ) THEN IF( J.GT.1 ) THEN * * Compute the update * x(1:j-1) := x(1:j-1) - x(j) * A(1:j-1,j) * CALL DAXPY( J-1, -X( J )*TSCAL, A( 1, J ), 1, X, $ 1 ) I = IDAMAX( J-1, X, 1 ) XMAX = ABS( X( I ) ) END IF ELSE IF( J.LT.N ) THEN * * Compute the update * x(j+1:n) := x(j+1:n) - x(j) * A(j+1:n,j) * CALL DAXPY( N-J, -X( J )*TSCAL, A( J+1, J ), 1, $ X( J+1 ), 1 ) I = J + IDAMAX( N-J, X( J+1 ), 1 ) XMAX = ABS( X( I ) ) END IF END IF 110 CONTINUE * ELSE * * Solve A' * x = b * DO 160 J = JFIRST, JLAST, JINC * * Compute x(j) = b(j) - sum A(k,j)*x(k). * k<>j * XJ = ABS( X( J ) ) USCAL = TSCAL REC = ONE / MAX( XMAX, ONE ) IF( CNORM( J ).GT.( BIGNUM-XJ )*REC ) THEN * * If x(j) could overflow, scale x by 1/(2*XMAX). * REC = REC*HALF IF( NOUNIT ) THEN TJJS = A( J, J )*TSCAL ELSE TJJS = TSCAL END IF TJJ = ABS( TJJS ) IF( TJJ.GT.ONE ) THEN * * Divide by A(j,j) when scaling x if A(j,j) > 1. * REC = MIN( ONE, REC*TJJ ) USCAL = USCAL / TJJS END IF IF( REC.LT.ONE ) THEN CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF * SUMJ = ZERO IF( USCAL.EQ.ONE ) THEN * * If the scaling needed for A in the dot product is 1, * call DDOT to perform the dot product. * IF( UPPER ) THEN SUMJ = DDOT( J-1, A( 1, J ), 1, X, 1 ) ELSE IF( J.LT.N ) THEN SUMJ = DDOT( N-J, A( J+1, J ), 1, X( J+1 ), 1 ) END IF ELSE * * Otherwise, use in-line code for the dot product. * IF( UPPER ) THEN DO 120 I = 1, J - 1 SUMJ = SUMJ + ( A( I, J )*USCAL )*X( I ) 120 CONTINUE ELSE IF( J.LT.N ) THEN DO 130 I = J + 1, N SUMJ = SUMJ + ( A( I, J )*USCAL )*X( I ) 130 CONTINUE END IF END IF * IF( USCAL.EQ.TSCAL ) THEN * * Compute x(j) := ( x(j) - sumj ) / A(j,j) if 1/A(j,j) * was not used to scale the dotproduct. * X( J ) = X( J ) - SUMJ XJ = ABS( X( J ) ) IF( NOUNIT ) THEN TJJS = A( J, J )*TSCAL ELSE TJJS = TSCAL IF( TSCAL.EQ.ONE ) $ GO TO 150 END IF * * Compute x(j) = x(j) / A(j,j), scaling if necessary. * TJJ = ABS( TJJS ) IF( TJJ.GT.SMLNUM ) THEN * * abs(A(j,j)) > SMLNUM: * IF( TJJ.LT.ONE ) THEN IF( XJ.GT.TJJ*BIGNUM ) THEN * * Scale X by 1/abs(x(j)). * REC = ONE / XJ CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF END IF X( J ) = X( J ) / TJJS ELSE IF( TJJ.GT.ZERO ) THEN * * 0 < abs(A(j,j)) <= SMLNUM: * IF( XJ.GT.TJJ*BIGNUM ) THEN * * Scale x by (1/abs(x(j)))*abs(A(j,j))*BIGNUM. * REC = ( TJJ*BIGNUM ) / XJ CALL DSCAL( N, REC, X, 1 ) SCALE = SCALE*REC XMAX = XMAX*REC END IF X( J ) = X( J ) / TJJS ELSE * * A(j,j) = 0: Set x(1:n) = 0, x(j) = 1, and * scale = 0, and compute a solution to A'*x = 0. * DO 140 I = 1, N X( I ) = ZERO 140 CONTINUE X( J ) = ONE SCALE = ZERO XMAX = ZERO END IF 150 CONTINUE ELSE * * Compute x(j) := x(j) / A(j,j) - sumj if the dot * product has already been divided by 1/A(j,j). * X( J ) = X( J ) / TJJS - SUMJ END IF XMAX = MAX( XMAX, ABS( X( J ) ) ) 160 CONTINUE END IF SCALE = SCALE / TSCAL END IF * * Scale the column norms by 1/TSCAL for return. * IF( TSCAL.NE.ONE ) THEN CALL DSCAL( N, ONE / TSCAL, CNORM, 1 ) END IF * RETURN * * End of DLATRS * END SUBROUTINE DORG2L( M, N, K, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORG2L generates an m by n real matrix Q with orthonormal columns, * which is defined as the last n columns of a product of k elementary * reflectors of order m * * Q = H(k) . . . H(2) H(1) * * as returned by DGEQLF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. M >= N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. N >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the (n-k+i)-th column must contain the vector which * defines the elementary reflector H(i), for i = 1,2,...,k, as * returned by DGEQLF in the last k columns of its array * argument A. * On exit, the m by n matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQLF. * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, II, J, L * .. * .. External Subroutines .. EXTERNAL DLARF, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 .OR. N.GT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORG2L', -INFO ) RETURN END IF * * Quick return if possible * IF( N.LE.0 ) $ RETURN * * Initialise columns 1:n-k to columns of the unit matrix * DO 20 J = 1, N - K DO 10 L = 1, M A( L, J ) = ZERO 10 CONTINUE A( M-N+J, J ) = ONE 20 CONTINUE * DO 40 I = 1, K II = N - K + I * * Apply H(i) to A(1:m-k+i,1:n-k+i) from the left * A( M-N+II, II ) = ONE CALL DLARF( 'Left', M-N+II, II-1, A( 1, II ), 1, TAU( I ), A, $ LDA, WORK ) CALL DSCAL( M-N+II-1, -TAU( I ), A( 1, II ), 1 ) A( M-N+II, II ) = ONE - TAU( I ) * * Set A(m-k+i+1:m,n-k+i) to zero * DO 30 L = M - N + II + 1, M A( L, II ) = ZERO 30 CONTINUE 40 CONTINUE RETURN * * End of DORG2L * END SUBROUTINE DORG2R( M, N, K, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORG2R generates an m by n real matrix Q with orthonormal columns, * which is defined as the first n columns of a product of k elementary * reflectors of order m * * Q = H(1) H(2) . . . H(k) * * as returned by DGEQRF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. M >= N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. N >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the i-th column must contain the vector which * defines the elementary reflector H(i), for i = 1,2,...,k, as * returned by DGEQRF in the first k columns of its array * argument A. * On exit, the m-by-n matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQRF. * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J, L * .. * .. External Subroutines .. EXTERNAL DLARF, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 .OR. N.GT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORG2R', -INFO ) RETURN END IF * * Quick return if possible * IF( N.LE.0 ) $ RETURN * * Initialise columns k+1:n to columns of the unit matrix * DO 20 J = K + 1, N DO 10 L = 1, M A( L, J ) = ZERO 10 CONTINUE A( J, J ) = ONE 20 CONTINUE * DO 40 I = K, 1, -1 * * Apply H(i) to A(i:m,i:n) from the left * IF( I.LT.N ) THEN A( I, I ) = ONE CALL DLARF( 'Left', M-I+1, N-I, A( I, I ), 1, TAU( I ), $ A( I, I+1 ), LDA, WORK ) END IF IF( I.LT.M ) $ CALL DSCAL( M-I, -TAU( I ), A( I+1, I ), 1 ) A( I, I ) = ONE - TAU( I ) * * Set A(1:i-1,i) to zero * DO 30 L = 1, I - 1 A( L, I ) = ZERO 30 CONTINUE 40 CONTINUE RETURN * * End of DORG2R * END SUBROUTINE DORGBR( VECT, M, N, K, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER VECT INTEGER INFO, K, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGBR generates one of the real orthogonal matrices Q or P**T * determined by DGEBRD when reducing a real matrix A to bidiagonal * form: A = Q * B * P**T. Q and P**T are defined as products of * elementary reflectors H(i) or G(i) respectively. * * If VECT = 'Q', A is assumed to have been an M-by-K matrix, and Q * is of order M: * if m >= k, Q = H(1) H(2) . . . H(k) and DORGBR returns the first n * columns of Q, where m >= n >= k; * if m < k, Q = H(1) H(2) . . . H(m-1) and DORGBR returns Q as an * M-by-M matrix. * * If VECT = 'P', A is assumed to have been a K-by-N matrix, and P**T * is of order N: * if k < n, P**T = G(k) . . . G(2) G(1) and DORGBR returns the first m * rows of P**T, where n >= m >= k; * if k >= n, P**T = G(n-1) . . . G(2) G(1) and DORGBR returns P**T as * an N-by-N matrix. * * Arguments * ========= * * VECT (input) CHARACTER*1 * Specifies whether the matrix Q or the matrix P**T is * required, as defined in the transformation applied by DGEBRD: * = 'Q': generate Q; * = 'P': generate P**T. * * M (input) INTEGER * The number of rows of the matrix Q or P**T to be returned. * M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q or P**T to be returned. * N >= 0. * If VECT = 'Q', M >= N >= min(M,K); * if VECT = 'P', N >= M >= min(N,K). * * K (input) INTEGER * If VECT = 'Q', the number of columns in the original M-by-K * matrix reduced by DGEBRD. * If VECT = 'P', the number of rows in the original K-by-N * matrix reduced by DGEBRD. * K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the vectors which define the elementary reflectors, * as returned by DGEBRD. * On exit, the M-by-N matrix Q or P**T. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension * (min(M,K)) if VECT = 'Q' * (min(N,K)) if VECT = 'P' * TAU(i) must contain the scalar factor of the elementary * reflector H(i) or G(i), which determines Q or P**T, as * returned by DGEBRD in its array argument TAUQ or TAUP. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,min(M,N)). * For optimum performance LWORK >= min(M,N)*NB, where NB * is the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WANTQ INTEGER I, IINFO, J, LWKOPT, MN, NB * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DORGLQ, DORGQR, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 WANTQ = LSAME( VECT, 'Q' ) MN = MIN( M, N ) LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.WANTQ .AND. .NOT.LSAME( VECT, 'P' ) ) THEN INFO = -1 ELSE IF( M.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 .OR. ( WANTQ .AND. ( N.GT.M .OR. N.LT.MIN( M, $ K ) ) ) .OR. ( .NOT.WANTQ .AND. ( M.GT.N .OR. M.LT. $ MIN( N, K ) ) ) ) THEN INFO = -3 ELSE IF( K.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -6 ELSE IF( LWORK.LT.MAX( 1, MN ) .AND. .NOT.LQUERY ) THEN INFO = -9 END IF * IF( INFO.EQ.0 ) THEN IF( WANTQ ) THEN NB = ILAENV( 1, 'DORGQR', ' ', M, N, K, -1 ) ELSE NB = ILAENV( 1, 'DORGLQ', ' ', M, N, K, -1 ) END IF LWKOPT = MAX( 1, MN )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGBR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( WANTQ ) THEN * * Form Q, determined by a call to DGEBRD to reduce an m-by-k * matrix * IF( M.GE.K ) THEN * * If m >= k, assume m >= n >= k * CALL DORGQR( M, N, K, A, LDA, TAU, WORK, LWORK, IINFO ) * ELSE * * If m < k, assume m = n * * Shift the vectors which define the elementary reflectors one * column to the right, and set the first row and column of Q * to those of the unit matrix * DO 20 J = M, 2, -1 A( 1, J ) = ZERO DO 10 I = J + 1, M A( I, J ) = A( I, J-1 ) 10 CONTINUE 20 CONTINUE A( 1, 1 ) = ONE DO 30 I = 2, M A( I, 1 ) = ZERO 30 CONTINUE IF( M.GT.1 ) THEN * * Form Q(2:m,2:m) * CALL DORGQR( M-1, M-1, M-1, A( 2, 2 ), LDA, TAU, WORK, $ LWORK, IINFO ) END IF END IF ELSE * * Form P', determined by a call to DGEBRD to reduce a k-by-n * matrix * IF( K.LT.N ) THEN * * If k < n, assume k <= m <= n * CALL DORGLQ( M, N, K, A, LDA, TAU, WORK, LWORK, IINFO ) * ELSE * * If k >= n, assume m = n * * Shift the vectors which define the elementary reflectors one * row downward, and set the first row and column of P' to * those of the unit matrix * A( 1, 1 ) = ONE DO 40 I = 2, N A( I, 1 ) = ZERO 40 CONTINUE DO 60 J = 2, N DO 50 I = J - 1, 2, -1 A( I, J ) = A( I-1, J ) 50 CONTINUE A( 1, J ) = ZERO 60 CONTINUE IF( N.GT.1 ) THEN * * Form P'(2:n,2:n) * CALL DORGLQ( N-1, N-1, N-1, A( 2, 2 ), LDA, TAU, WORK, $ LWORK, IINFO ) END IF END IF END IF WORK( 1 ) = LWKOPT RETURN * * End of DORGBR * END SUBROUTINE DORGHR( N, ILO, IHI, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IHI, ILO, INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGHR generates a real orthogonal matrix Q which is defined as the * product of IHI-ILO elementary reflectors of order N, as returned by * DGEHRD: * * Q = H(ilo) H(ilo+1) . . . H(ihi-1). * * Arguments * ========= * * N (input) INTEGER * The order of the matrix Q. N >= 0. * * ILO (input) INTEGER * IHI (input) INTEGER * ILO and IHI must have the same values as in the previous call * of DGEHRD. Q is equal to the unit matrix except in the * submatrix Q(ilo+1:ihi,ilo+1:ihi). * 1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the vectors which define the elementary reflectors, * as returned by DGEHRD. * On exit, the N-by-N orthogonal matrix Q. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (N-1) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEHRD. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= IHI-ILO. * For optimum performance LWORK >= (IHI-ILO)*NB, where NB is * the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IINFO, J, LWKOPT, NB, NH * .. * .. External Subroutines .. EXTERNAL DORGQR, XERBLA * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NH = IHI - ILO LQUERY = ( LWORK.EQ.-1 ) IF( N.LT.0 ) THEN INFO = -1 ELSE IF( ILO.LT.1 .OR. ILO.GT.MAX( 1, N ) ) THEN INFO = -2 ELSE IF( IHI.LT.MIN( ILO, N ) .OR. IHI.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, NH ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DORGQR', ' ', NH, NH, NH, -1 ) LWKOPT = MAX( 1, NH )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGHR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * * Shift the vectors which define the elementary reflectors one * column to the right, and set the first ilo and the last n-ihi * rows and columns to those of the unit matrix * DO 40 J = IHI, ILO + 1, -1 DO 10 I = 1, J - 1 A( I, J ) = ZERO 10 CONTINUE DO 20 I = J + 1, IHI A( I, J ) = A( I, J-1 ) 20 CONTINUE DO 30 I = IHI + 1, N A( I, J ) = ZERO 30 CONTINUE 40 CONTINUE DO 60 J = 1, ILO DO 50 I = 1, N A( I, J ) = ZERO 50 CONTINUE A( J, J ) = ONE 60 CONTINUE DO 80 J = IHI + 1, N DO 70 I = 1, N A( I, J ) = ZERO 70 CONTINUE A( J, J ) = ONE 80 CONTINUE * IF( NH.GT.0 ) THEN * * Generate Q(ilo+1:ihi,ilo+1:ihi) * CALL DORGQR( NH, NH, NH, A( ILO+1, ILO+1 ), LDA, TAU( ILO ), $ WORK, LWORK, IINFO ) END IF WORK( 1 ) = LWKOPT RETURN * * End of DORGHR * END SUBROUTINE DORGL2( M, N, K, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGL2 generates an m by n real matrix Q with orthonormal rows, * which is defined as the first m rows of a product of k elementary * reflectors of order n * * Q = H(k) . . . H(2) H(1) * * as returned by DGELQF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. N >= M. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. M >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the i-th row must contain the vector which defines * the elementary reflector H(i), for i = 1,2,...,k, as returned * by DGELQF in the first k rows of its array argument A. * On exit, the m-by-n matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGELQF. * * WORK (workspace) DOUBLE PRECISION array, dimension (M) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, J, L * .. * .. External Subroutines .. EXTERNAL DLARF, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.M ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGL2', -INFO ) RETURN END IF * * Quick return if possible * IF( M.LE.0 ) $ RETURN * IF( K.LT.M ) THEN * * Initialise rows k+1:m to rows of the unit matrix * DO 20 J = 1, N DO 10 L = K + 1, M A( L, J ) = ZERO 10 CONTINUE IF( J.GT.K .AND. J.LE.M ) $ A( J, J ) = ONE 20 CONTINUE END IF * DO 40 I = K, 1, -1 * * Apply H(i) to A(i:m,i:n) from the right * IF( I.LT.N ) THEN IF( I.LT.M ) THEN A( I, I ) = ONE CALL DLARF( 'Right', M-I, N-I+1, A( I, I ), LDA, $ TAU( I ), A( I+1, I ), LDA, WORK ) END IF CALL DSCAL( N-I, -TAU( I ), A( I, I+1 ), LDA ) END IF A( I, I ) = ONE - TAU( I ) * * Set A(i,1:i-1) to zero * DO 30 L = 1, I - 1 A( I, L ) = ZERO 30 CONTINUE 40 CONTINUE RETURN * * End of DORGL2 * END SUBROUTINE DORGLQ( M, N, K, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGLQ generates an M-by-N real matrix Q with orthonormal rows, * which is defined as the first M rows of a product of K elementary * reflectors of order N * * Q = H(k) . . . H(2) H(1) * * as returned by DGELQF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. N >= M. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. M >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the i-th row must contain the vector which defines * the elementary reflector H(i), for i = 1,2,...,k, as returned * by DGELQF in the first k rows of its array argument A. * On exit, the M-by-N matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGELQF. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,M). * For optimum performance LWORK >= M*NB, where NB is * the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, J, KI, KK, L, LDWORK, $ LWKOPT, NB, NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORGL2, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NB = ILAENV( 1, 'DORGLQ', ' ', M, N, K, -1 ) LWKOPT = MAX( 1, M )*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.M ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, M ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGLQ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.LE.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 NX = 0 IWS = M IF( NB.GT.1 .AND. NB.LT.K ) THEN * * Determine when to cross over from blocked to unblocked code. * NX = MAX( 0, ILAENV( 3, 'DORGLQ', ' ', M, N, K, -1 ) ) IF( NX.LT.K ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = M IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: reduce NB and * determine the minimum value of NB. * NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORGLQ', ' ', M, N, K, -1 ) ) END IF END IF END IF * IF( NB.GE.NBMIN .AND. NB.LT.K .AND. NX.LT.K ) THEN * * Use blocked code after the last block. * The first kk rows are handled by the block method. * KI = ( ( K-NX-1 ) / NB )*NB KK = MIN( K, KI+NB ) * * Set A(kk+1:m,1:kk) to zero. * DO 20 J = 1, KK DO 10 I = KK + 1, M A( I, J ) = ZERO 10 CONTINUE 20 CONTINUE ELSE KK = 0 END IF * * Use unblocked code for the last or only block. * IF( KK.LT.M ) $ CALL DORGL2( M-KK, N-KK, K-KK, A( KK+1, KK+1 ), LDA, $ TAU( KK+1 ), WORK, IINFO ) * IF( KK.GT.0 ) THEN * * Use blocked code * DO 50 I = KI + 1, 1, -NB IB = MIN( NB, K-I+1 ) IF( I+IB.LE.M ) THEN * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Rowwise', N-I+1, IB, A( I, I ), $ LDA, TAU( I ), WORK, LDWORK ) * * Apply H' to A(i+ib:m,i:n) from the right * CALL DLARFB( 'Right', 'Transpose', 'Forward', 'Rowwise', $ M-I-IB+1, N-I+1, IB, A( I, I ), LDA, WORK, $ LDWORK, A( I+IB, I ), LDA, WORK( IB+1 ), $ LDWORK ) END IF * * Apply H' to columns i:n of current block * CALL DORGL2( IB, N-I+1, IB, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) * * Set columns 1:i-1 of current block to zero * DO 40 J = 1, I - 1 DO 30 L = I, I + IB - 1 A( L, J ) = ZERO 30 CONTINUE 40 CONTINUE 50 CONTINUE END IF * WORK( 1 ) = IWS RETURN * * End of DORGLQ * END SUBROUTINE DORGQL( M, N, K, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGQL generates an M-by-N real matrix Q with orthonormal columns, * which is defined as the last N columns of a product of K elementary * reflectors of order M * * Q = H(k) . . . H(2) H(1) * * as returned by DGEQLF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. M >= N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. N >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the (n-k+i)-th column must contain the vector which * defines the elementary reflector H(i), for i = 1,2,...,k, as * returned by DGEQLF in the last k columns of its array * argument A. * On exit, the M-by-N matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQLF. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N). * For optimum performance LWORK >= N*NB, where NB is the * optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, J, KK, L, LDWORK, LWKOPT, $ NB, NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORG2L, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NB = ILAENV( 1, 'DORGQL', ' ', M, N, K, -1 ) LWKOPT = MAX( 1, N )*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 .OR. N.GT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, N ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGQL', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.LE.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 NX = 0 IWS = N IF( NB.GT.1 .AND. NB.LT.K ) THEN * * Determine when to cross over from blocked to unblocked code. * NX = MAX( 0, ILAENV( 3, 'DORGQL', ' ', M, N, K, -1 ) ) IF( NX.LT.K ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = N IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: reduce NB and * determine the minimum value of NB. * NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORGQL', ' ', M, N, K, -1 ) ) END IF END IF END IF * IF( NB.GE.NBMIN .AND. NB.LT.K .AND. NX.LT.K ) THEN * * Use blocked code after the first block. * The last kk columns are handled by the block method. * KK = MIN( K, ( ( K-NX+NB-1 ) / NB )*NB ) * * Set A(m-kk+1:m,1:n-kk) to zero. * DO 20 J = 1, N - KK DO 10 I = M - KK + 1, M A( I, J ) = ZERO 10 CONTINUE 20 CONTINUE ELSE KK = 0 END IF * * Use unblocked code for the first or only block. * CALL DORG2L( M-KK, N-KK, K-KK, A, LDA, TAU, WORK, IINFO ) * IF( KK.GT.0 ) THEN * * Use blocked code * DO 50 I = K - KK + 1, K, NB IB = MIN( NB, K-I+1 ) IF( N-K+I.GT.1 ) THEN * * Form the triangular factor of the block reflector * H = H(i+ib-1) . . . H(i+1) H(i) * CALL DLARFT( 'Backward', 'Columnwise', M-K+I+IB-1, IB, $ A( 1, N-K+I ), LDA, TAU( I ), WORK, LDWORK ) * * Apply H to A(1:m-k+i+ib-1,1:n-k+i-1) from the left * CALL DLARFB( 'Left', 'No transpose', 'Backward', $ 'Columnwise', M-K+I+IB-1, N-K+I-1, IB, $ A( 1, N-K+I ), LDA, WORK, LDWORK, A, LDA, $ WORK( IB+1 ), LDWORK ) END IF * * Apply H to rows 1:m-k+i+ib-1 of current block * CALL DORG2L( M-K+I+IB-1, IB, IB, A( 1, N-K+I ), LDA, $ TAU( I ), WORK, IINFO ) * * Set rows m-k+i+ib:m of current block to zero * DO 40 J = N - K + I, N - K + I + IB - 1 DO 30 L = M - K + I + IB, M A( L, J ) = ZERO 30 CONTINUE 40 CONTINUE 50 CONTINUE END IF * WORK( 1 ) = IWS RETURN * * End of DORGQL * END SUBROUTINE DORGQR( M, N, K, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDA, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGQR generates an M-by-N real matrix Q with orthonormal columns, * which is defined as the first N columns of a product of K elementary * reflectors of order M * * Q = H(1) H(2) . . . H(k) * * as returned by DGEQRF. * * Arguments * ========= * * M (input) INTEGER * The number of rows of the matrix Q. M >= 0. * * N (input) INTEGER * The number of columns of the matrix Q. M >= N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines the * matrix Q. N >= K >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the i-th column must contain the vector which * defines the elementary reflector H(i), for i = 1,2,...,k, as * returned by DGEQRF in the first k columns of its array * argument A. * On exit, the M-by-N matrix Q. * * LDA (input) INTEGER * The first dimension of the array A. LDA >= max(1,M). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQRF. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N). * For optimum performance LWORK >= N*NB, where NB is the * optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument has an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY INTEGER I, IB, IINFO, IWS, J, KI, KK, L, LDWORK, $ LWKOPT, NB, NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORG2R, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. External Functions .. INTEGER ILAENV EXTERNAL ILAENV * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 NB = ILAENV( 1, 'DORGQR', ' ', M, N, K, -1 ) LWKOPT = MAX( 1, N )*NB WORK( 1 ) = LWKOPT LQUERY = ( LWORK.EQ.-1 ) IF( M.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 .OR. N.GT.M ) THEN INFO = -2 ELSE IF( K.LT.0 .OR. K.GT.N ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, N ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGQR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.LE.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 NX = 0 IWS = N IF( NB.GT.1 .AND. NB.LT.K ) THEN * * Determine when to cross over from blocked to unblocked code. * NX = MAX( 0, ILAENV( 3, 'DORGQR', ' ', M, N, K, -1 ) ) IF( NX.LT.K ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = N IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: reduce NB and * determine the minimum value of NB. * NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORGQR', ' ', M, N, K, -1 ) ) END IF END IF END IF * IF( NB.GE.NBMIN .AND. NB.LT.K .AND. NX.LT.K ) THEN * * Use blocked code after the last block. * The first kk columns are handled by the block method. * KI = ( ( K-NX-1 ) / NB )*NB KK = MIN( K, KI+NB ) * * Set A(1:kk,kk+1:n) to zero. * DO 20 J = KK + 1, N DO 10 I = 1, KK A( I, J ) = ZERO 10 CONTINUE 20 CONTINUE ELSE KK = 0 END IF * * Use unblocked code for the last or only block. * IF( KK.LT.N ) $ CALL DORG2R( M-KK, N-KK, K-KK, A( KK+1, KK+1 ), LDA, $ TAU( KK+1 ), WORK, IINFO ) * IF( KK.GT.0 ) THEN * * Use blocked code * DO 50 I = KI + 1, 1, -NB IB = MIN( NB, K-I+1 ) IF( I+IB.LE.N ) THEN * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Columnwise', M-I+1, IB, $ A( I, I ), LDA, TAU( I ), WORK, LDWORK ) * * Apply H to A(i:m,i+ib:n) from the left * CALL DLARFB( 'Left', 'No transpose', 'Forward', $ 'Columnwise', M-I+1, N-I-IB+1, IB, $ A( I, I ), LDA, WORK, LDWORK, A( I, I+IB ), $ LDA, WORK( IB+1 ), LDWORK ) END IF * * Apply H to rows i:m of current block * CALL DORG2R( M-I+1, IB, IB, A( I, I ), LDA, TAU( I ), WORK, $ IINFO ) * * Set rows 1:i-1 of current block to zero * DO 40 J = I, I + IB - 1 DO 30 L = 1, I - 1 A( L, J ) = ZERO 30 CONTINUE 40 CONTINUE 50 CONTINUE END IF * WORK( 1 ) = IWS RETURN * * End of DORGQR * END SUBROUTINE DORGTR( UPLO, N, A, LDA, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORGTR generates a real orthogonal matrix Q which is defined as the * product of n-1 elementary reflectors of order N, as returned by * DSYTRD: * * if UPLO = 'U', Q = H(n-1) . . . H(2) H(1), * * if UPLO = 'L', Q = H(1) H(2) . . . H(n-1). * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A contains elementary reflectors * from DSYTRD; * = 'L': Lower triangle of A contains elementary reflectors * from DSYTRD. * * N (input) INTEGER * The order of the matrix Q. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the vectors which define the elementary reflectors, * as returned by DSYTRD. * On exit, the N-by-N orthogonal matrix Q. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (N-1) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DSYTRD. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,N-1). * For optimum performance LWORK >= (N-1)*NB, where NB is * the optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER INTEGER I, IINFO, J, LWKOPT, NB * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DORGQL, DORGQR, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) UPPER = LSAME( UPLO, 'U' ) IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( LWORK.LT.MAX( 1, N-1 ) .AND. .NOT.LQUERY ) THEN INFO = -7 END IF * IF( INFO.EQ.0 ) THEN IF( UPPER ) THEN NB = ILAENV( 1, 'DORGQL', ' ', N-1, N-1, N-1, -1 ) ELSE NB = ILAENV( 1, 'DORGQR', ' ', N-1, N-1, N-1, -1 ) END IF LWKOPT = MAX( 1, N-1 )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORGTR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( UPPER ) THEN * * Q was determined by a call to DSYTRD with UPLO = 'U' * * Shift the vectors which define the elementary reflectors one * column to the left, and set the last row and column of Q to * those of the unit matrix * DO 20 J = 1, N - 1 DO 10 I = 1, J - 1 A( I, J ) = A( I, J+1 ) 10 CONTINUE A( N, J ) = ZERO 20 CONTINUE DO 30 I = 1, N - 1 A( I, N ) = ZERO 30 CONTINUE A( N, N ) = ONE * * Generate Q(1:n-1,1:n-1) * CALL DORGQL( N-1, N-1, N-1, A, LDA, TAU, WORK, LWORK, IINFO ) * ELSE * * Q was determined by a call to DSYTRD with UPLO = 'L'. * * Shift the vectors which define the elementary reflectors one * column to the right, and set the first row and column of Q to * those of the unit matrix * DO 50 J = N, 2, -1 A( 1, J ) = ZERO DO 40 I = J + 1, N A( I, J ) = A( I, J-1 ) 40 CONTINUE 50 CONTINUE A( 1, 1 ) = ONE DO 60 I = 2, N A( I, 1 ) = ZERO 60 CONTINUE IF( N.GT.1 ) THEN * * Generate Q(2:n,2:n) * CALL DORGQR( N-1, N-1, N-1, A( 2, 2 ), LDA, TAU, WORK, $ LWORK, IINFO ) END IF END IF WORK( 1 ) = LWKOPT RETURN * * End of DORGTR * END SUBROUTINE DORM2R( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORM2R overwrites the general real m by n matrix C with * * Q * C if SIDE = 'L' and TRANS = 'N', or * * Q'* C if SIDE = 'L' and TRANS = 'T', or * * C * Q if SIDE = 'R' and TRANS = 'N', or * * C * Q' if SIDE = 'R' and TRANS = 'T', * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(1) H(2) . . . H(k) * * as returned by DGEQRF. Q is of order m if SIDE = 'L' and of order n * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q' from the Left * = 'R': apply Q or Q' from the Right * * TRANS (input) CHARACTER*1 * = 'N': apply Q (No transpose) * = 'T': apply Q' (Transpose) * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,K) * The i-th column must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGEQRF in the first k columns of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. * If SIDE = 'L', LDA >= max(1,M); * if SIDE = 'R', LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQRF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension * (N) if SIDE = 'L', * (M) if SIDE = 'R' * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LEFT, NOTRAN INTEGER I, I1, I2, I3, IC, JC, MI, NI, NQ DOUBLE PRECISION AII * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLARF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) * * NQ is the order of Q * IF( LEFT ) THEN NQ = M ELSE NQ = N END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, NQ ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORM2R', -INFO ) RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) $ RETURN * IF( ( LEFT .AND. .NOT.NOTRAN ) .OR. ( .NOT.LEFT .AND. NOTRAN ) ) $ THEN I1 = 1 I2 = K I3 = 1 ELSE I1 = K I2 = 1 I3 = -1 END IF * IF( LEFT ) THEN NI = N JC = 1 ELSE MI = M IC = 1 END IF * DO 10 I = I1, I2, I3 IF( LEFT ) THEN * * H(i) is applied to C(i:m,1:n) * MI = M - I + 1 IC = I ELSE * * H(i) is applied to C(1:m,i:n) * NI = N - I + 1 JC = I END IF * * Apply H(i) * AII = A( I, I ) A( I, I ) = ONE CALL DLARF( SIDE, MI, NI, A( I, I ), 1, TAU( I ), C( IC, JC ), $ LDC, WORK ) A( I, I ) = AII 10 CONTINUE RETURN * * End of DORM2R * END SUBROUTINE DORMBR( VECT, SIDE, TRANS, M, N, K, A, LDA, TAU, C, $ LDC, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS, VECT INTEGER INFO, K, LDA, LDC, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * If VECT = 'Q', DORMBR overwrites the general real M-by-N matrix C * with * SIDE = 'L' SIDE = 'R' * TRANS = 'N': Q * C C * Q * TRANS = 'T': Q**T * C C * Q**T * * If VECT = 'P', DORMBR overwrites the general real M-by-N matrix C * with * SIDE = 'L' SIDE = 'R' * TRANS = 'N': P * C C * P * TRANS = 'T': P**T * C C * P**T * * Here Q and P**T are the orthogonal matrices determined by DGEBRD when * reducing a real matrix A to bidiagonal form: A = Q * B * P**T. Q and * P**T are defined as products of elementary reflectors H(i) and G(i) * respectively. * * Let nq = m if SIDE = 'L' and nq = n if SIDE = 'R'. Thus nq is the * order of the orthogonal matrix Q or P**T that is applied. * * If VECT = 'Q', A is assumed to have been an NQ-by-K matrix: * if nq >= k, Q = H(1) H(2) . . . H(k); * if nq < k, Q = H(1) H(2) . . . H(nq-1). * * If VECT = 'P', A is assumed to have been a K-by-NQ matrix: * if k < nq, P = G(1) G(2) . . . G(k); * if k >= nq, P = G(1) G(2) . . . G(nq-1). * * Arguments * ========= * * VECT (input) CHARACTER*1 * = 'Q': apply Q or Q**T; * = 'P': apply P or P**T. * * SIDE (input) CHARACTER*1 * = 'L': apply Q, Q**T, P or P**T from the Left; * = 'R': apply Q, Q**T, P or P**T from the Right. * * TRANS (input) CHARACTER*1 * = 'N': No transpose, apply Q or P; * = 'T': Transpose, apply Q**T or P**T. * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * If VECT = 'Q', the number of columns in the original * matrix reduced by DGEBRD. * If VECT = 'P', the number of rows in the original * matrix reduced by DGEBRD. * K >= 0. * * A (input) DOUBLE PRECISION array, dimension * (LDA,min(nq,K)) if VECT = 'Q' * (LDA,nq) if VECT = 'P' * The vectors which define the elementary reflectors H(i) and * G(i), whose products determine the matrices Q and P, as * returned by DGEBRD. * * LDA (input) INTEGER * The leading dimension of the array A. * If VECT = 'Q', LDA >= max(1,nq); * if VECT = 'P', LDA >= max(1,min(nq,K)). * * TAU (input) DOUBLE PRECISION array, dimension (min(nq,K)) * TAU(i) must contain the scalar factor of the elementary * reflector H(i) or G(i) which determines Q or P, as returned * by DGEBRD in the array argument TAUQ or TAUP. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N matrix C. * On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q * or P*C or P**T*C or C*P or C*P**T. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If SIDE = 'L', LWORK >= max(1,N); * if SIDE = 'R', LWORK >= max(1,M). * For optimum performance LWORK >= N*NB if SIDE = 'L', and * LWORK >= M*NB if SIDE = 'R', where NB is the optimal * blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Local Scalars .. LOGICAL APPLYQ, LEFT, LQUERY, NOTRAN CHARACTER TRANST INTEGER I1, I2, IINFO, LWKOPT, MI, NB, NI, NQ, NW * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DORMLQ, DORMQR, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 APPLYQ = LSAME( VECT, 'Q' ) LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) LQUERY = ( LWORK.EQ.-1 ) * * NQ is the order of Q or P and NW is the minimum dimension of WORK * IF( LEFT ) THEN NQ = M NW = N ELSE NQ = N NW = M END IF IF( .NOT.APPLYQ .AND. .NOT.LSAME( VECT, 'P' ) ) THEN INFO = -1 ELSE IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -2 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -3 ELSE IF( M.LT.0 ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( K.LT.0 ) THEN INFO = -6 ELSE IF( ( APPLYQ .AND. LDA.LT.MAX( 1, NQ ) ) .OR. $ ( .NOT.APPLYQ .AND. LDA.LT.MAX( 1, MIN( NQ, K ) ) ) ) $ THEN INFO = -8 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -11 ELSE IF( LWORK.LT.MAX( 1, NW ) .AND. .NOT.LQUERY ) THEN INFO = -13 END IF * IF( INFO.EQ.0 ) THEN IF( APPLYQ ) THEN IF( LEFT ) THEN NB = ILAENV( 1, 'DORMQR', SIDE // TRANS, M-1, N, M-1, $ -1 ) ELSE NB = ILAENV( 1, 'DORMQR', SIDE // TRANS, M, N-1, N-1, $ -1 ) END IF ELSE IF( LEFT ) THEN NB = ILAENV( 1, 'DORMLQ', SIDE // TRANS, M-1, N, M-1, $ -1 ) ELSE NB = ILAENV( 1, 'DORMLQ', SIDE // TRANS, M, N-1, N-1, $ -1 ) END IF END IF LWKOPT = MAX( 1, NW )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORMBR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * WORK( 1 ) = 1 IF( M.EQ.0 .OR. N.EQ.0 ) $ RETURN * IF( APPLYQ ) THEN * * Apply Q * IF( NQ.GE.K ) THEN * * Q was determined by a call to DGEBRD with nq >= k * CALL DORMQR( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, LWORK, IINFO ) ELSE IF( NQ.GT.1 ) THEN * * Q was determined by a call to DGEBRD with nq < k * IF( LEFT ) THEN MI = M - 1 NI = N I1 = 2 I2 = 1 ELSE MI = M NI = N - 1 I1 = 1 I2 = 2 END IF CALL DORMQR( SIDE, TRANS, MI, NI, NQ-1, A( 2, 1 ), LDA, TAU, $ C( I1, I2 ), LDC, WORK, LWORK, IINFO ) END IF ELSE * * Apply P * IF( NOTRAN ) THEN TRANST = 'T' ELSE TRANST = 'N' END IF IF( NQ.GT.K ) THEN * * P was determined by a call to DGEBRD with nq > k * CALL DORMLQ( SIDE, TRANST, M, N, K, A, LDA, TAU, C, LDC, $ WORK, LWORK, IINFO ) ELSE IF( NQ.GT.1 ) THEN * * P was determined by a call to DGEBRD with nq <= k * IF( LEFT ) THEN MI = M - 1 NI = N I1 = 2 I2 = 1 ELSE MI = M NI = N - 1 I1 = 1 I2 = 2 END IF CALL DORMLQ( SIDE, TRANST, MI, NI, NQ-1, A( 1, 2 ), LDA, $ TAU, C( I1, I2 ), LDC, WORK, LWORK, IINFO ) END IF END IF WORK( 1 ) = LWKOPT RETURN * * End of DORMBR * END SUBROUTINE DORML2( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORML2 overwrites the general real m by n matrix C with * * Q * C if SIDE = 'L' and TRANS = 'N', or * * Q'* C if SIDE = 'L' and TRANS = 'T', or * * C * Q if SIDE = 'R' and TRANS = 'N', or * * C * Q' if SIDE = 'R' and TRANS = 'T', * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(k) . . . H(2) H(1) * * as returned by DGELQF. Q is of order m if SIDE = 'L' and of order n * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q' from the Left * = 'R': apply Q or Q' from the Right * * TRANS (input) CHARACTER*1 * = 'N': apply Q (No transpose) * = 'T': apply Q' (Transpose) * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension * (LDA,M) if SIDE = 'L', * (LDA,N) if SIDE = 'R' * The i-th row must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGELQF in the first k rows of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,K). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGELQF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension * (N) if SIDE = 'L', * (M) if SIDE = 'R' * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LEFT, NOTRAN INTEGER I, I1, I2, I3, IC, JC, MI, NI, NQ DOUBLE PRECISION AII * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLARF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) * * NQ is the order of Q * IF( LEFT ) THEN NQ = M ELSE NQ = N END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, K ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORML2', -INFO ) RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) $ RETURN * IF( ( LEFT .AND. NOTRAN ) .OR. ( .NOT.LEFT .AND. .NOT.NOTRAN ) ) $ THEN I1 = 1 I2 = K I3 = 1 ELSE I1 = K I2 = 1 I3 = -1 END IF * IF( LEFT ) THEN NI = N JC = 1 ELSE MI = M IC = 1 END IF * DO 10 I = I1, I2, I3 IF( LEFT ) THEN * * H(i) is applied to C(i:m,1:n) * MI = M - I + 1 IC = I ELSE * * H(i) is applied to C(1:m,i:n) * NI = N - I + 1 JC = I END IF * * Apply H(i) * AII = A( I, I ) A( I, I ) = ONE CALL DLARF( SIDE, MI, NI, A( I, I ), LDA, TAU( I ), $ C( IC, JC ), LDC, WORK ) A( I, I ) = AII 10 CONTINUE RETURN * * End of DORML2 * END SUBROUTINE DORMLQ( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORMLQ overwrites the general real M-by-N matrix C with * * SIDE = 'L' SIDE = 'R' * TRANS = 'N': Q * C C * Q * TRANS = 'T': Q**T * C C * Q**T * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(k) . . . H(2) H(1) * * as returned by DGELQF. Q is of order M if SIDE = 'L' and of order N * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q**T from the Left; * = 'R': apply Q or Q**T from the Right. * * TRANS (input) CHARACTER*1 * = 'N': No transpose, apply Q; * = 'T': Transpose, apply Q**T. * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension * (LDA,M) if SIDE = 'L', * (LDA,N) if SIDE = 'R' * The i-th row must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGELQF in the first k rows of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,K). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGELQF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N matrix C. * On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If SIDE = 'L', LWORK >= max(1,N); * if SIDE = 'R', LWORK >= max(1,M). * For optimum performance LWORK >= N*NB if SIDE = 'L', and * LWORK >= M*NB if SIDE = 'R', where NB is the optimal * blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. INTEGER NBMAX, LDT PARAMETER ( NBMAX = 64, LDT = NBMAX+1 ) * .. * .. Local Scalars .. LOGICAL LEFT, LQUERY, NOTRAN CHARACTER TRANST INTEGER I, I1, I2, I3, IB, IC, IINFO, IWS, JC, LDWORK, $ LWKOPT, MI, NB, NBMIN, NI, NQ, NW * .. * .. Local Arrays .. DOUBLE PRECISION T( LDT, NBMAX ) * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORML2, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) LQUERY = ( LWORK.EQ.-1 ) * * NQ is the order of Q and NW is the minimum dimension of WORK * IF( LEFT ) THEN NQ = M NW = N ELSE NQ = N NW = M END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, K ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 ELSE IF( LWORK.LT.MAX( 1, NW ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF * IF( INFO.EQ.0 ) THEN * * Determine the block size. NB may be at most NBMAX, where NBMAX * is used to define the local array T. * NB = MIN( NBMAX, ILAENV( 1, 'DORMLQ', SIDE // TRANS, M, N, K, $ -1 ) ) LWKOPT = MAX( 1, NW )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORMLQ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 LDWORK = NW IF( NB.GT.1 .AND. NB.LT.K ) THEN IWS = NW*NB IF( LWORK.LT.IWS ) THEN NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORMLQ', SIDE // TRANS, M, N, K, $ -1 ) ) END IF ELSE IWS = NW END IF * IF( NB.LT.NBMIN .OR. NB.GE.K ) THEN * * Use unblocked code * CALL DORML2( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, $ IINFO ) ELSE * * Use blocked code * IF( ( LEFT .AND. NOTRAN ) .OR. $ ( .NOT.LEFT .AND. .NOT.NOTRAN ) ) THEN I1 = 1 I2 = K I3 = NB ELSE I1 = ( ( K-1 ) / NB )*NB + 1 I2 = 1 I3 = -NB END IF * IF( LEFT ) THEN NI = N JC = 1 ELSE MI = M IC = 1 END IF * IF( NOTRAN ) THEN TRANST = 'T' ELSE TRANST = 'N' END IF * DO 10 I = I1, I2, I3 IB = MIN( NB, K-I+1 ) * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Rowwise', NQ-I+1, IB, A( I, I ), $ LDA, TAU( I ), T, LDT ) IF( LEFT ) THEN * * H or H' is applied to C(i:m,1:n) * MI = M - I + 1 IC = I ELSE * * H or H' is applied to C(1:m,i:n) * NI = N - I + 1 JC = I END IF * * Apply H or H' * CALL DLARFB( SIDE, TRANST, 'Forward', 'Rowwise', MI, NI, IB, $ A( I, I ), LDA, T, LDT, C( IC, JC ), LDC, WORK, $ LDWORK ) 10 CONTINUE END IF WORK( 1 ) = LWKOPT RETURN * * End of DORMLQ * END SUBROUTINE DORMQR( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORMQR overwrites the general real M-by-N matrix C with * * SIDE = 'L' SIDE = 'R' * TRANS = 'N': Q * C C * Q * TRANS = 'T': Q**T * C C * Q**T * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(1) H(2) . . . H(k) * * as returned by DGEQRF. Q is of order M if SIDE = 'L' and of order N * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q**T from the Left; * = 'R': apply Q or Q**T from the Right. * * TRANS (input) CHARACTER*1 * = 'N': No transpose, apply Q; * = 'T': Transpose, apply Q**T. * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,K) * The i-th column must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGEQRF in the first k columns of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. * If SIDE = 'L', LDA >= max(1,M); * if SIDE = 'R', LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQRF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N matrix C. * On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If SIDE = 'L', LWORK >= max(1,N); * if SIDE = 'R', LWORK >= max(1,M). * For optimum performance LWORK >= N*NB if SIDE = 'L', and * LWORK >= M*NB if SIDE = 'R', where NB is the optimal * blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. INTEGER NBMAX, LDT PARAMETER ( NBMAX = 64, LDT = NBMAX+1 ) * .. * .. Local Scalars .. LOGICAL LEFT, LQUERY, NOTRAN INTEGER I, I1, I2, I3, IB, IC, IINFO, IWS, JC, LDWORK, $ LWKOPT, MI, NB, NBMIN, NI, NQ, NW * .. * .. Local Arrays .. DOUBLE PRECISION T( LDT, NBMAX ) * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORM2R, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) LQUERY = ( LWORK.EQ.-1 ) * * NQ is the order of Q and NW is the minimum dimension of WORK * IF( LEFT ) THEN NQ = M NW = N ELSE NQ = N NW = M END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, NQ ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 ELSE IF( LWORK.LT.MAX( 1, NW ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF * IF( INFO.EQ.0 ) THEN * * Determine the block size. NB may be at most NBMAX, where NBMAX * is used to define the local array T. * NB = MIN( NBMAX, ILAENV( 1, 'DORMQR', SIDE // TRANS, M, N, K, $ -1 ) ) LWKOPT = MAX( 1, NW )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORMQR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 LDWORK = NW IF( NB.GT.1 .AND. NB.LT.K ) THEN IWS = NW*NB IF( LWORK.LT.IWS ) THEN NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORMQR', SIDE // TRANS, M, N, K, $ -1 ) ) END IF ELSE IWS = NW END IF * IF( NB.LT.NBMIN .OR. NB.GE.K ) THEN * * Use unblocked code * CALL DORM2R( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, $ IINFO ) ELSE * * Use blocked code * IF( ( LEFT .AND. .NOT.NOTRAN ) .OR. $ ( .NOT.LEFT .AND. NOTRAN ) ) THEN I1 = 1 I2 = K I3 = NB ELSE I1 = ( ( K-1 ) / NB )*NB + 1 I2 = 1 I3 = -NB END IF * IF( LEFT ) THEN NI = N JC = 1 ELSE MI = M IC = 1 END IF * DO 10 I = I1, I2, I3 IB = MIN( NB, K-I+1 ) * * Form the triangular factor of the block reflector * H = H(i) H(i+1) . . . H(i+ib-1) * CALL DLARFT( 'Forward', 'Columnwise', NQ-I+1, IB, A( I, I ), $ LDA, TAU( I ), T, LDT ) IF( LEFT ) THEN * * H or H' is applied to C(i:m,1:n) * MI = M - I + 1 IC = I ELSE * * H or H' is applied to C(1:m,i:n) * NI = N - I + 1 JC = I END IF * * Apply H or H' * CALL DLARFB( SIDE, TRANS, 'Forward', 'Columnwise', MI, NI, $ IB, A( I, I ), LDA, T, LDT, C( IC, JC ), LDC, $ WORK, LDWORK ) 10 CONTINUE END IF WORK( 1 ) = LWKOPT RETURN * * End of DORMQR * END SUBROUTINE DRSCL( N, SA, SX, INCX ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER INCX, N DOUBLE PRECISION SA * .. * .. Array Arguments .. DOUBLE PRECISION SX( * ) * .. * * Purpose * ======= * * DRSCL multiplies an n-element real vector x by the real scalar 1/a. * This is done without overflow or underflow as long as * the final result x/a does not overflow or underflow. * * Arguments * ========= * * N (input) INTEGER * The number of components of the vector x. * * SA (input) DOUBLE PRECISION * The scalar a which is used to divide each component of x. * SA must be >= 0, or the subroutine will divide by zero. * * SX (input/output) DOUBLE PRECISION array, dimension * (1+(N-1)*abs(INCX)) * The n-element vector x. * * INCX (input) INTEGER * The increment between successive values of the vector SX. * > 0: SX(1) = X(1) and SX(1+(i-1)*INCX) = x(i), 1< i<= n * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL DONE DOUBLE PRECISION BIGNUM, CDEN, CDEN1, CNUM, CNUM1, MUL, SMLNUM * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. External Subroutines .. EXTERNAL DSCAL * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * * Quick return if possible * IF( N.LE.0 ) $ RETURN * * Get machine parameters * SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * * Initialize the denominator to SA and the numerator to 1. * CDEN = SA CNUM = ONE * 10 CONTINUE CDEN1 = CDEN*SMLNUM CNUM1 = CNUM / BIGNUM IF( ABS( CDEN1 ).GT.ABS( CNUM ) .AND. CNUM.NE.ZERO ) THEN * * Pre-multiply X by SMLNUM if CDEN is large compared to CNUM. * MUL = SMLNUM DONE = .FALSE. CDEN = CDEN1 ELSE IF( ABS( CNUM1 ).GT.ABS( CDEN ) ) THEN * * Pre-multiply X by BIGNUM if CDEN is small compared to CNUM. * MUL = BIGNUM DONE = .FALSE. CNUM = CNUM1 ELSE * * Multiply X by CNUM / CDEN and return. * MUL = CNUM / CDEN DONE = .TRUE. END IF * * Scale the vector X by MUL * CALL DSCAL( N, MUL, SX, INCX ) * IF( .NOT.DONE ) $ GO TO 10 * RETURN * * End of DRSCL * END SUBROUTINE DSTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER COMPZ INTEGER INFO, LDZ, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEQR computes all eigenvalues and, optionally, eigenvectors of a * symmetric tridiagonal matrix using the implicit QL or QR method. * The eigenvectors of a full or band symmetric matrix can also be found * if DSYTRD or DSPTRD or DSBTRD has been used to reduce this matrix to * tridiagonal form. * * Arguments * ========= * * COMPZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only. * = 'V': Compute eigenvalues and eigenvectors of the original * symmetric matrix. On entry, Z must contain the * orthogonal matrix used to reduce the original matrix * to tridiagonal form. * = 'I': Compute eigenvalues and eigenvectors of the * tridiagonal matrix. Z is initialized to the identity * matrix. * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the diagonal elements of the tridiagonal matrix. * On exit, if INFO = 0, the eigenvalues in ascending order. * * E (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix. * On exit, E has been destroyed. * * Z (input/output) DOUBLE PRECISION array, dimension (LDZ, N) * On entry, if COMPZ = 'V', then Z contains the orthogonal * matrix used in the reduction to tridiagonal form. * On exit, if INFO = 0, then if COMPZ = 'V', Z contains the * orthonormal eigenvectors of the original symmetric matrix, * and if COMPZ = 'I', Z contains the orthonormal eigenvectors * of the symmetric tridiagonal matrix. * If COMPZ = 'N', then Z is not referenced. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * eigenvectors are desired, then LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (max(1,2*N-2)) * If COMPZ = 'N', then WORK is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: the algorithm has failed to find all the eigenvalues in * a total of 30*N iterations; if INFO = i, then i * elements of E have not converged to zero; on exit, D * and E contain the elements of a symmetric tridiagonal * matrix which is orthogonally similar to the original * matrix. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, THREE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ THREE = 3.0D0 ) INTEGER MAXIT PARAMETER ( MAXIT = 30 ) * .. * .. Local Scalars .. INTEGER I, ICOMPZ, II, ISCALE, J, JTOT, K, L, L1, LEND, $ LENDM1, LENDP1, LENDSV, LM1, LSV, M, MM, MM1, $ NM1, NMAXIT DOUBLE PRECISION ANORM, B, C, EPS, EPS2, F, G, P, R, RT1, RT2, $ S, SAFMAX, SAFMIN, SSFMAX, SSFMIN, TST * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST, DLAPY2 EXTERNAL LSAME, DLAMCH, DLANST, DLAPY2 * .. * .. External Subroutines .. EXTERNAL DLAE2, DLAEV2, DLARTG, DLASCL, DLASET, DLASR, $ DLASRT, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( LSAME( COMPZ, 'N' ) ) THEN ICOMPZ = 0 ELSE IF( LSAME( COMPZ, 'V' ) ) THEN ICOMPZ = 1 ELSE IF( LSAME( COMPZ, 'I' ) ) THEN ICOMPZ = 2 ELSE ICOMPZ = -1 END IF IF( ICOMPZ.LT.0 ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( ( LDZ.LT.1 ) .OR. ( ICOMPZ.GT.0 .AND. LDZ.LT.MAX( 1, $ N ) ) ) THEN INFO = -6 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEQR', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ICOMPZ.EQ.2 ) $ Z( 1, 1 ) = ONE RETURN END IF * * Determine the unit roundoff and over/underflow thresholds. * EPS = DLAMCH( 'E' ) EPS2 = EPS**2 SAFMIN = DLAMCH( 'S' ) SAFMAX = ONE / SAFMIN SSFMAX = SQRT( SAFMAX ) / THREE SSFMIN = SQRT( SAFMIN ) / EPS2 * * Compute the eigenvalues and eigenvectors of the tridiagonal * matrix. * IF( ICOMPZ.EQ.2 ) $ CALL DLASET( 'Full', N, N, ZERO, ONE, Z, LDZ ) * NMAXIT = N*MAXIT JTOT = 0 * * Determine where the matrix splits and choose QL or QR iteration * for each block, according to whether top or bottom diagonal * element is smaller. * L1 = 1 NM1 = N - 1 * 10 CONTINUE IF( L1.GT.N ) $ GO TO 160 IF( L1.GT.1 ) $ E( L1-1 ) = ZERO IF( L1.LE.NM1 ) THEN DO 20 M = L1, NM1 TST = ABS( E( M ) ) IF( TST.EQ.ZERO ) $ GO TO 30 IF( TST.LE.( SQRT( ABS( D( M ) ) )*SQRT( ABS( D( M+ $ 1 ) ) ) )*EPS ) THEN E( M ) = ZERO GO TO 30 END IF 20 CONTINUE END IF M = N * 30 CONTINUE L = L1 LSV = L LEND = M LENDSV = LEND L1 = M + 1 IF( LEND.EQ.L ) $ GO TO 10 * * Scale submatrix in rows and columns L to LEND * ANORM = DLANST( 'I', LEND-L+1, D( L ), E( L ) ) ISCALE = 0 IF( ANORM.EQ.ZERO ) $ GO TO 10 IF( ANORM.GT.SSFMAX ) THEN ISCALE = 1 CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L+1, 1, D( L ), N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L, 1, E( L ), N, $ INFO ) ELSE IF( ANORM.LT.SSFMIN ) THEN ISCALE = 2 CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L+1, 1, D( L ), N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L, 1, E( L ), N, $ INFO ) END IF * * Choose between QL and QR iteration * IF( ABS( D( LEND ) ).LT.ABS( D( L ) ) ) THEN LEND = LSV L = LENDSV END IF * IF( LEND.GT.L ) THEN * * QL Iteration * * Look for small subdiagonal element. * 40 CONTINUE IF( L.NE.LEND ) THEN LENDM1 = LEND - 1 DO 50 M = L, LENDM1 TST = ABS( E( M ) )**2 IF( TST.LE.( EPS2*ABS( D( M ) ) )*ABS( D( M+1 ) )+ $ SAFMIN )GO TO 60 50 CONTINUE END IF * M = LEND * 60 CONTINUE IF( M.LT.LEND ) $ E( M ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 80 * * If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 * to compute its eigensystem. * IF( M.EQ.L+1 ) THEN IF( ICOMPZ.GT.0 ) THEN CALL DLAEV2( D( L ), E( L ), D( L+1 ), RT1, RT2, C, S ) WORK( L ) = C WORK( N-1+L ) = S CALL DLASR( 'R', 'V', 'B', N, 2, WORK( L ), $ WORK( N-1+L ), Z( 1, L ), LDZ ) ELSE CALL DLAE2( D( L ), E( L ), D( L+1 ), RT1, RT2 ) END IF D( L ) = RT1 D( L+1 ) = RT2 E( L ) = ZERO L = L + 2 IF( L.LE.LEND ) $ GO TO 40 GO TO 140 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 140 JTOT = JTOT + 1 * * Form shift. * G = ( D( L+1 )-P ) / ( TWO*E( L ) ) R = DLAPY2( G, ONE ) G = D( M ) - P + ( E( L ) / ( G+SIGN( R, G ) ) ) * S = ONE C = ONE P = ZERO * * Inner loop * MM1 = M - 1 DO 70 I = MM1, L, -1 F = S*E( I ) B = C*E( I ) CALL DLARTG( G, F, C, S, R ) IF( I.NE.M-1 ) $ E( I+1 ) = R G = D( I+1 ) - P R = ( D( I )-G )*S + TWO*C*B P = S*R D( I+1 ) = G + P G = C*R - B * * If eigenvectors are desired, then save rotations. * IF( ICOMPZ.GT.0 ) THEN WORK( I ) = C WORK( N-1+I ) = -S END IF * 70 CONTINUE * * If eigenvectors are desired, then apply saved rotations. * IF( ICOMPZ.GT.0 ) THEN MM = M - L + 1 CALL DLASR( 'R', 'V', 'B', N, MM, WORK( L ), WORK( N-1+L ), $ Z( 1, L ), LDZ ) END IF * D( L ) = D( L ) - P E( L ) = G GO TO 40 * * Eigenvalue found. * 80 CONTINUE D( L ) = P * L = L + 1 IF( L.LE.LEND ) $ GO TO 40 GO TO 140 * ELSE * * QR Iteration * * Look for small superdiagonal element. * 90 CONTINUE IF( L.NE.LEND ) THEN LENDP1 = LEND + 1 DO 100 M = L, LENDP1, -1 TST = ABS( E( M-1 ) )**2 IF( TST.LE.( EPS2*ABS( D( M ) ) )*ABS( D( M-1 ) )+ $ SAFMIN )GO TO 110 100 CONTINUE END IF * M = LEND * 110 CONTINUE IF( M.GT.LEND ) $ E( M-1 ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 130 * * If remaining matrix is 2-by-2, use DLAE2 or SLAEV2 * to compute its eigensystem. * IF( M.EQ.L-1 ) THEN IF( ICOMPZ.GT.0 ) THEN CALL DLAEV2( D( L-1 ), E( L-1 ), D( L ), RT1, RT2, C, S ) WORK( M ) = C WORK( N-1+M ) = S CALL DLASR( 'R', 'V', 'F', N, 2, WORK( M ), $ WORK( N-1+M ), Z( 1, L-1 ), LDZ ) ELSE CALL DLAE2( D( L-1 ), E( L-1 ), D( L ), RT1, RT2 ) END IF D( L-1 ) = RT1 D( L ) = RT2 E( L-1 ) = ZERO L = L - 2 IF( L.GE.LEND ) $ GO TO 90 GO TO 140 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 140 JTOT = JTOT + 1 * * Form shift. * G = ( D( L-1 )-P ) / ( TWO*E( L-1 ) ) R = DLAPY2( G, ONE ) G = D( M ) - P + ( E( L-1 ) / ( G+SIGN( R, G ) ) ) * S = ONE C = ONE P = ZERO * * Inner loop * LM1 = L - 1 DO 120 I = M, LM1 F = S*E( I ) B = C*E( I ) CALL DLARTG( G, F, C, S, R ) IF( I.NE.M ) $ E( I-1 ) = R G = D( I ) - P R = ( D( I+1 )-G )*S + TWO*C*B P = S*R D( I ) = G + P G = C*R - B * * If eigenvectors are desired, then save rotations. * IF( ICOMPZ.GT.0 ) THEN WORK( I ) = C WORK( N-1+I ) = S END IF * 120 CONTINUE * * If eigenvectors are desired, then apply saved rotations. * IF( ICOMPZ.GT.0 ) THEN MM = L - M + 1 CALL DLASR( 'R', 'V', 'F', N, MM, WORK( M ), WORK( N-1+M ), $ Z( 1, M ), LDZ ) END IF * D( L ) = D( L ) - P E( LM1 ) = G GO TO 90 * * Eigenvalue found. * 130 CONTINUE D( L ) = P * L = L - 1 IF( L.GE.LEND ) $ GO TO 90 GO TO 140 * END IF * * Undo scaling if necessary * 140 CONTINUE IF( ISCALE.EQ.1 ) THEN CALL DLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) CALL DLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV, 1, E( LSV ), $ N, INFO ) ELSE IF( ISCALE.EQ.2 ) THEN CALL DLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) CALL DLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV, 1, E( LSV ), $ N, INFO ) END IF * * Check for no convergence to an eigenvalue after a total * of N*MAXIT iterations. * IF( JTOT.LT.NMAXIT ) $ GO TO 10 DO 150 I = 1, N - 1 IF( E( I ).NE.ZERO ) $ INFO = INFO + 1 150 CONTINUE GO TO 190 * * Order eigenvalues and eigenvectors. * 160 CONTINUE IF( ICOMPZ.EQ.0 ) THEN * * Use Quick Sort * CALL DLASRT( 'I', N, D, INFO ) * ELSE * * Use Selection Sort to minimize swaps of eigenvectors * DO 180 II = 2, N I = II - 1 K = I P = D( I ) DO 170 J = II, N IF( D( J ).LT.P ) THEN K = J P = D( J ) END IF 170 CONTINUE IF( K.NE.I ) THEN D( K ) = D( I ) D( I ) = P CALL DSWAP( N, Z( 1, I ), 1, Z( 1, K ), 1 ) END IF 180 CONTINUE END IF * 190 CONTINUE RETURN * * End of DSTEQR * END SUBROUTINE DSTERF( N, D, E, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, N * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), E( * ) * .. * * Purpose * ======= * * DSTERF computes all eigenvalues of a symmetric tridiagonal matrix * using the Pal-Walker-Kahan variant of the QL or QR algorithm. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix. * On exit, if INFO = 0, the eigenvalues in ascending order. * * E (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix. * On exit, E has been destroyed. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: the algorithm failed to find all of the eigenvalues in * a total of 30*N iterations; if INFO = i, then i * elements of E have not converged to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, THREE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ THREE = 3.0D0 ) INTEGER MAXIT PARAMETER ( MAXIT = 30 ) * .. * .. Local Scalars .. INTEGER I, ISCALE, JTOT, L, L1, LEND, LENDSV, LSV, M, $ NMAXIT DOUBLE PRECISION ALPHA, ANORM, BB, C, EPS, EPS2, GAMMA, OLDC, $ OLDGAM, P, R, RT1, RT2, RTE, S, SAFMAX, SAFMIN, $ SIGMA, SSFMAX, SSFMIN * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLANST, DLAPY2 EXTERNAL DLAMCH, DLANST, DLAPY2 * .. * .. External Subroutines .. EXTERNAL DLAE2, DLASCL, DLASRT, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * * Quick return if possible * IF( N.LT.0 ) THEN INFO = -1 CALL XERBLA( 'DSTERF', -INFO ) RETURN END IF IF( N.LE.1 ) $ RETURN * * Determine the unit roundoff for this environment. * EPS = DLAMCH( 'E' ) EPS2 = EPS**2 SAFMIN = DLAMCH( 'S' ) SAFMAX = ONE / SAFMIN SSFMAX = SQRT( SAFMAX ) / THREE SSFMIN = SQRT( SAFMIN ) / EPS2 * * Compute the eigenvalues of the tridiagonal matrix. * NMAXIT = N*MAXIT SIGMA = ZERO JTOT = 0 * * Determine where the matrix splits and choose QL or QR iteration * for each block, according to whether top or bottom diagonal * element is smaller. * L1 = 1 * 10 CONTINUE IF( L1.GT.N ) $ GO TO 170 IF( L1.GT.1 ) $ E( L1-1 ) = ZERO DO 20 M = L1, N - 1 IF( ABS( E( M ) ).LE.( SQRT( ABS( D( M ) ) )*SQRT( ABS( D( M+ $ 1 ) ) ) )*EPS ) THEN E( M ) = ZERO GO TO 30 END IF 20 CONTINUE M = N * 30 CONTINUE L = L1 LSV = L LEND = M LENDSV = LEND L1 = M + 1 IF( LEND.EQ.L ) $ GO TO 10 * * Scale submatrix in rows and columns L to LEND * ANORM = DLANST( 'I', LEND-L+1, D( L ), E( L ) ) ISCALE = 0 IF( ANORM.GT.SSFMAX ) THEN ISCALE = 1 CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L+1, 1, D( L ), N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMAX, LEND-L, 1, E( L ), N, $ INFO ) ELSE IF( ANORM.LT.SSFMIN ) THEN ISCALE = 2 CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L+1, 1, D( L ), N, $ INFO ) CALL DLASCL( 'G', 0, 0, ANORM, SSFMIN, LEND-L, 1, E( L ), N, $ INFO ) END IF * DO 40 I = L, LEND - 1 E( I ) = E( I )**2 40 CONTINUE * * Choose between QL and QR iteration * IF( ABS( D( LEND ) ).LT.ABS( D( L ) ) ) THEN LEND = LSV L = LENDSV END IF * IF( LEND.GE.L ) THEN * * QL Iteration * * Look for small subdiagonal element. * 50 CONTINUE IF( L.NE.LEND ) THEN DO 60 M = L, LEND - 1 IF( ABS( E( M ) ).LE.EPS2*ABS( D( M )*D( M+1 ) ) ) $ GO TO 70 60 CONTINUE END IF M = LEND * 70 CONTINUE IF( M.LT.LEND ) $ E( M ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 90 * * If remaining matrix is 2 by 2, use DLAE2 to compute its * eigenvalues. * IF( M.EQ.L+1 ) THEN RTE = SQRT( E( L ) ) CALL DLAE2( D( L ), RTE, D( L+1 ), RT1, RT2 ) D( L ) = RT1 D( L+1 ) = RT2 E( L ) = ZERO L = L + 2 IF( L.LE.LEND ) $ GO TO 50 GO TO 150 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 150 JTOT = JTOT + 1 * * Form shift. * RTE = SQRT( E( L ) ) SIGMA = ( D( L+1 )-P ) / ( TWO*RTE ) R = DLAPY2( SIGMA, ONE ) SIGMA = P - ( RTE / ( SIGMA+SIGN( R, SIGMA ) ) ) * C = ONE S = ZERO GAMMA = D( M ) - SIGMA P = GAMMA*GAMMA * * Inner loop * DO 80 I = M - 1, L, -1 BB = E( I ) R = P + BB IF( I.NE.M-1 ) $ E( I+1 ) = S*R OLDC = C C = P / R S = BB / R OLDGAM = GAMMA ALPHA = D( I ) GAMMA = C*( ALPHA-SIGMA ) - S*OLDGAM D( I+1 ) = OLDGAM + ( ALPHA-GAMMA ) IF( C.NE.ZERO ) THEN P = ( GAMMA*GAMMA ) / C ELSE P = OLDC*BB END IF 80 CONTINUE * E( L ) = S*P D( L ) = SIGMA + GAMMA GO TO 50 * * Eigenvalue found. * 90 CONTINUE D( L ) = P * L = L + 1 IF( L.LE.LEND ) $ GO TO 50 GO TO 150 * ELSE * * QR Iteration * * Look for small superdiagonal element. * 100 CONTINUE DO 110 M = L, LEND + 1, -1 IF( ABS( E( M-1 ) ).LE.EPS2*ABS( D( M )*D( M-1 ) ) ) $ GO TO 120 110 CONTINUE M = LEND * 120 CONTINUE IF( M.GT.LEND ) $ E( M-1 ) = ZERO P = D( L ) IF( M.EQ.L ) $ GO TO 140 * * If remaining matrix is 2 by 2, use DLAE2 to compute its * eigenvalues. * IF( M.EQ.L-1 ) THEN RTE = SQRT( E( L-1 ) ) CALL DLAE2( D( L ), RTE, D( L-1 ), RT1, RT2 ) D( L ) = RT1 D( L-1 ) = RT2 E( L-1 ) = ZERO L = L - 2 IF( L.GE.LEND ) $ GO TO 100 GO TO 150 END IF * IF( JTOT.EQ.NMAXIT ) $ GO TO 150 JTOT = JTOT + 1 * * Form shift. * RTE = SQRT( E( L-1 ) ) SIGMA = ( D( L-1 )-P ) / ( TWO*RTE ) R = DLAPY2( SIGMA, ONE ) SIGMA = P - ( RTE / ( SIGMA+SIGN( R, SIGMA ) ) ) * C = ONE S = ZERO GAMMA = D( M ) - SIGMA P = GAMMA*GAMMA * * Inner loop * DO 130 I = M, L - 1 BB = E( I ) R = P + BB IF( I.NE.M ) $ E( I-1 ) = S*R OLDC = C C = P / R S = BB / R OLDGAM = GAMMA ALPHA = D( I+1 ) GAMMA = C*( ALPHA-SIGMA ) - S*OLDGAM D( I ) = OLDGAM + ( ALPHA-GAMMA ) IF( C.NE.ZERO ) THEN P = ( GAMMA*GAMMA ) / C ELSE P = OLDC*BB END IF 130 CONTINUE * E( L-1 ) = S*P D( L ) = SIGMA + GAMMA GO TO 100 * * Eigenvalue found. * 140 CONTINUE D( L ) = P * L = L - 1 IF( L.GE.LEND ) $ GO TO 100 GO TO 150 * END IF * * Undo scaling if necessary * 150 CONTINUE IF( ISCALE.EQ.1 ) $ CALL DLASCL( 'G', 0, 0, SSFMAX, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) IF( ISCALE.EQ.2 ) $ CALL DLASCL( 'G', 0, 0, SSFMIN, ANORM, LENDSV-LSV+1, 1, $ D( LSV ), N, INFO ) * * Check for no convergence to an eigenvalue after a total * of N*MAXIT iterations. * IF( JTOT.LT.NMAXIT ) $ GO TO 10 DO 160 I = 1, N - 1 IF( E( I ).NE.ZERO ) $ INFO = INFO + 1 160 CONTINUE GO TO 180 * * Sort eigenvalues in increasing order. * 170 CONTINUE CALL DLASRT( 'I', N, D, INFO ) * 180 CONTINUE RETURN * * End of DSTERF * END SUBROUTINE RSYEV( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, UPLO INTEGER INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSYEV computes all eigenvalues and, optionally, eigenvectors of a * real symmetric matrix A. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, if JOBZ = 'V', then if INFO = 0, A contains the * orthonormal eigenvectors of the matrix A. * If JOBZ = 'N', then on exit the lower triangle (if UPLO='L') * or the upper triangle (if UPLO='U') of A, including the * diagonal, is destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * W (output) DOUBLE PRECISION array, dimension (N) * If INFO = 0, the eigenvalues in ascending order. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The length of the array WORK. LWORK >= max(1,3*N-1). * For optimal efficiency, LWORK >= (NB+2)*N, * where NB is the blocksize for DSYTRD returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, the algorithm failed to converge; i * off-diagonal elements of an intermediate tridiagonal * form did not converge to zero. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LOWER, LQUERY, WANTZ INTEGER IINFO, IMAX, INDE, INDTAU, INDWRK, ISCALE, $ LLWORK, LOPT, LWKOPT, NB DOUBLE PRECISION ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, $ SMLNUM * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DLASCL, DORGTR, DSCAL, DSTEQR, DSTERF, DSYTRD, $ XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) LOWER = LSAME( UPLO, 'L' ) LQUERY = ( LWORK.EQ.-1 ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -5 ELSE IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY ) THEN INFO = -8 END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) LWKOPT = MAX( 1, ( NB+2 )*N ) WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEV ', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( N.EQ.1 ) THEN W( 1 ) = A( 1, 1 ) WORK( 1 ) = 3 IF( WANTZ ) $ A( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = SQRT( BIGNUM ) * * Scale matrix to allowable range, if necessary. * ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) ISCALE = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) $ CALL DLASCL( UPLO, 0, 0, ONE, SIGMA, N, N, A, LDA, INFO ) * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDE = 1 INDTAU = INDE + N INDWRK = INDTAU + N LLWORK = LWORK - INDWRK + 1 CALL DSYTRD( UPLO, N, A, LDA, W, WORK( INDE ), WORK( INDTAU ), $ WORK( INDWRK ), LLWORK, IINFO ) LOPT = 2*N + WORK( INDWRK ) * * For eigenvalues only, call DSTERF. For eigenvectors, first call * DORGTR to generate the orthogonal matrix, then call DSTEQR. * IF( .NOT.WANTZ ) THEN CALL DSTERF( N, W, WORK( INDE ), INFO ) ELSE CALL DORGTR( UPLO, N, A, LDA, WORK( INDTAU ), WORK( INDWRK ), $ LLWORK, IINFO ) CALL DSTEQR( JOBZ, N, W, WORK( INDE ), A, LDA, WORK( INDTAU ), $ INFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = N ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT * RETURN * * End of DSYEV * END SUBROUTINE DSYTD2( UPLO, N, A, LDA, D, E, TAU, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDA, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAU( * ) * .. * * Purpose * ======= * * DSYTD2 reduces a real symmetric matrix A to symmetric tridiagonal * form T by an orthogonal similarity transformation: Q' * A * Q = T. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * Specifies whether the upper or lower triangular part of the * symmetric matrix A is stored: * = 'U': Upper triangular * = 'L': Lower triangular * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A. If UPLO = 'U', the leading * n-by-n upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading n-by-n lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. * On exit, if UPLO = 'U', the diagonal and first superdiagonal * of A are overwritten by the corresponding elements of the * tridiagonal matrix T, and the elements above the first * superdiagonal, with the array TAU, represent the orthogonal * matrix Q as a product of elementary reflectors; if UPLO * = 'L', the diagonal and first subdiagonal of A are over- * written by the corresponding elements of the tridiagonal * matrix T, and the elements below the first subdiagonal, with * the array TAU, represent the orthogonal matrix Q as a product * of elementary reflectors. See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * D (output) DOUBLE PRECISION array, dimension (N) * The diagonal elements of the tridiagonal matrix T: * D(i) = A(i,i). * * E (output) DOUBLE PRECISION array, dimension (N-1) * The off-diagonal elements of the tridiagonal matrix T: * E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'. * * TAU (output) DOUBLE PRECISION array, dimension (N-1) * The scalar factors of the elementary reflectors (see Further * Details). * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value. * * Further Details * =============== * * If UPLO = 'U', the matrix Q is represented as a product of elementary * reflectors * * Q = H(n-1) . . . H(2) H(1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in * A(1:i-1,i+1), and tau in TAU(i). * * If UPLO = 'L', the matrix Q is represented as a product of elementary * reflectors * * Q = H(1) H(2) . . . H(n-1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i), * and tau in TAU(i). * * The contents of A on exit are illustrated by the following examples * with n = 5: * * if UPLO = 'U': if UPLO = 'L': * * ( d e v2 v3 v4 ) ( d ) * ( d e v3 v4 ) ( e d ) * ( d e v4 ) ( v1 e d ) * ( d e ) ( v1 v2 e d ) * ( d ) ( v1 v2 v3 e d ) * * where d and e denote diagonal and off-diagonal elements of T, and vi * denotes an element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO, HALF PARAMETER ( ONE = 1.0D0, ZERO = 0.0D0, $ HALF = 1.0D0 / 2.0D0 ) * .. * .. Local Scalars .. LOGICAL UPPER INTEGER I DOUBLE PRECISION ALPHA, TAUI * .. * .. External Subroutines .. EXTERNAL DAXPY, DLARFG, DSYMV, DSYR2, XERBLA * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DDOT EXTERNAL LSAME, DDOT * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 UPPER = LSAME( UPLO, 'U' ) IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYTD2', -INFO ) RETURN END IF * * Quick return if possible * IF( N.LE.0 ) $ RETURN * IF( UPPER ) THEN * * Reduce the upper triangle of A * DO 10 I = N - 1, 1, -1 * * Generate elementary reflector H(i) = I - tau * v * v' * to annihilate A(1:i-1,i+1) * CALL DLARFG( I, A( I, I+1 ), A( 1, I+1 ), 1, TAUI ) E( I ) = A( I, I+1 ) * IF( TAUI.NE.ZERO ) THEN * * Apply H(i) from both sides to A(1:i,1:i) * A( I, I+1 ) = ONE * * Compute x := tau * A * v storing x in TAU(1:i) * CALL DSYMV( UPLO, I, TAUI, A, LDA, A( 1, I+1 ), 1, ZERO, $ TAU, 1 ) * * Compute w := x - 1/2 * tau * (x'*v) * v * ALPHA = -HALF*TAUI*DDOT( I, TAU, 1, A( 1, I+1 ), 1 ) CALL DAXPY( I, ALPHA, A( 1, I+1 ), 1, TAU, 1 ) * * Apply the transformation as a rank-2 update: * A := A - v * w' - w * v' * CALL DSYR2( UPLO, I, -ONE, A( 1, I+1 ), 1, TAU, 1, A, $ LDA ) * A( I, I+1 ) = E( I ) END IF D( I+1 ) = A( I+1, I+1 ) TAU( I ) = TAUI 10 CONTINUE D( 1 ) = A( 1, 1 ) ELSE * * Reduce the lower triangle of A * DO 20 I = 1, N - 1 * * Generate elementary reflector H(i) = I - tau * v * v' * to annihilate A(i+2:n,i) * CALL DLARFG( N-I, A( I+1, I ), A( MIN( I+2, N ), I ), 1, $ TAUI ) E( I ) = A( I+1, I ) * IF( TAUI.NE.ZERO ) THEN * * Apply H(i) from both sides to A(i+1:n,i+1:n) * A( I+1, I ) = ONE * * Compute x := tau * A * v storing y in TAU(i:n-1) * CALL DSYMV( UPLO, N-I, TAUI, A( I+1, I+1 ), LDA, $ A( I+1, I ), 1, ZERO, TAU( I ), 1 ) * * Compute w := x - 1/2 * tau * (x'*v) * v * ALPHA = -HALF*TAUI*DDOT( N-I, TAU( I ), 1, A( I+1, I ), $ 1 ) CALL DAXPY( N-I, ALPHA, A( I+1, I ), 1, TAU( I ), 1 ) * * Apply the transformation as a rank-2 update: * A := A - v * w' - w * v' * CALL DSYR2( UPLO, N-I, -ONE, A( I+1, I ), 1, TAU( I ), 1, $ A( I+1, I+1 ), LDA ) * A( I+1, I ) = E( I ) END IF D( I ) = A( I, I ) TAU( I ) = TAUI 20 CONTINUE D( N ) = A( N, N ) END IF * RETURN * * End of DSYTD2 * END SUBROUTINE DSYTRD( UPLO, N, A, LDA, D, E, TAU, WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), D( * ), E( * ), TAU( * ), $ WORK( * ) * .. * * Purpose * ======= * * DSYTRD reduces a real symmetric matrix A to real symmetric * tridiagonal form T by an orthogonal similarity transformation: * Q**T * A * Q = T. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the symmetric matrix A. If UPLO = 'U', the leading * N-by-N upper triangular part of A contains the upper * triangular part of the matrix A, and the strictly lower * triangular part of A is not referenced. If UPLO = 'L', the * leading N-by-N lower triangular part of A contains the lower * triangular part of the matrix A, and the strictly upper * triangular part of A is not referenced. * On exit, if UPLO = 'U', the diagonal and first superdiagonal * of A are overwritten by the corresponding elements of the * tridiagonal matrix T, and the elements above the first * superdiagonal, with the array TAU, represent the orthogonal * matrix Q as a product of elementary reflectors; if UPLO * = 'L', the diagonal and first subdiagonal of A are over- * written by the corresponding elements of the tridiagonal * matrix T, and the elements below the first subdiagonal, with * the array TAU, represent the orthogonal matrix Q as a product * of elementary reflectors. See Further Details. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * D (output) DOUBLE PRECISION array, dimension (N) * The diagonal elements of the tridiagonal matrix T: * D(i) = A(i,i). * * E (output) DOUBLE PRECISION array, dimension (N-1) * The off-diagonal elements of the tridiagonal matrix T: * E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'. * * TAU (output) DOUBLE PRECISION array, dimension (N-1) * The scalar factors of the elementary reflectors (see Further * Details). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1. * For optimum performance LWORK >= N*NB, where NB is the * optimal blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * If UPLO = 'U', the matrix Q is represented as a product of elementary * reflectors * * Q = H(n-1) . . . H(2) H(1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in * A(1:i-1,i+1), and tau in TAU(i). * * If UPLO = 'L', the matrix Q is represented as a product of elementary * reflectors * * Q = H(1) H(2) . . . H(n-1). * * Each H(i) has the form * * H(i) = I - tau * v * v' * * where tau is a real scalar, and v is a real vector with * v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i), * and tau in TAU(i). * * The contents of A on exit are illustrated by the following examples * with n = 5: * * if UPLO = 'U': if UPLO = 'L': * * ( d e v2 v3 v4 ) ( d ) * ( d e v3 v4 ) ( e d ) * ( d e v4 ) ( v1 e d ) * ( d e ) ( v1 v2 e d ) * ( d ) ( v1 v2 v3 e d ) * * where d and e denote diagonal and off-diagonal elements of T, and vi * denotes an element of the vector defining H(i). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, UPPER INTEGER I, IINFO, IWS, J, KK, LDWORK, LWKOPT, NB, $ NBMIN, NX * .. * .. External Subroutines .. EXTERNAL DLATRD, DSYR2K, DSYTD2, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. Executable Statements .. * * Test the input parameters * INFO = 0 UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( LWORK.LT.1 .AND. .NOT.LQUERY ) THEN INFO = -9 END IF * IF( INFO.EQ.0 ) THEN * * Determine the block size. * NB = ILAENV( 1, 'DSYTRD', UPLO, N, -1, -1, -1 ) LWKOPT = N*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYTRD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NX = N IWS = 1 IF( NB.GT.1 .AND. NB.LT.N ) THEN * * Determine when to cross over from blocked to unblocked code * (last block is always handled by unblocked code). * NX = MAX( NB, ILAENV( 3, 'DSYTRD', UPLO, N, -1, -1, -1 ) ) IF( NX.LT.N ) THEN * * Determine if workspace is large enough for blocked code. * LDWORK = N IWS = LDWORK*NB IF( LWORK.LT.IWS ) THEN * * Not enough workspace to use optimal NB: determine the * minimum value of NB, and reduce NB or force use of * unblocked code by setting NX = N. * NB = MAX( LWORK / LDWORK, 1 ) NBMIN = ILAENV( 2, 'DSYTRD', UPLO, N, -1, -1, -1 ) IF( NB.LT.NBMIN ) $ NX = N END IF ELSE NX = N END IF ELSE NB = 1 END IF * IF( UPPER ) THEN * * Reduce the upper triangle of A. * Columns 1:kk are handled by the unblocked method. * KK = N - ( ( N-NX+NB-1 ) / NB )*NB DO 20 I = N - NB + 1, KK + 1, -NB * * Reduce columns i:i+nb-1 to tridiagonal form and form the * matrix W which is needed to update the unreduced part of * the matrix * CALL DLATRD( UPLO, I+NB-1, NB, A, LDA, E, TAU, WORK, $ LDWORK ) * * Update the unreduced submatrix A(1:i-1,1:i-1), using an * update of the form: A := A - V*W' - W*V' * CALL DSYR2K( UPLO, 'No transpose', I-1, NB, -ONE, A( 1, I ), $ LDA, WORK, LDWORK, ONE, A, LDA ) * * Copy superdiagonal elements back into A, and diagonal * elements into D * DO 10 J = I, I + NB - 1 A( J-1, J ) = E( J-1 ) D( J ) = A( J, J ) 10 CONTINUE 20 CONTINUE * * Use unblocked code to reduce the last or only block * CALL DSYTD2( UPLO, KK, A, LDA, D, E, TAU, IINFO ) ELSE * * Reduce the lower triangle of A * DO 40 I = 1, N - NX, NB * * Reduce columns i:i+nb-1 to tridiagonal form and form the * matrix W which is needed to update the unreduced part of * the matrix * CALL DLATRD( UPLO, N-I+1, NB, A( I, I ), LDA, E( I ), $ TAU( I ), WORK, LDWORK ) * * Update the unreduced submatrix A(i+ib:n,i+ib:n), using * an update of the form: A := A - V*W' - W*V' * CALL DSYR2K( UPLO, 'No transpose', N-I-NB+1, NB, -ONE, $ A( I+NB, I ), LDA, WORK( NB+1 ), LDWORK, ONE, $ A( I+NB, I+NB ), LDA ) * * Copy subdiagonal elements back into A, and diagonal * elements into D * DO 30 J = I, I + NB - 1 A( J+1, J ) = E( J ) D( J ) = A( J, J ) 30 CONTINUE 40 CONTINUE * * Use unblocked code to reduce the last or only block * CALL DSYTD2( UPLO, N-I+1, A( I, I ), LDA, D( I ), E( I ), $ TAU( I ), IINFO ) END IF * WORK( 1 ) = LWKOPT RETURN * * End of DSYTRD * END SUBROUTINE DTREVC( SIDE, HOWMNY, SELECT, N, T, LDT, VL, LDVL, VR, $ LDVR, MM, M, WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER HOWMNY, SIDE INTEGER INFO, LDT, LDVL, LDVR, M, MM, N * .. * .. Array Arguments .. LOGICAL SELECT( * ) DOUBLE PRECISION T( LDT, * ), VL( LDVL, * ), VR( LDVR, * ), $ WORK( * ) * .. * * Purpose * ======= * * DTREVC computes some or all of the right and/or left eigenvectors of * a real upper quasi-triangular matrix T. * * The right eigenvector x and the left eigenvector y of T corresponding * to an eigenvalue w are defined by: * * T*x = w*x, y'*T = w*y' * * where y' denotes the conjugate transpose of the vector y. * * If all eigenvectors are requested, the routine may either return the * matrices X and/or Y of right or left eigenvectors of T, or the * products Q*X and/or Q*Y, where Q is an input orthogonal * matrix. If T was obtained from the real-Schur factorization of an * original matrix A = Q*T*Q', then Q*X and Q*Y are the matrices of * right or left eigenvectors of A. * * T must be in Schur canonical form (as returned by DHSEQR), that is, * block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each * 2-by-2 diagonal block has its diagonal elements equal and its * off-diagonal elements of opposite sign. Corresponding to each 2-by-2 * diagonal block is a complex conjugate pair of eigenvalues and * eigenvectors; only one eigenvector of the pair is computed, namely * the one corresponding to the eigenvalue with positive imaginary part. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'R': compute right eigenvectors only; * = 'L': compute left eigenvectors only; * = 'B': compute both right and left eigenvectors. * * HOWMNY (input) CHARACTER*1 * = 'A': compute all right and/or left eigenvectors; * = 'B': compute all right and/or left eigenvectors, * and backtransform them using the input matrices * supplied in VR and/or VL; * = 'S': compute selected right and/or left eigenvectors, * specified by the logical array SELECT. * * SELECT (input/output) LOGICAL array, dimension (N) * If HOWMNY = 'S', SELECT specifies the eigenvectors to be * computed. * If HOWMNY = 'A' or 'B', SELECT is not referenced. * To select the real eigenvector corresponding to a real * eigenvalue w(j), SELECT(j) must be set to .TRUE.. To select * the complex eigenvector corresponding to a complex conjugate * pair w(j) and w(j+1), either SELECT(j) or SELECT(j+1) must be * set to .TRUE.; then on exit SELECT(j) is .TRUE. and * SELECT(j+1) is .FALSE.. * * N (input) INTEGER * The order of the matrix T. N >= 0. * * T (input) DOUBLE PRECISION array, dimension (LDT,N) * The upper quasi-triangular matrix T in Schur canonical form. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= max(1,N). * * VL (input/output) DOUBLE PRECISION array, dimension (LDVL,MM) * On entry, if SIDE = 'L' or 'B' and HOWMNY = 'B', VL must * contain an N-by-N matrix Q (usually the orthogonal matrix Q * of Schur vectors returned by DHSEQR). * On exit, if SIDE = 'L' or 'B', VL contains: * if HOWMNY = 'A', the matrix Y of left eigenvectors of T; * VL has the same quasi-lower triangular form * as T'. If T(i,i) is a real eigenvalue, then * the i-th column VL(i) of VL is its * corresponding eigenvector. If T(i:i+1,i:i+1) * is a 2-by-2 block whose eigenvalues are * complex-conjugate eigenvalues of T, then * VL(i)+sqrt(-1)*VL(i+1) is the complex * eigenvector corresponding to the eigenvalue * with positive real part. * if HOWMNY = 'B', the matrix Q*Y; * if HOWMNY = 'S', the left eigenvectors of T specified by * SELECT, stored consecutively in the columns * of VL, in the same order as their * eigenvalues. * A complex eigenvector corresponding to a complex eigenvalue * is stored in two consecutive columns, the first holding the * real part, and the second the imaginary part. * If SIDE = 'R', VL is not referenced. * * LDVL (input) INTEGER * The leading dimension of the array VL. LDVL >= max(1,N) if * SIDE = 'L' or 'B'; LDVL >= 1 otherwise. * * VR (input/output) DOUBLE PRECISION array, dimension (LDVR,MM) * On entry, if SIDE = 'R' or 'B' and HOWMNY = 'B', VR must * contain an N-by-N matrix Q (usually the orthogonal matrix Q * of Schur vectors returned by DHSEQR). * On exit, if SIDE = 'R' or 'B', VR contains: * if HOWMNY = 'A', the matrix X of right eigenvectors of T; * VR has the same quasi-upper triangular form * as T. If T(i,i) is a real eigenvalue, then * the i-th column VR(i) of VR is its * corresponding eigenvector. If T(i:i+1,i:i+1) * is a 2-by-2 block whose eigenvalues are * complex-conjugate eigenvalues of T, then * VR(i)+sqrt(-1)*VR(i+1) is the complex * eigenvector corresponding to the eigenvalue * with positive real part. * if HOWMNY = 'B', the matrix Q*X; * if HOWMNY = 'S', the right eigenvectors of T specified by * SELECT, stored consecutively in the columns * of VR, in the same order as their * eigenvalues. * A complex eigenvector corresponding to a complex eigenvalue * is stored in two consecutive columns, the first holding the * real part and the second the imaginary part. * If SIDE = 'L', VR is not referenced. * * LDVR (input) INTEGER * The leading dimension of the array VR. LDVR >= max(1,N) if * SIDE = 'R' or 'B'; LDVR >= 1 otherwise. * * MM (input) INTEGER * The number of columns in the arrays VL and/or VR. MM >= M. * * M (output) INTEGER * The number of columns in the arrays VL and/or VR actually * used to store the eigenvectors. * If HOWMNY = 'A' or 'B', M is set to N. * Each selected real eigenvector occupies one column and each * selected complex eigenvector occupies two columns. * * WORK (workspace) DOUBLE PRECISION array, dimension (3*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The algorithm used in this program is basically backward (forward) * substitution, with scaling to make the the code robust against * possible overflow. * * Each eigenvector is normalized so that the element of largest * magnitude has magnitude 1; here the magnitude of a complex number * (x,y) is taken to be |x| + |y|. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLV, BOTHV, LEFTV, OVER, PAIR, RIGHTV, SOMEV INTEGER I, IERR, II, IP, IS, J, J1, J2, JNXT, K, KI, N2 DOUBLE PRECISION BETA, BIGNUM, EMAX, OVFL, REC, REMAX, SCALE, $ SMIN, SMLNUM, ULP, UNFL, VCRIT, VMAX, WI, WR, $ XNORM * .. * .. External Functions .. LOGICAL LSAME INTEGER IDAMAX DOUBLE PRECISION DDOT, DLAMCH EXTERNAL LSAME, IDAMAX, DDOT, DLAMCH * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DGEMV, DLALN2, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Local Arrays .. DOUBLE PRECISION X( 2, 2 ) * .. * .. Executable Statements .. * * Decode and test the input parameters * BOTHV = LSAME( SIDE, 'B' ) RIGHTV = LSAME( SIDE, 'R' ) .OR. BOTHV LEFTV = LSAME( SIDE, 'L' ) .OR. BOTHV * ALLV = LSAME( HOWMNY, 'A' ) OVER = LSAME( HOWMNY, 'B' ) SOMEV = LSAME( HOWMNY, 'S' ) * INFO = 0 IF( .NOT.RIGHTV .AND. .NOT.LEFTV ) THEN INFO = -1 ELSE IF( .NOT.ALLV .AND. .NOT.OVER .AND. .NOT.SOMEV ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDT.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDVL.LT.1 .OR. ( LEFTV .AND. LDVL.LT.N ) ) THEN INFO = -8 ELSE IF( LDVR.LT.1 .OR. ( RIGHTV .AND. LDVR.LT.N ) ) THEN INFO = -10 ELSE * * Set M to the number of columns required to store the selected * eigenvectors, standardize the array SELECT if necessary, and * test MM. * IF( SOMEV ) THEN M = 0 PAIR = .FALSE. DO 10 J = 1, N IF( PAIR ) THEN PAIR = .FALSE. SELECT( J ) = .FALSE. ELSE IF( J.LT.N ) THEN IF( T( J+1, J ).EQ.ZERO ) THEN IF( SELECT( J ) ) $ M = M + 1 ELSE PAIR = .TRUE. IF( SELECT( J ) .OR. SELECT( J+1 ) ) THEN SELECT( J ) = .TRUE. M = M + 2 END IF END IF ELSE IF( SELECT( N ) ) $ M = M + 1 END IF END IF 10 CONTINUE ELSE M = N END IF * IF( MM.LT.M ) THEN INFO = -11 END IF END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DTREVC', -INFO ) RETURN END IF * * Quick return if possible. * IF( N.EQ.0 ) $ RETURN * * Set the constants to control overflow. * UNFL = DLAMCH( 'Safe minimum' ) OVFL = ONE / UNFL CALL DLABAD( UNFL, OVFL ) ULP = DLAMCH( 'Precision' ) SMLNUM = UNFL*( N / ULP ) BIGNUM = ( ONE-ULP ) / SMLNUM * * Compute 1-norm of each column of strictly upper triangular * part of T to control overflow in triangular solver. * WORK( 1 ) = ZERO DO 30 J = 2, N WORK( J ) = ZERO DO 20 I = 1, J - 1 WORK( J ) = WORK( J ) + ABS( T( I, J ) ) 20 CONTINUE 30 CONTINUE * * Index IP is used to specify the real or complex eigenvalue: * IP = 0, real eigenvalue, * 1, first of conjugate complex pair: (wr,wi) * -1, second of conjugate complex pair: (wr,wi) * N2 = 2*N * IF( RIGHTV ) THEN * * Compute right eigenvectors. * IP = 0 IS = M DO 140 KI = N, 1, -1 * IF( IP.EQ.1 ) $ GO TO 130 IF( KI.EQ.1 ) $ GO TO 40 IF( T( KI, KI-1 ).EQ.ZERO ) $ GO TO 40 IP = -1 * 40 CONTINUE IF( SOMEV ) THEN IF( IP.EQ.0 ) THEN IF( .NOT.SELECT( KI ) ) $ GO TO 130 ELSE IF( .NOT.SELECT( KI-1 ) ) $ GO TO 130 END IF END IF * * Compute the KI-th eigenvalue (WR,WI). * WR = T( KI, KI ) WI = ZERO IF( IP.NE.0 ) $ WI = SQRT( ABS( T( KI, KI-1 ) ) )* $ SQRT( ABS( T( KI-1, KI ) ) ) SMIN = MAX( ULP*( ABS( WR )+ABS( WI ) ), SMLNUM ) * IF( IP.EQ.0 ) THEN * * Real right eigenvector * WORK( KI+N ) = ONE * * Form right-hand side * DO 50 K = 1, KI - 1 WORK( K+N ) = -T( K, KI ) 50 CONTINUE * * Solve the upper quasi-triangular system: * (T(1:KI-1,1:KI-1) - WR)*X = SCALE*WORK. * JNXT = KI - 1 DO 60 J = KI - 1, 1, -1 IF( J.GT.JNXT ) $ GO TO 60 J1 = J J2 = J JNXT = J - 1 IF( J.GT.1 ) THEN IF( T( J, J-1 ).NE.ZERO ) THEN J1 = J - 1 JNXT = J - 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1-by-1 diagonal block * CALL DLALN2( .FALSE., 1, 1, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, $ ZERO, X, 2, SCALE, XNORM, IERR ) * * Scale X(1,1) to avoid overflow when updating * the right-hand side. * IF( XNORM.GT.ONE ) THEN IF( WORK( J ).GT.BIGNUM / XNORM ) THEN X( 1, 1 ) = X( 1, 1 ) / XNORM SCALE = SCALE / XNORM END IF END IF * * Scale if necessary * IF( SCALE.NE.ONE ) $ CALL DSCAL( KI, SCALE, WORK( 1+N ), 1 ) WORK( J+N ) = X( 1, 1 ) * * Update right-hand side * CALL DAXPY( J-1, -X( 1, 1 ), T( 1, J ), 1, $ WORK( 1+N ), 1 ) * ELSE * * 2-by-2 diagonal block * CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, $ T( J-1, J-1 ), LDT, ONE, ONE, $ WORK( J-1+N ), N, WR, ZERO, X, 2, $ SCALE, XNORM, IERR ) * * Scale X(1,1) and X(2,1) to avoid overflow when * updating the right-hand side. * IF( XNORM.GT.ONE ) THEN BETA = MAX( WORK( J-1 ), WORK( J ) ) IF( BETA.GT.BIGNUM / XNORM ) THEN X( 1, 1 ) = X( 1, 1 ) / XNORM X( 2, 1 ) = X( 2, 1 ) / XNORM SCALE = SCALE / XNORM END IF END IF * * Scale if necessary * IF( SCALE.NE.ONE ) $ CALL DSCAL( KI, SCALE, WORK( 1+N ), 1 ) WORK( J-1+N ) = X( 1, 1 ) WORK( J+N ) = X( 2, 1 ) * * Update right-hand side * CALL DAXPY( J-2, -X( 1, 1 ), T( 1, J-1 ), 1, $ WORK( 1+N ), 1 ) CALL DAXPY( J-2, -X( 2, 1 ), T( 1, J ), 1, $ WORK( 1+N ), 1 ) END IF 60 CONTINUE * * Copy the vector x or Q*x to VR and normalize. * IF( .NOT.OVER ) THEN CALL DCOPY( KI, WORK( 1+N ), 1, VR( 1, IS ), 1 ) * II = IDAMAX( KI, VR( 1, IS ), 1 ) REMAX = ONE / ABS( VR( II, IS ) ) CALL DSCAL( KI, REMAX, VR( 1, IS ), 1 ) * DO 70 K = KI + 1, N VR( K, IS ) = ZERO 70 CONTINUE ELSE IF( KI.GT.1 ) $ CALL DGEMV( 'N', N, KI-1, ONE, VR, LDVR, $ WORK( 1+N ), 1, WORK( KI+N ), $ VR( 1, KI ), 1 ) * II = IDAMAX( N, VR( 1, KI ), 1 ) REMAX = ONE / ABS( VR( II, KI ) ) CALL DSCAL( N, REMAX, VR( 1, KI ), 1 ) END IF * ELSE * * Complex right eigenvector. * * Initial solve * [ (T(KI-1,KI-1) T(KI-1,KI) ) - (WR + I* WI)]*X = 0. * [ (T(KI,KI-1) T(KI,KI) ) ] * IF( ABS( T( KI-1, KI ) ).GE.ABS( T( KI, KI-1 ) ) ) THEN WORK( KI-1+N ) = ONE WORK( KI+N2 ) = WI / T( KI-1, KI ) ELSE WORK( KI-1+N ) = -WI / T( KI, KI-1 ) WORK( KI+N2 ) = ONE END IF WORK( KI+N ) = ZERO WORK( KI-1+N2 ) = ZERO * * Form right-hand side * DO 80 K = 1, KI - 2 WORK( K+N ) = -WORK( KI-1+N )*T( K, KI-1 ) WORK( K+N2 ) = -WORK( KI+N2 )*T( K, KI ) 80 CONTINUE * * Solve upper quasi-triangular system: * (T(1:KI-2,1:KI-2) - (WR+i*WI))*X = SCALE*(WORK+i*WORK2) * JNXT = KI - 2 DO 90 J = KI - 2, 1, -1 IF( J.GT.JNXT ) $ GO TO 90 J1 = J J2 = J JNXT = J - 1 IF( J.GT.1 ) THEN IF( T( J, J-1 ).NE.ZERO ) THEN J1 = J - 1 JNXT = J - 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1-by-1 diagonal block * CALL DLALN2( .FALSE., 1, 2, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, WI, $ X, 2, SCALE, XNORM, IERR ) * * Scale X(1,1) and X(1,2) to avoid overflow when * updating the right-hand side. * IF( XNORM.GT.ONE ) THEN IF( WORK( J ).GT.BIGNUM / XNORM ) THEN X( 1, 1 ) = X( 1, 1 ) / XNORM X( 1, 2 ) = X( 1, 2 ) / XNORM SCALE = SCALE / XNORM END IF END IF * * Scale if necessary * IF( SCALE.NE.ONE ) THEN CALL DSCAL( KI, SCALE, WORK( 1+N ), 1 ) CALL DSCAL( KI, SCALE, WORK( 1+N2 ), 1 ) END IF WORK( J+N ) = X( 1, 1 ) WORK( J+N2 ) = X( 1, 2 ) * * Update the right-hand side * CALL DAXPY( J-1, -X( 1, 1 ), T( 1, J ), 1, $ WORK( 1+N ), 1 ) CALL DAXPY( J-1, -X( 1, 2 ), T( 1, J ), 1, $ WORK( 1+N2 ), 1 ) * ELSE * * 2-by-2 diagonal block * CALL DLALN2( .FALSE., 2, 2, SMIN, ONE, $ T( J-1, J-1 ), LDT, ONE, ONE, $ WORK( J-1+N ), N, WR, WI, X, 2, SCALE, $ XNORM, IERR ) * * Scale X to avoid overflow when updating * the right-hand side. * IF( XNORM.GT.ONE ) THEN BETA = MAX( WORK( J-1 ), WORK( J ) ) IF( BETA.GT.BIGNUM / XNORM ) THEN REC = ONE / XNORM X( 1, 1 ) = X( 1, 1 )*REC X( 1, 2 ) = X( 1, 2 )*REC X( 2, 1 ) = X( 2, 1 )*REC X( 2, 2 ) = X( 2, 2 )*REC SCALE = SCALE*REC END IF END IF * * Scale if necessary * IF( SCALE.NE.ONE ) THEN CALL DSCAL( KI, SCALE, WORK( 1+N ), 1 ) CALL DSCAL( KI, SCALE, WORK( 1+N2 ), 1 ) END IF WORK( J-1+N ) = X( 1, 1 ) WORK( J+N ) = X( 2, 1 ) WORK( J-1+N2 ) = X( 1, 2 ) WORK( J+N2 ) = X( 2, 2 ) * * Update the right-hand side * CALL DAXPY( J-2, -X( 1, 1 ), T( 1, J-1 ), 1, $ WORK( 1+N ), 1 ) CALL DAXPY( J-2, -X( 2, 1 ), T( 1, J ), 1, $ WORK( 1+N ), 1 ) CALL DAXPY( J-2, -X( 1, 2 ), T( 1, J-1 ), 1, $ WORK( 1+N2 ), 1 ) CALL DAXPY( J-2, -X( 2, 2 ), T( 1, J ), 1, $ WORK( 1+N2 ), 1 ) END IF 90 CONTINUE * * Copy the vector x or Q*x to VR and normalize. * IF( .NOT.OVER ) THEN CALL DCOPY( KI, WORK( 1+N ), 1, VR( 1, IS-1 ), 1 ) CALL DCOPY( KI, WORK( 1+N2 ), 1, VR( 1, IS ), 1 ) * EMAX = ZERO DO 100 K = 1, KI EMAX = MAX( EMAX, ABS( VR( K, IS-1 ) )+ $ ABS( VR( K, IS ) ) ) 100 CONTINUE * REMAX = ONE / EMAX CALL DSCAL( KI, REMAX, VR( 1, IS-1 ), 1 ) CALL DSCAL( KI, REMAX, VR( 1, IS ), 1 ) * DO 110 K = KI + 1, N VR( K, IS-1 ) = ZERO VR( K, IS ) = ZERO 110 CONTINUE * ELSE * IF( KI.GT.2 ) THEN CALL DGEMV( 'N', N, KI-2, ONE, VR, LDVR, $ WORK( 1+N ), 1, WORK( KI-1+N ), $ VR( 1, KI-1 ), 1 ) CALL DGEMV( 'N', N, KI-2, ONE, VR, LDVR, $ WORK( 1+N2 ), 1, WORK( KI+N2 ), $ VR( 1, KI ), 1 ) ELSE CALL DSCAL( N, WORK( KI-1+N ), VR( 1, KI-1 ), 1 ) CALL DSCAL( N, WORK( KI+N2 ), VR( 1, KI ), 1 ) END IF * EMAX = ZERO DO 120 K = 1, N EMAX = MAX( EMAX, ABS( VR( K, KI-1 ) )+ $ ABS( VR( K, KI ) ) ) 120 CONTINUE REMAX = ONE / EMAX CALL DSCAL( N, REMAX, VR( 1, KI-1 ), 1 ) CALL DSCAL( N, REMAX, VR( 1, KI ), 1 ) END IF END IF * IS = IS - 1 IF( IP.NE.0 ) $ IS = IS - 1 130 CONTINUE IF( IP.EQ.1 ) $ IP = 0 IF( IP.EQ.-1 ) $ IP = 1 140 CONTINUE END IF * IF( LEFTV ) THEN * * Compute left eigenvectors. * IP = 0 IS = 1 DO 260 KI = 1, N * IF( IP.EQ.-1 ) $ GO TO 250 IF( KI.EQ.N ) $ GO TO 150 IF( T( KI+1, KI ).EQ.ZERO ) $ GO TO 150 IP = 1 * 150 CONTINUE IF( SOMEV ) THEN IF( .NOT.SELECT( KI ) ) $ GO TO 250 END IF * * Compute the KI-th eigenvalue (WR,WI). * WR = T( KI, KI ) WI = ZERO IF( IP.NE.0 ) $ WI = SQRT( ABS( T( KI, KI+1 ) ) )* $ SQRT( ABS( T( KI+1, KI ) ) ) SMIN = MAX( ULP*( ABS( WR )+ABS( WI ) ), SMLNUM ) * IF( IP.EQ.0 ) THEN * * Real left eigenvector. * WORK( KI+N ) = ONE * * Form right-hand side * DO 160 K = KI + 1, N WORK( K+N ) = -T( KI, K ) 160 CONTINUE * * Solve the quasi-triangular system: * (T(KI+1:N,KI+1:N) - WR)'*X = SCALE*WORK * VMAX = ONE VCRIT = BIGNUM * JNXT = KI + 1 DO 170 J = KI + 1, N IF( J.LT.JNXT ) $ GO TO 170 J1 = J J2 = J JNXT = J + 1 IF( J.LT.N ) THEN IF( T( J+1, J ).NE.ZERO ) THEN J2 = J + 1 JNXT = J + 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1-by-1 diagonal block * * Scale if necessary to avoid overflow when forming * the right-hand side. * IF( WORK( J ).GT.VCRIT ) THEN REC = ONE / VMAX CALL DSCAL( N-KI+1, REC, WORK( KI+N ), 1 ) VMAX = ONE VCRIT = BIGNUM END IF * WORK( J+N ) = WORK( J+N ) - $ DDOT( J-KI-1, T( KI+1, J ), 1, $ WORK( KI+1+N ), 1 ) * * Solve (T(J,J)-WR)'*X = WORK * CALL DLALN2( .FALSE., 1, 1, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, $ ZERO, X, 2, SCALE, XNORM, IERR ) * * Scale if necessary * IF( SCALE.NE.ONE ) $ CALL DSCAL( N-KI+1, SCALE, WORK( KI+N ), 1 ) WORK( J+N ) = X( 1, 1 ) VMAX = MAX( ABS( WORK( J+N ) ), VMAX ) VCRIT = BIGNUM / VMAX * ELSE * * 2-by-2 diagonal block * * Scale if necessary to avoid overflow when forming * the right-hand side. * BETA = MAX( WORK( J ), WORK( J+1 ) ) IF( BETA.GT.VCRIT ) THEN REC = ONE / VMAX CALL DSCAL( N-KI+1, REC, WORK( KI+N ), 1 ) VMAX = ONE VCRIT = BIGNUM END IF * WORK( J+N ) = WORK( J+N ) - $ DDOT( J-KI-1, T( KI+1, J ), 1, $ WORK( KI+1+N ), 1 ) * WORK( J+1+N ) = WORK( J+1+N ) - $ DDOT( J-KI-1, T( KI+1, J+1 ), 1, $ WORK( KI+1+N ), 1 ) * * Solve * [T(J,J)-WR T(J,J+1) ]'* X = SCALE*( WORK1 ) * [T(J+1,J) T(J+1,J+1)-WR] ( WORK2 ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, $ ZERO, X, 2, SCALE, XNORM, IERR ) * * Scale if necessary * IF( SCALE.NE.ONE ) $ CALL DSCAL( N-KI+1, SCALE, WORK( KI+N ), 1 ) WORK( J+N ) = X( 1, 1 ) WORK( J+1+N ) = X( 2, 1 ) * VMAX = MAX( ABS( WORK( J+N ) ), $ ABS( WORK( J+1+N ) ), VMAX ) VCRIT = BIGNUM / VMAX * END IF 170 CONTINUE * * Copy the vector x or Q*x to VL and normalize. * IF( .NOT.OVER ) THEN CALL DCOPY( N-KI+1, WORK( KI+N ), 1, VL( KI, IS ), 1 ) * II = IDAMAX( N-KI+1, VL( KI, IS ), 1 ) + KI - 1 REMAX = ONE / ABS( VL( II, IS ) ) CALL DSCAL( N-KI+1, REMAX, VL( KI, IS ), 1 ) * DO 180 K = 1, KI - 1 VL( K, IS ) = ZERO 180 CONTINUE * ELSE * IF( KI.LT.N ) $ CALL DGEMV( 'N', N, N-KI, ONE, VL( 1, KI+1 ), LDVL, $ WORK( KI+1+N ), 1, WORK( KI+N ), $ VL( 1, KI ), 1 ) * II = IDAMAX( N, VL( 1, KI ), 1 ) REMAX = ONE / ABS( VL( II, KI ) ) CALL DSCAL( N, REMAX, VL( 1, KI ), 1 ) * END IF * ELSE * * Complex left eigenvector. * * Initial solve: * ((T(KI,KI) T(KI,KI+1) )' - (WR - I* WI))*X = 0. * ((T(KI+1,KI) T(KI+1,KI+1)) ) * IF( ABS( T( KI, KI+1 ) ).GE.ABS( T( KI+1, KI ) ) ) THEN WORK( KI+N ) = WI / T( KI, KI+1 ) WORK( KI+1+N2 ) = ONE ELSE WORK( KI+N ) = ONE WORK( KI+1+N2 ) = -WI / T( KI+1, KI ) END IF WORK( KI+1+N ) = ZERO WORK( KI+N2 ) = ZERO * * Form right-hand side * DO 190 K = KI + 2, N WORK( K+N ) = -WORK( KI+N )*T( KI, K ) WORK( K+N2 ) = -WORK( KI+1+N2 )*T( KI+1, K ) 190 CONTINUE * * Solve complex quasi-triangular system: * ( T(KI+2,N:KI+2,N) - (WR-i*WI) )*X = WORK1+i*WORK2 * VMAX = ONE VCRIT = BIGNUM * JNXT = KI + 2 DO 200 J = KI + 2, N IF( J.LT.JNXT ) $ GO TO 200 J1 = J J2 = J JNXT = J + 1 IF( J.LT.N ) THEN IF( T( J+1, J ).NE.ZERO ) THEN J2 = J + 1 JNXT = J + 2 END IF END IF * IF( J1.EQ.J2 ) THEN * * 1-by-1 diagonal block * * Scale if necessary to avoid overflow when * forming the right-hand side elements. * IF( WORK( J ).GT.VCRIT ) THEN REC = ONE / VMAX CALL DSCAL( N-KI+1, REC, WORK( KI+N ), 1 ) CALL DSCAL( N-KI+1, REC, WORK( KI+N2 ), 1 ) VMAX = ONE VCRIT = BIGNUM END IF * WORK( J+N ) = WORK( J+N ) - $ DDOT( J-KI-2, T( KI+2, J ), 1, $ WORK( KI+2+N ), 1 ) WORK( J+N2 ) = WORK( J+N2 ) - $ DDOT( J-KI-2, T( KI+2, J ), 1, $ WORK( KI+2+N2 ), 1 ) * * Solve (T(J,J)-(WR-i*WI))*(X11+i*X12)= WK+I*WK2 * CALL DLALN2( .FALSE., 1, 2, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, $ -WI, X, 2, SCALE, XNORM, IERR ) * * Scale if necessary * IF( SCALE.NE.ONE ) THEN CALL DSCAL( N-KI+1, SCALE, WORK( KI+N ), 1 ) CALL DSCAL( N-KI+1, SCALE, WORK( KI+N2 ), 1 ) END IF WORK( J+N ) = X( 1, 1 ) WORK( J+N2 ) = X( 1, 2 ) VMAX = MAX( ABS( WORK( J+N ) ), $ ABS( WORK( J+N2 ) ), VMAX ) VCRIT = BIGNUM / VMAX * ELSE * * 2-by-2 diagonal block * * Scale if necessary to avoid overflow when forming * the right-hand side elements. * BETA = MAX( WORK( J ), WORK( J+1 ) ) IF( BETA.GT.VCRIT ) THEN REC = ONE / VMAX CALL DSCAL( N-KI+1, REC, WORK( KI+N ), 1 ) CALL DSCAL( N-KI+1, REC, WORK( KI+N2 ), 1 ) VMAX = ONE VCRIT = BIGNUM END IF * WORK( J+N ) = WORK( J+N ) - $ DDOT( J-KI-2, T( KI+2, J ), 1, $ WORK( KI+2+N ), 1 ) * WORK( J+N2 ) = WORK( J+N2 ) - $ DDOT( J-KI-2, T( KI+2, J ), 1, $ WORK( KI+2+N2 ), 1 ) * WORK( J+1+N ) = WORK( J+1+N ) - $ DDOT( J-KI-2, T( KI+2, J+1 ), 1, $ WORK( KI+2+N ), 1 ) * WORK( J+1+N2 ) = WORK( J+1+N2 ) - $ DDOT( J-KI-2, T( KI+2, J+1 ), 1, $ WORK( KI+2+N2 ), 1 ) * * Solve 2-by-2 complex linear equation * ([T(j,j) T(j,j+1) ]'-(wr-i*wi)*I)*X = SCALE*B * ([T(j+1,j) T(j+1,j+1)] ) * CALL DLALN2( .TRUE., 2, 2, SMIN, ONE, T( J, J ), $ LDT, ONE, ONE, WORK( J+N ), N, WR, $ -WI, X, 2, SCALE, XNORM, IERR ) * * Scale if necessary * IF( SCALE.NE.ONE ) THEN CALL DSCAL( N-KI+1, SCALE, WORK( KI+N ), 1 ) CALL DSCAL( N-KI+1, SCALE, WORK( KI+N2 ), 1 ) END IF WORK( J+N ) = X( 1, 1 ) WORK( J+N2 ) = X( 1, 2 ) WORK( J+1+N ) = X( 2, 1 ) WORK( J+1+N2 ) = X( 2, 2 ) VMAX = MAX( ABS( X( 1, 1 ) ), ABS( X( 1, 2 ) ), $ ABS( X( 2, 1 ) ), ABS( X( 2, 2 ) ), VMAX ) VCRIT = BIGNUM / VMAX * END IF 200 CONTINUE * * Copy the vector x or Q*x to VL and normalize. * 210 CONTINUE IF( .NOT.OVER ) THEN CALL DCOPY( N-KI+1, WORK( KI+N ), 1, VL( KI, IS ), 1 ) CALL DCOPY( N-KI+1, WORK( KI+N2 ), 1, VL( KI, IS+1 ), $ 1 ) * EMAX = ZERO DO 220 K = KI, N EMAX = MAX( EMAX, ABS( VL( K, IS ) )+ $ ABS( VL( K, IS+1 ) ) ) 220 CONTINUE REMAX = ONE / EMAX CALL DSCAL( N-KI+1, REMAX, VL( KI, IS ), 1 ) CALL DSCAL( N-KI+1, REMAX, VL( KI, IS+1 ), 1 ) * DO 230 K = 1, KI - 1 VL( K, IS ) = ZERO VL( K, IS+1 ) = ZERO 230 CONTINUE ELSE IF( KI.LT.N-1 ) THEN CALL DGEMV( 'N', N, N-KI-1, ONE, VL( 1, KI+2 ), $ LDVL, WORK( KI+2+N ), 1, WORK( KI+N ), $ VL( 1, KI ), 1 ) CALL DGEMV( 'N', N, N-KI-1, ONE, VL( 1, KI+2 ), $ LDVL, WORK( KI+2+N2 ), 1, $ WORK( KI+1+N2 ), VL( 1, KI+1 ), 1 ) ELSE CALL DSCAL( N, WORK( KI+N ), VL( 1, KI ), 1 ) CALL DSCAL( N, WORK( KI+1+N2 ), VL( 1, KI+1 ), 1 ) END IF * EMAX = ZERO DO 240 K = 1, N EMAX = MAX( EMAX, ABS( VL( K, KI ) )+ $ ABS( VL( K, KI+1 ) ) ) 240 CONTINUE REMAX = ONE / EMAX CALL DSCAL( N, REMAX, VL( 1, KI ), 1 ) CALL DSCAL( N, REMAX, VL( 1, KI+1 ), 1 ) * END IF * END IF * IS = IS + 1 IF( IP.NE.0 ) $ IS = IS + 1 250 CONTINUE IF( IP.EQ.-1 ) $ IP = 0 IF( IP.EQ.1 ) $ IP = -1 * 260 CONTINUE * END IF * RETURN * * End of DTREVC * END SUBROUTINE DTREXC( COMPQ, N, T, LDT, Q, LDQ, IFST, ILST, WORK, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER COMPQ INTEGER IFST, ILST, INFO, LDQ, LDT, N * .. * .. Array Arguments .. DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WORK( * ) * .. * * Purpose * ======= * * DTREXC reorders the real Schur factorization of a real matrix * A = Q*T*Q**T, so that the diagonal block of T with row index IFST is * moved to row ILST. * * The real Schur form T is reordered by an orthogonal similarity * transformation Z**T*T*Z, and optionally the matrix Q of Schur vectors * is updated by postmultiplying it with Z. * * T must be in Schur canonical form (as returned by DHSEQR), that is, * block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each * 2-by-2 diagonal block has its diagonal elements equal and its * off-diagonal elements of opposite sign. * * Arguments * ========= * * COMPQ (input) CHARACTER*1 * = 'V': update the matrix Q of Schur vectors; * = 'N': do not update Q. * * N (input) INTEGER * The order of the matrix T. N >= 0. * * T (input/output) DOUBLE PRECISION array, dimension (LDT,N) * On entry, the upper quasi-triangular matrix T, in Schur * Schur canonical form. * On exit, the reordered upper quasi-triangular matrix, again * in Schur canonical form. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= max(1,N). * * Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N) * On entry, if COMPQ = 'V', the matrix Q of Schur vectors. * On exit, if COMPQ = 'V', Q has been postmultiplied by the * orthogonal transformation matrix Z which reorders T. * If COMPQ = 'N', Q is not referenced. * * LDQ (input) INTEGER * The leading dimension of the array Q. LDQ >= max(1,N). * * IFST (input/output) INTEGER * ILST (input/output) INTEGER * Specify the reordering of the diagonal blocks of T. * The block with row index IFST is moved to row ILST, by a * sequence of transpositions between adjacent blocks. * On exit, if IFST pointed on entry to the second row of a * 2-by-2 block, it is changed to point to the first row; ILST * always points to the first row of the block in its final * position (which may differ from its input value by +1 or -1). * 1 <= IFST <= N; 1 <= ILST <= N. * * WORK (workspace) DOUBLE PRECISION array, dimension (N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * = 1: two adjacent blocks were too close to swap (the problem * is very ill-conditioned); T may have been partially * reordered, and ILST points to the first row of the * current position of the block being moved. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL WANTQ INTEGER HERE, NBF, NBL, NBNEXT * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLAEXC, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Decode and test the input arguments. * INFO = 0 WANTQ = LSAME( COMPQ, 'V' ) IF( .NOT.WANTQ .AND. .NOT.LSAME( COMPQ, 'N' ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 ELSE IF( LDT.LT.MAX( 1, N ) ) THEN INFO = -4 ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.MAX( 1, N ) ) ) THEN INFO = -6 ELSE IF( IFST.LT.1 .OR. IFST.GT.N ) THEN INFO = -7 ELSE IF( ILST.LT.1 .OR. ILST.GT.N ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DTREXC', -INFO ) RETURN END IF * * Quick return if possible * IF( N.LE.1 ) $ RETURN * * Determine the first row of specified block * and find out it is 1 by 1 or 2 by 2. * IF( IFST.GT.1 ) THEN IF( T( IFST, IFST-1 ).NE.ZERO ) $ IFST = IFST - 1 END IF NBF = 1 IF( IFST.LT.N ) THEN IF( T( IFST+1, IFST ).NE.ZERO ) $ NBF = 2 END IF * * Determine the first row of the final block * and find out it is 1 by 1 or 2 by 2. * IF( ILST.GT.1 ) THEN IF( T( ILST, ILST-1 ).NE.ZERO ) $ ILST = ILST - 1 END IF NBL = 1 IF( ILST.LT.N ) THEN IF( T( ILST+1, ILST ).NE.ZERO ) $ NBL = 2 END IF * IF( IFST.EQ.ILST ) $ RETURN * IF( IFST.LT.ILST ) THEN * * Update ILST * IF( NBF.EQ.2 .AND. NBL.EQ.1 ) $ ILST = ILST - 1 IF( NBF.EQ.1 .AND. NBL.EQ.2 ) $ ILST = ILST + 1 * HERE = IFST * 10 CONTINUE * * Swap block with next one below * IF( NBF.EQ.1 .OR. NBF.EQ.2 ) THEN * * Current block either 1 by 1 or 2 by 2 * NBNEXT = 1 IF( HERE+NBF+1.LE.N ) THEN IF( T( HERE+NBF+1, HERE+NBF ).NE.ZERO ) $ NBNEXT = 2 END IF CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, NBF, NBNEXT, $ WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF HERE = HERE + NBNEXT * * Test if 2 by 2 block breaks into two 1 by 1 blocks * IF( NBF.EQ.2 ) THEN IF( T( HERE+1, HERE ).EQ.ZERO ) $ NBF = 3 END IF * ELSE * * Current block consists of two 1 by 1 blocks each of which * must be swapped individually * NBNEXT = 1 IF( HERE+3.LE.N ) THEN IF( T( HERE+3, HERE+2 ).NE.ZERO ) $ NBNEXT = 2 END IF CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE+1, 1, NBNEXT, $ WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF IF( NBNEXT.EQ.1 ) THEN * * Swap two 1 by 1 blocks, no problems possible * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, 1, NBNEXT, $ WORK, INFO ) HERE = HERE + 1 ELSE * * Recompute NBNEXT in case 2 by 2 split * IF( T( HERE+2, HERE+1 ).EQ.ZERO ) $ NBNEXT = 1 IF( NBNEXT.EQ.2 ) THEN * * 2 by 2 Block did not split * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, 1, $ NBNEXT, WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF HERE = HERE + 2 ELSE * * 2 by 2 Block did split * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, 1, 1, $ WORK, INFO ) CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE+1, 1, 1, $ WORK, INFO ) HERE = HERE + 2 END IF END IF END IF IF( HERE.LT.ILST ) $ GO TO 10 * ELSE * HERE = IFST 20 CONTINUE * * Swap block with next one above * IF( NBF.EQ.1 .OR. NBF.EQ.2 ) THEN * * Current block either 1 by 1 or 2 by 2 * NBNEXT = 1 IF( HERE.GE.3 ) THEN IF( T( HERE-1, HERE-2 ).NE.ZERO ) $ NBNEXT = 2 END IF CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE-NBNEXT, NBNEXT, $ NBF, WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF HERE = HERE - NBNEXT * * Test if 2 by 2 block breaks into two 1 by 1 blocks * IF( NBF.EQ.2 ) THEN IF( T( HERE+1, HERE ).EQ.ZERO ) $ NBF = 3 END IF * ELSE * * Current block consists of two 1 by 1 blocks each of which * must be swapped individually * NBNEXT = 1 IF( HERE.GE.3 ) THEN IF( T( HERE-1, HERE-2 ).NE.ZERO ) $ NBNEXT = 2 END IF CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE-NBNEXT, NBNEXT, $ 1, WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF IF( NBNEXT.EQ.1 ) THEN * * Swap two 1 by 1 blocks, no problems possible * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, NBNEXT, 1, $ WORK, INFO ) HERE = HERE - 1 ELSE * * Recompute NBNEXT in case 2 by 2 split * IF( T( HERE, HERE-1 ).EQ.ZERO ) $ NBNEXT = 1 IF( NBNEXT.EQ.2 ) THEN * * 2 by 2 Block did not split * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE-1, 2, 1, $ WORK, INFO ) IF( INFO.NE.0 ) THEN ILST = HERE RETURN END IF HERE = HERE - 2 ELSE * * 2 by 2 Block did split * CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE, 1, 1, $ WORK, INFO ) CALL DLAEXC( WANTQ, N, T, LDT, Q, LDQ, HERE-1, 1, 1, $ WORK, INFO ) HERE = HERE - 2 END IF END IF END IF IF( HERE.GT.ILST ) $ GO TO 20 END IF ILST = HERE * RETURN * * End of DTREXC * END SUBROUTINE DTRSEN( JOB, COMPQ, SELECT, N, T, LDT, Q, LDQ, WR, WI, $ M, S, SEP, WORK, LWORK, IWORK, LIWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER COMPQ, JOB INTEGER INFO, LDQ, LDT, LIWORK, LWORK, M, N DOUBLE PRECISION S, SEP * .. * .. Array Arguments .. LOGICAL SELECT( * ) INTEGER IWORK( * ) DOUBLE PRECISION Q( LDQ, * ), T( LDT, * ), WI( * ), WORK( * ), $ WR( * ) * .. * * Purpose * ======= * * DTRSEN reorders the real Schur factorization of a real matrix * A = Q*T*Q**T, so that a selected cluster of eigenvalues appears in * the leading diagonal blocks of the upper quasi-triangular matrix T, * and the leading columns of Q form an orthonormal basis of the * corresponding right invariant subspace. * * Optionally the routine computes the reciprocal condition numbers of * the cluster of eigenvalues and/or the invariant subspace. * * T must be in Schur canonical form (as returned by DHSEQR), that is, * block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each * 2-by-2 diagonal block has its diagonal elemnts equal and its * off-diagonal elements of opposite sign. * * Arguments * ========= * * JOB (input) CHARACTER*1 * Specifies whether condition numbers are required for the * cluster of eigenvalues (S) or the invariant subspace (SEP): * = 'N': none; * = 'E': for eigenvalues only (S); * = 'V': for invariant subspace only (SEP); * = 'B': for both eigenvalues and invariant subspace (S and * SEP). * * COMPQ (input) CHARACTER*1 * = 'V': update the matrix Q of Schur vectors; * = 'N': do not update Q. * * SELECT (input) LOGICAL array, dimension (N) * SELECT specifies the eigenvalues in the selected cluster. To * select a real eigenvalue w(j), SELECT(j) must be set to * .TRUE.. To select a complex conjugate pair of eigenvalues * w(j) and w(j+1), corresponding to a 2-by-2 diagonal block, * either SELECT(j) or SELECT(j+1) or both must be set to * .TRUE.; a complex conjugate pair of eigenvalues must be * either both included in the cluster or both excluded. * * N (input) INTEGER * The order of the matrix T. N >= 0. * * T (input/output) DOUBLE PRECISION array, dimension (LDT,N) * On entry, the upper quasi-triangular matrix T, in Schur * canonical form. * On exit, T is overwritten by the reordered matrix T, again in * Schur canonical form, with the selected eigenvalues in the * leading diagonal blocks. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= max(1,N). * * Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N) * On entry, if COMPQ = 'V', the matrix Q of Schur vectors. * On exit, if COMPQ = 'V', Q has been postmultiplied by the * orthogonal transformation matrix which reorders T; the * leading M columns of Q form an orthonormal basis for the * specified invariant subspace. * If COMPQ = 'N', Q is not referenced. * * LDQ (input) INTEGER * The leading dimension of the array Q. * LDQ >= 1; and if COMPQ = 'V', LDQ >= N. * * WR (output) DOUBLE PRECISION array, dimension (N) * WI (output) DOUBLE PRECISION array, dimension (N) * The real and imaginary parts, respectively, of the reordered * eigenvalues of T. The eigenvalues are stored in the same * order as on the diagonal of T, with WR(i) = T(i,i) and, if * T(i:i+1,i:i+1) is a 2-by-2 diagonal block, WI(i) > 0 and * WI(i+1) = -WI(i). Note that if a complex eigenvalue is * sufficiently ill-conditioned, then its value may differ * significantly from its value before reordering. * * M (output) INTEGER * The dimension of the specified invariant subspace. * 0 < = M <= N. * * S (output) DOUBLE PRECISION * If JOB = 'E' or 'B', S is a lower bound on the reciprocal * condition number for the selected cluster of eigenvalues. * S cannot underestimate the true reciprocal condition number * by more than a factor of sqrt(N). If M = 0 or N, S = 1. * If JOB = 'N' or 'V', S is not referenced. * * SEP (output) DOUBLE PRECISION * If JOB = 'V' or 'B', SEP is the estimated reciprocal * condition number of the specified invariant subspace. If * M = 0 or N, SEP = norm(T). * If JOB = 'N' or 'E', SEP is not referenced. * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If JOB = 'N', LWORK >= max(1,N); * if JOB = 'E', LWORK >= M*(N-M); * if JOB = 'V' or 'B', LWORK >= 2*M*(N-M). * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace) INTEGER array, dimension (LIWORK) * IF JOB = 'N' or 'E', IWORK is not referenced. * * LIWORK (input) INTEGER * The dimension of the array IWORK. * If JOB = 'N' or 'E', LIWORK >= 1; * if JOB = 'V' or 'B', LIWORK >= M*(N-M). * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * = 1: reordering of T failed because some eigenvalues are too * close to separate (the problem is very ill-conditioned); * T may have been partially reordered, and WR and WI * contain the eigenvalues in the same order as in T; S and * SEP (if requested) are set to zero. * * Further Details * =============== * * DTRSEN first collects the selected eigenvalues by computing an * orthogonal transformation Z to move them to the top left corner of T. * In other words, the selected eigenvalues are the eigenvalues of T11 * in: * * Z'*T*Z = ( T11 T12 ) n1 * ( 0 T22 ) n2 * n1 n2 * * where N = n1+n2 and Z' means the transpose of Z. The first n1 columns * of Z span the specified invariant subspace of T. * * If T has been obtained from the real Schur factorization of a matrix * A = Q*T*Q', then the reordered real Schur factorization of A is given * by A = (Q*Z)*(Z'*T*Z)*(Q*Z)', and the first n1 columns of Q*Z span * the corresponding invariant subspace of A. * * The reciprocal condition number of the average of the eigenvalues of * T11 may be returned in S. S lies between 0 (very badly conditioned) * and 1 (very well conditioned). It is computed as follows. First we * compute R so that * * P = ( I R ) n1 * ( 0 0 ) n2 * n1 n2 * * is the projector on the invariant subspace associated with T11. * R is the solution of the Sylvester equation: * * T11*R - R*T22 = T12. * * Let F-norm(M) denote the Frobenius-norm of M and 2-norm(M) denote * the two-norm of M. Then S is computed as the lower bound * * (1 + F-norm(R)**2)**(-1/2) * * on the reciprocal of 2-norm(P), the true reciprocal condition number. * S cannot underestimate 1 / 2-norm(P) by more than a factor of * sqrt(N). * * An approximate error bound for the computed average of the * eigenvalues of T11 is * * EPS * norm(T) / S * * where EPS is the machine precision. * * The reciprocal condition number of the right invariant subspace * spanned by the first n1 columns of Z (or of Q*Z) is returned in SEP. * SEP is defined as the separation of T11 and T22: * * sep( T11, T22 ) = sigma-min( C ) * * where sigma-min(C) is the smallest singular value of the * n1*n2-by-n1*n2 matrix * * C = kprod( I(n2), T11 ) - kprod( transpose(T22), I(n1) ) * * I(m) is an m by m identity matrix, and kprod denotes the Kronecker * product. We estimate sigma-min(C) by the reciprocal of an estimate of * the 1-norm of inverse(C). The true reciprocal 1-norm of inverse(C) * cannot differ from sigma-min(C) by more than a factor of sqrt(n1*n2). * * When SEP is small, small changes in T can cause large changes in * the invariant subspace. An approximate bound on the maximum angular * error in the computed right invariant subspace is * * EPS * norm(T) / SEP * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, PAIR, SWAP, WANTBH, WANTQ, WANTS, $ WANTSP INTEGER IERR, K, KASE, KK, KS, LIWMIN, LWMIN, N1, N2, $ NN DOUBLE PRECISION EST, RNORM, SCALE * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLANGE EXTERNAL LSAME, DLANGE * .. * .. External Subroutines .. EXTERNAL DLACON, DLACPY, DTREXC, DTRSYL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode and test the input parameters * WANTBH = LSAME( JOB, 'B' ) WANTS = LSAME( JOB, 'E' ) .OR. WANTBH WANTSP = LSAME( JOB, 'V' ) .OR. WANTBH WANTQ = LSAME( COMPQ, 'V' ) * INFO = 0 LQUERY = ( LWORK.EQ.-1 ) IF( .NOT.LSAME( JOB, 'N' ) .AND. .NOT.WANTS .AND. .NOT.WANTSP ) $ THEN INFO = -1 ELSE IF( .NOT.LSAME( COMPQ, 'N' ) .AND. .NOT.WANTQ ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDT.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDQ.LT.1 .OR. ( WANTQ .AND. LDQ.LT.N ) ) THEN INFO = -8 ELSE * * Set M to the dimension of the specified invariant subspace, * and test LWORK and LIWORK. * M = 0 PAIR = .FALSE. DO 10 K = 1, N IF( PAIR ) THEN PAIR = .FALSE. ELSE IF( K.LT.N ) THEN IF( T( K+1, K ).EQ.ZERO ) THEN IF( SELECT( K ) ) $ M = M + 1 ELSE PAIR = .TRUE. IF( SELECT( K ) .OR. SELECT( K+1 ) ) $ M = M + 2 END IF ELSE IF( SELECT( N ) ) $ M = M + 1 END IF END IF 10 CONTINUE * N1 = M N2 = N - M NN = N1*N2 * IF( WANTSP ) THEN LWMIN = MAX( 1, 2*NN ) LIWMIN = MAX( 1, NN ) ELSE IF( LSAME( JOB, 'N' ) ) THEN LWMIN = MAX( 1, N ) LIWMIN = 1 ELSE IF( LSAME( JOB, 'E' ) ) THEN LWMIN = MAX( 1, NN ) LIWMIN = 1 END IF * IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -15 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -17 END IF END IF * IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DTRSEN', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible. * IF( M.EQ.N .OR. M.EQ.0 ) THEN IF( WANTS ) $ S = ONE IF( WANTSP ) $ SEP = DLANGE( '1', N, N, T, LDT, WORK ) GO TO 40 END IF * * Collect the selected blocks at the top-left corner of T. * KS = 0 PAIR = .FALSE. DO 20 K = 1, N IF( PAIR ) THEN PAIR = .FALSE. ELSE SWAP = SELECT( K ) IF( K.LT.N ) THEN IF( T( K+1, K ).NE.ZERO ) THEN PAIR = .TRUE. SWAP = SWAP .OR. SELECT( K+1 ) END IF END IF IF( SWAP ) THEN KS = KS + 1 * * Swap the K-th block to position KS. * IERR = 0 KK = K IF( K.NE.KS ) $ CALL DTREXC( COMPQ, N, T, LDT, Q, LDQ, KK, KS, WORK, $ IERR ) IF( IERR.EQ.1 .OR. IERR.EQ.2 ) THEN * * Blocks too close to swap: exit. * INFO = 1 IF( WANTS ) $ S = ZERO IF( WANTSP ) $ SEP = ZERO GO TO 40 END IF IF( PAIR ) $ KS = KS + 1 END IF END IF 20 CONTINUE * IF( WANTS ) THEN * * Solve Sylvester equation for R: * * T11*R - R*T22 = scale*T12 * CALL DLACPY( 'F', N1, N2, T( 1, N1+1 ), LDT, WORK, N1 ) CALL DTRSYL( 'N', 'N', -1, N1, N2, T, LDT, T( N1+1, N1+1 ), $ LDT, WORK, N1, SCALE, IERR ) * * Estimate the reciprocal of the condition number of the cluster * of eigenvalues. * RNORM = DLANGE( 'F', N1, N2, WORK, N1, WORK ) IF( RNORM.EQ.ZERO ) THEN S = ONE ELSE S = SCALE / ( SQRT( SCALE*SCALE / RNORM+RNORM )* $ SQRT( RNORM ) ) END IF END IF * IF( WANTSP ) THEN * * Estimate sep(T11,T22). * EST = ZERO KASE = 0 30 CONTINUE CALL DLACON( NN, WORK( NN+1 ), WORK, IWORK, EST, KASE ) IF( KASE.NE.0 ) THEN IF( KASE.EQ.1 ) THEN * * Solve T11*R - R*T22 = scale*X. * CALL DTRSYL( 'N', 'N', -1, N1, N2, T, LDT, $ T( N1+1, N1+1 ), LDT, WORK, N1, SCALE, $ IERR ) ELSE * * Solve T11'*R - R*T22' = scale*X. * CALL DTRSYL( 'T', 'T', -1, N1, N2, T, LDT, $ T( N1+1, N1+1 ), LDT, WORK, N1, SCALE, $ IERR ) END IF GO TO 30 END IF * SEP = SCALE / EST END IF * 40 CONTINUE * * Store the output eigenvalues in WR and WI. * DO 50 K = 1, N WR( K ) = T( K, K ) WI( K ) = ZERO 50 CONTINUE DO 60 K = 1, N - 1 IF( T( K+1, K ).NE.ZERO ) THEN WI( K ) = SQRT( ABS( T( K, K+1 ) ) )* $ SQRT( ABS( T( K+1, K ) ) ) WI( K+1 ) = -WI( K ) END IF 60 CONTINUE * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN * RETURN * * End of DTRSEN * END SUBROUTINE DTRSNA( JOB, HOWMNY, SELECT, N, T, LDT, VL, LDVL, VR, $ LDVR, S, SEP, MM, M, WORK, LDWORK, IWORK, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER HOWMNY, JOB INTEGER INFO, LDT, LDVL, LDVR, LDWORK, M, MM, N * .. * .. Array Arguments .. LOGICAL SELECT( * ) INTEGER IWORK( * ) DOUBLE PRECISION S( * ), SEP( * ), T( LDT, * ), VL( LDVL, * ), $ VR( LDVR, * ), WORK( LDWORK, * ) * .. * * Purpose * ======= * * DTRSNA estimates reciprocal condition numbers for specified * eigenvalues and/or right eigenvectors of a real upper * quasi-triangular matrix T (or of any matrix Q*T*Q**T with Q * orthogonal). * * T must be in Schur canonical form (as returned by DHSEQR), that is, * block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each * 2-by-2 diagonal block has its diagonal elements equal and its * off-diagonal elements of opposite sign. * * Arguments * ========= * * JOB (input) CHARACTER*1 * Specifies whether condition numbers are required for * eigenvalues (S) or eigenvectors (SEP): * = 'E': for eigenvalues only (S); * = 'V': for eigenvectors only (SEP); * = 'B': for both eigenvalues and eigenvectors (S and SEP). * * HOWMNY (input) CHARACTER*1 * = 'A': compute condition numbers for all eigenpairs; * = 'S': compute condition numbers for selected eigenpairs * specified by the array SELECT. * * SELECT (input) LOGICAL array, dimension (N) * If HOWMNY = 'S', SELECT specifies the eigenpairs for which * condition numbers are required. To select condition numbers * for the eigenpair corresponding to a real eigenvalue w(j), * SELECT(j) must be set to .TRUE.. To select condition numbers * corresponding to a complex conjugate pair of eigenvalues w(j) * and w(j+1), either SELECT(j) or SELECT(j+1) or both, must be * set to .TRUE.. * If HOWMNY = 'A', SELECT is not referenced. * * N (input) INTEGER * The order of the matrix T. N >= 0. * * T (input) DOUBLE PRECISION array, dimension (LDT,N) * The upper quasi-triangular matrix T, in Schur canonical form. * * LDT (input) INTEGER * The leading dimension of the array T. LDT >= max(1,N). * * VL (input) DOUBLE PRECISION array, dimension (LDVL,M) * If JOB = 'E' or 'B', VL must contain left eigenvectors of T * (or of any Q*T*Q**T with Q orthogonal), corresponding to the * eigenpairs specified by HOWMNY and SELECT. The eigenvectors * must be stored in consecutive columns of VL, as returned by * DHSEIN or DTREVC. * If JOB = 'V', VL is not referenced. * * LDVL (input) INTEGER * The leading dimension of the array VL. * LDVL >= 1; and if JOB = 'E' or 'B', LDVL >= N. * * VR (input) DOUBLE PRECISION array, dimension (LDVR,M) * If JOB = 'E' or 'B', VR must contain right eigenvectors of T * (or of any Q*T*Q**T with Q orthogonal), corresponding to the * eigenpairs specified by HOWMNY and SELECT. The eigenvectors * must be stored in consecutive columns of VR, as returned by * DHSEIN or DTREVC. * If JOB = 'V', VR is not referenced. * * LDVR (input) INTEGER * The leading dimension of the array VR. * LDVR >= 1; and if JOB = 'E' or 'B', LDVR >= N. * * S (output) DOUBLE PRECISION array, dimension (MM) * If JOB = 'E' or 'B', the reciprocal condition numbers of the * selected eigenvalues, stored in consecutive elements of the * array. For a complex conjugate pair of eigenvalues two * consecutive elements of S are set to the same value. Thus * S(j), SEP(j), and the j-th columns of VL and VR all * correspond to the same eigenpair (but not in general the * j-th eigenpair, unless all eigenpairs are selected). * If JOB = 'V', S is not referenced. * * SEP (output) DOUBLE PRECISION array, dimension (MM) * If JOB = 'V' or 'B', the estimated reciprocal condition * numbers of the selected eigenvectors, stored in consecutive * elements of the array. For a complex eigenvector two * consecutive elements of SEP are set to the same value. If * the eigenvalues cannot be reordered to compute SEP(j), SEP(j) * is set to 0; this can only occur when the true value would be * very small anyway. * If JOB = 'E', SEP is not referenced. * * MM (input) INTEGER * The number of elements in the arrays S (if JOB = 'E' or 'B') * and/or SEP (if JOB = 'V' or 'B'). MM >= M. * * M (output) INTEGER * The number of elements of the arrays S and/or SEP actually * used to store the estimated condition numbers. * If HOWMNY = 'A', M is set to N. * * WORK (workspace) DOUBLE PRECISION array, dimension (LDWORK,N+1) * If JOB = 'E', WORK is not referenced. * * LDWORK (input) INTEGER * The leading dimension of the array WORK. * LDWORK >= 1; and if JOB = 'V' or 'B', LDWORK >= N. * * IWORK (workspace) INTEGER array, dimension (N) * If JOB = 'E', IWORK is not referenced. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * Further Details * =============== * * The reciprocal of the condition number of an eigenvalue lambda is * defined as * * S(lambda) = |v'*u| / (norm(u)*norm(v)) * * where u and v are the right and left eigenvectors of T corresponding * to lambda; v' denotes the conjugate-transpose of v, and norm(u) * denotes the Euclidean norm. These reciprocal condition numbers always * lie between zero (very badly conditioned) and one (very well * conditioned). If n = 1, S(lambda) is defined to be 1. * * An approximate error bound for a computed eigenvalue W(i) is given by * * EPS * norm(T) / S(i) * * where EPS is the machine precision. * * The reciprocal of the condition number of the right eigenvector u * corresponding to lambda is defined as follows. Suppose * * T = ( lambda c ) * ( 0 T22 ) * * Then the reciprocal condition number is * * SEP( lambda, T22 ) = sigma-min( T22 - lambda*I ) * * where sigma-min denotes the smallest singular value. We approximate * the smallest singular value by the reciprocal of an estimate of the * one-norm of the inverse of T22 - lambda*I. If n = 1, SEP(1) is * defined to be abs(T(1,1)). * * An approximate error bound for a computed right eigenvector VR(i) * is given by * * EPS * norm(T) / SEP(i) * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0 ) * .. * .. Local Scalars .. LOGICAL PAIR, SOMCON, WANTBH, WANTS, WANTSP INTEGER I, IERR, IFST, ILST, J, K, KASE, KS, N2, NN DOUBLE PRECISION BIGNUM, COND, CS, DELTA, DUMM, EPS, EST, LNRM, $ MU, PROD, PROD1, PROD2, RNRM, SCALE, SMLNUM, SN * .. * .. Local Arrays .. DOUBLE PRECISION DUMMY( 1 ) * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DDOT, DLAMCH, DLAPY2, DNRM2 EXTERNAL LSAME, DDOT, DLAMCH, DLAPY2, DNRM2 * .. * .. External Subroutines .. EXTERNAL DLACON, DLACPY, DLAQTR, DTREXC, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Decode and test the input parameters * WANTBH = LSAME( JOB, 'B' ) WANTS = LSAME( JOB, 'E' ) .OR. WANTBH WANTSP = LSAME( JOB, 'V' ) .OR. WANTBH * SOMCON = LSAME( HOWMNY, 'S' ) * INFO = 0 IF( .NOT.WANTS .AND. .NOT.WANTSP ) THEN INFO = -1 ELSE IF( .NOT.LSAME( HOWMNY, 'A' ) .AND. .NOT.SOMCON ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDT.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( LDVL.LT.1 .OR. ( WANTS .AND. LDVL.LT.N ) ) THEN INFO = -8 ELSE IF( LDVR.LT.1 .OR. ( WANTS .AND. LDVR.LT.N ) ) THEN INFO = -10 ELSE * * Set M to the number of eigenpairs for which condition numbers * are required, and test MM. * IF( SOMCON ) THEN M = 0 PAIR = .FALSE. DO 10 K = 1, N IF( PAIR ) THEN PAIR = .FALSE. ELSE IF( K.LT.N ) THEN IF( T( K+1, K ).EQ.ZERO ) THEN IF( SELECT( K ) ) $ M = M + 1 ELSE PAIR = .TRUE. IF( SELECT( K ) .OR. SELECT( K+1 ) ) $ M = M + 2 END IF ELSE IF( SELECT( N ) ) $ M = M + 1 END IF END IF 10 CONTINUE ELSE M = N END IF * IF( MM.LT.M ) THEN INFO = -13 ELSE IF( LDWORK.LT.1 .OR. ( WANTSP .AND. LDWORK.LT.N ) ) THEN INFO = -16 END IF END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DTRSNA', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( SOMCON ) THEN IF( .NOT.SELECT( 1 ) ) $ RETURN END IF IF( WANTS ) $ S( 1 ) = ONE IF( WANTSP ) $ SEP( 1 ) = ABS( T( 1, 1 ) ) RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) / EPS BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) * KS = 0 PAIR = .FALSE. DO 60 K = 1, N * * Determine whether T(k,k) begins a 1-by-1 or 2-by-2 block. * IF( PAIR ) THEN PAIR = .FALSE. GO TO 60 ELSE IF( K.LT.N ) $ PAIR = T( K+1, K ).NE.ZERO END IF * * Determine whether condition numbers are required for the k-th * eigenpair. * IF( SOMCON ) THEN IF( PAIR ) THEN IF( .NOT.SELECT( K ) .AND. .NOT.SELECT( K+1 ) ) $ GO TO 60 ELSE IF( .NOT.SELECT( K ) ) $ GO TO 60 END IF END IF * KS = KS + 1 * IF( WANTS ) THEN * * Compute the reciprocal condition number of the k-th * eigenvalue. * IF( .NOT.PAIR ) THEN * * Real eigenvalue. * PROD = DDOT( N, VR( 1, KS ), 1, VL( 1, KS ), 1 ) RNRM = DNRM2( N, VR( 1, KS ), 1 ) LNRM = DNRM2( N, VL( 1, KS ), 1 ) S( KS ) = ABS( PROD ) / ( RNRM*LNRM ) ELSE * * Complex eigenvalue. * PROD1 = DDOT( N, VR( 1, KS ), 1, VL( 1, KS ), 1 ) PROD1 = PROD1 + DDOT( N, VR( 1, KS+1 ), 1, VL( 1, KS+1 ), $ 1 ) PROD2 = DDOT( N, VL( 1, KS ), 1, VR( 1, KS+1 ), 1 ) PROD2 = PROD2 - DDOT( N, VL( 1, KS+1 ), 1, VR( 1, KS ), $ 1 ) RNRM = DLAPY2( DNRM2( N, VR( 1, KS ), 1 ), $ DNRM2( N, VR( 1, KS+1 ), 1 ) ) LNRM = DLAPY2( DNRM2( N, VL( 1, KS ), 1 ), $ DNRM2( N, VL( 1, KS+1 ), 1 ) ) COND = DLAPY2( PROD1, PROD2 ) / ( RNRM*LNRM ) S( KS ) = COND S( KS+1 ) = COND END IF END IF * IF( WANTSP ) THEN * * Estimate the reciprocal condition number of the k-th * eigenvector. * * Copy the matrix T to the array WORK and swap the diagonal * block beginning at T(k,k) to the (1,1) position. * CALL DLACPY( 'Full', N, N, T, LDT, WORK, LDWORK ) IFST = K ILST = 1 CALL DTREXC( 'No Q', N, WORK, LDWORK, DUMMY, 1, IFST, ILST, $ WORK( 1, N+1 ), IERR ) * IF( IERR.EQ.1 .OR. IERR.EQ.2 ) THEN * * Could not swap because blocks not well separated * SCALE = ONE EST = BIGNUM ELSE * * Reordering successful * IF( WORK( 2, 1 ).EQ.ZERO ) THEN * * Form C = T22 - lambda*I in WORK(2:N,2:N). * DO 20 I = 2, N WORK( I, I ) = WORK( I, I ) - WORK( 1, 1 ) 20 CONTINUE N2 = 1 NN = N - 1 ELSE * * Triangularize the 2 by 2 block by unitary * transformation U = [ cs i*ss ] * [ i*ss cs ]. * such that the (1,1) position of WORK is complex * eigenvalue lambda with positive imaginary part. (2,2) * position of WORK is the complex eigenvalue lambda * with negative imaginary part. * MU = SQRT( ABS( WORK( 1, 2 ) ) )* $ SQRT( ABS( WORK( 2, 1 ) ) ) DELTA = DLAPY2( MU, WORK( 2, 1 ) ) CS = MU / DELTA SN = -WORK( 2, 1 ) / DELTA * * Form * * C' = WORK(2:N,2:N) + i*[rwork(1) ..... rwork(n-1) ] * [ mu ] * [ .. ] * [ .. ] * [ mu ] * where C' is conjugate transpose of complex matrix C, * and RWORK is stored starting in the N+1-st column of * WORK. * DO 30 J = 3, N WORK( 2, J ) = CS*WORK( 2, J ) WORK( J, J ) = WORK( J, J ) - WORK( 1, 1 ) 30 CONTINUE WORK( 2, 2 ) = ZERO * WORK( 1, N+1 ) = TWO*MU DO 40 I = 2, N - 1 WORK( I, N+1 ) = SN*WORK( 1, I+1 ) 40 CONTINUE N2 = 2 NN = 2*( N-1 ) END IF * * Estimate norm(inv(C')) * EST = ZERO KASE = 0 50 CONTINUE CALL DLACON( NN, WORK( 1, N+2 ), WORK( 1, N+4 ), IWORK, $ EST, KASE ) IF( KASE.NE.0 ) THEN IF( KASE.EQ.1 ) THEN IF( N2.EQ.1 ) THEN * * Real eigenvalue: solve C'*x = scale*c. * CALL DLAQTR( .TRUE., .TRUE., N-1, WORK( 2, 2 ), $ LDWORK, DUMMY, DUMM, SCALE, $ WORK( 1, N+4 ), WORK( 1, N+6 ), $ IERR ) ELSE * * Complex eigenvalue: solve * C'*(p+iq) = scale*(c+id) in real arithmetic. * CALL DLAQTR( .TRUE., .FALSE., N-1, WORK( 2, 2 ), $ LDWORK, WORK( 1, N+1 ), MU, SCALE, $ WORK( 1, N+4 ), WORK( 1, N+6 ), $ IERR ) END IF ELSE IF( N2.EQ.1 ) THEN * * Real eigenvalue: solve C*x = scale*c. * CALL DLAQTR( .FALSE., .TRUE., N-1, WORK( 2, 2 ), $ LDWORK, DUMMY, DUMM, SCALE, $ WORK( 1, N+4 ), WORK( 1, N+6 ), $ IERR ) ELSE * * Complex eigenvalue: solve * C*(p+iq) = scale*(c+id) in real arithmetic. * CALL DLAQTR( .FALSE., .FALSE., N-1, $ WORK( 2, 2 ), LDWORK, $ WORK( 1, N+1 ), MU, SCALE, $ WORK( 1, N+4 ), WORK( 1, N+6 ), $ IERR ) * END IF END IF * GO TO 50 END IF END IF * SEP( KS ) = SCALE / MAX( EST, SMLNUM ) IF( PAIR ) $ SEP( KS+1 ) = SEP( KS ) END IF * IF( PAIR ) $ KS = KS + 1 * 60 CONTINUE RETURN * * End of DTRSNA * END SUBROUTINE DTRSYL( TRANA, TRANB, ISGN, M, N, A, LDA, B, LDB, C, $ LDC, SCALE, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 31, 1993 * * .. Scalar Arguments .. CHARACTER TRANA, TRANB INTEGER INFO, ISGN, LDA, LDB, LDC, M, N DOUBLE PRECISION SCALE * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), B( LDB, * ), C( LDC, * ) * .. * * Purpose * ======= * * DTRSYL solves the real Sylvester matrix equation: * * op(A)*X + X*op(B) = scale*C or * op(A)*X - X*op(B) = scale*C, * * where op(A) = A or A**T, and A and B are both upper quasi- * triangular. A is M-by-M and B is N-by-N; the right hand side C and * the solution X are M-by-N; and scale is an output scale factor, set * <= 1 to avoid overflow in X. * * A and B must be in Schur canonical form (as returned by DHSEQR), that * is, block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; * each 2-by-2 diagonal block has its diagonal elements equal and its * off-diagonal elements of opposite sign. * * Arguments * ========= * * TRANA (input) CHARACTER*1 * Specifies the option op(A): * = 'N': op(A) = A (No transpose) * = 'T': op(A) = A**T (Transpose) * = 'C': op(A) = A**H (Conjugate transpose = Transpose) * * TRANB (input) CHARACTER*1 * Specifies the option op(B): * = 'N': op(B) = B (No transpose) * = 'T': op(B) = B**T (Transpose) * = 'C': op(B) = B**H (Conjugate transpose = Transpose) * * ISGN (input) INTEGER * Specifies the sign in the equation: * = +1: solve op(A)*X + X*op(B) = scale*C * = -1: solve op(A)*X - X*op(B) = scale*C * * M (input) INTEGER * The order of the matrix A, and the number of rows in the * matrices X and C. M >= 0. * * N (input) INTEGER * The order of the matrix B, and the number of columns in the * matrices X and C. N >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,M) * The upper quasi-triangular matrix A, in Schur canonical form. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * B (input) DOUBLE PRECISION array, dimension (LDB,N) * The upper quasi-triangular matrix B, in Schur canonical form. * * LDB (input) INTEGER * The leading dimension of the array B. LDB >= max(1,N). * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N right hand side matrix C. * On exit, C is overwritten by the solution matrix X. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M) * * SCALE (output) DOUBLE PRECISION * The scale factor, scale, set <= 1 to avoid overflow in X. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * = 1: A and B have common or very close eigenvalues; perturbed * values were used to solve the equation (but the matrices * A and B are unchanged). * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL NOTRNA, NOTRNB INTEGER IERR, J, K, K1, K2, KNEXT, L, L1, L2, LNEXT DOUBLE PRECISION A11, BIGNUM, DA11, DB, EPS, SCALOC, SGN, SMIN, $ SMLNUM, SUML, SUMR, XNORM * .. * .. Local Arrays .. DOUBLE PRECISION DUM( 1 ), VEC( 2, 2 ), X( 2, 2 ) * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DDOT, DLAMCH, DLANGE EXTERNAL LSAME, DDOT, DLAMCH, DLANGE * .. * .. External Subroutines .. EXTERNAL DLALN2, DLASY2, DSCAL, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, MAX, MIN * .. * .. Executable Statements .. * * Decode and Test input parameters * NOTRNA = LSAME( TRANA, 'N' ) NOTRNB = LSAME( TRANB, 'N' ) * INFO = 0 IF( .NOT.NOTRNA .AND. .NOT.LSAME( TRANA, 'T' ) .AND. .NOT. $ LSAME( TRANA, 'C' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRNB .AND. .NOT.LSAME( TRANB, 'T' ) .AND. .NOT. $ LSAME( TRANB, 'C' ) ) THEN INFO = -2 ELSE IF( ISGN.NE.1 .AND. ISGN.NE.-1 ) THEN INFO = -3 ELSE IF( M.LT.0 ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -7 ELSE IF( LDB.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -11 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DTRSYL', -INFO ) RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) $ RETURN * * Set constants to control overflow * EPS = DLAMCH( 'P' ) SMLNUM = DLAMCH( 'S' ) BIGNUM = ONE / SMLNUM CALL DLABAD( SMLNUM, BIGNUM ) SMLNUM = SMLNUM*DBLE( M*N ) / EPS BIGNUM = ONE / SMLNUM * SMIN = MAX( SMLNUM, EPS*DLANGE( 'M', M, M, A, LDA, DUM ), $ EPS*DLANGE( 'M', N, N, B, LDB, DUM ) ) * SCALE = ONE SGN = ISGN * IF( NOTRNA .AND. NOTRNB ) THEN * * Solve A*X + ISGN*X*B = scale*C. * * The (K,L)th block of X is determined starting from * bottom-left corner column by column by * * A(K,K)*X(K,L) + ISGN*X(K,L)*B(L,L) = C(K,L) - R(K,L) * * Where * M L-1 * R(K,L) = SUM [A(K,I)*X(I,L)] + ISGN*SUM [X(K,J)*B(J,L)]. * I=K+1 J=1 * * Start column loop (index = L) * L1 (L2) : column index of the first (first) row of X(K,L). * LNEXT = 1 DO 60 L = 1, N IF( L.LT.LNEXT ) $ GO TO 60 IF( L.EQ.N ) THEN L1 = L L2 = L ELSE IF( B( L+1, L ).NE.ZERO ) THEN L1 = L L2 = L + 1 LNEXT = L + 2 ELSE L1 = L L2 = L LNEXT = L + 1 END IF END IF * * Start row loop (index = K) * K1 (K2): row index of the first (last) row of X(K,L). * KNEXT = M DO 50 K = M, 1, -1 IF( K.GT.KNEXT ) $ GO TO 50 IF( K.EQ.1 ) THEN K1 = K K2 = K ELSE IF( A( K, K-1 ).NE.ZERO ) THEN K1 = K - 1 K2 = K KNEXT = K - 2 ELSE K1 = K K2 = K KNEXT = K - 1 END IF END IF * IF( L1.EQ.L2 .AND. K1.EQ.K2 ) THEN SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) SCALOC = ONE * A11 = A( K1, K1 ) + SGN*B( L1, L1 ) DA11 = ABS( A11 ) IF( DA11.LE.SMIN ) THEN A11 = SMIN DA11 = SMIN INFO = 1 END IF DB = ABS( VEC( 1, 1 ) ) IF( DA11.LT.ONE .AND. DB.GT.ONE ) THEN IF( DB.GT.BIGNUM*DA11 ) $ SCALOC = ONE / DB END IF X( 1, 1 ) = ( VEC( 1, 1 )*SCALOC ) / A11 * IF( SCALOC.NE.ONE ) THEN DO 10 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 10 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) * ELSE IF( L1.EQ.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, A( K1, K1 ), $ LDA, ONE, ONE, VEC, 2, -SGN*B( L1, L1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 20 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 20 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K2, L1 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.EQ.K2 ) THEN * SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = SGN*( C( K1, L1 )-( SUML+SGN*SUMR ) ) * SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L2 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 2, 1 ) = SGN*( C( K1, L2 )-( SUML+SGN*SUMR ) ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, B( L1, L1 ), $ LDB, ONE, ONE, VEC, 2, -SGN*A( K1, K1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 30 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 30 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L2 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 1, 2 ) = C( K1, L2 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L2 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 2, 2 ) = C( K2, L2 ) - ( SUML+SGN*SUMR ) * CALL DLASY2( .FALSE., .FALSE., ISGN, 2, 2, $ A( K1, K1 ), LDA, B( L1, L1 ), LDB, VEC, $ 2, SCALOC, X, 2, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 40 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 40 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 1, 2 ) C( K2, L1 ) = X( 2, 1 ) C( K2, L2 ) = X( 2, 2 ) END IF * 50 CONTINUE * 60 CONTINUE * ELSE IF( .NOT.NOTRNA .AND. NOTRNB ) THEN * * Solve A' *X + ISGN*X*B = scale*C. * * The (K,L)th block of X is determined starting from * upper-left corner column by column by * * A(K,K)'*X(K,L) + ISGN*X(K,L)*B(L,L) = C(K,L) - R(K,L) * * Where * K-1 L-1 * R(K,L) = SUM [A(I,K)'*X(I,L)] +ISGN*SUM [X(K,J)*B(J,L)] * I=1 J=1 * * Start column loop (index = L) * L1 (L2): column index of the first (last) row of X(K,L) * LNEXT = 1 DO 120 L = 1, N IF( L.LT.LNEXT ) $ GO TO 120 IF( L.EQ.N ) THEN L1 = L L2 = L ELSE IF( B( L+1, L ).NE.ZERO ) THEN L1 = L L2 = L + 1 LNEXT = L + 2 ELSE L1 = L L2 = L LNEXT = L + 1 END IF END IF * * Start row loop (index = K) * K1 (K2): row index of the first (last) row of X(K,L) * KNEXT = 1 DO 110 K = 1, M IF( K.LT.KNEXT ) $ GO TO 110 IF( K.EQ.M ) THEN K1 = K K2 = K ELSE IF( A( K+1, K ).NE.ZERO ) THEN K1 = K K2 = K + 1 KNEXT = K + 2 ELSE K1 = K K2 = K KNEXT = K + 1 END IF END IF * IF( L1.EQ.L2 .AND. K1.EQ.K2 ) THEN SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) SCALOC = ONE * A11 = A( K1, K1 ) + SGN*B( L1, L1 ) DA11 = ABS( A11 ) IF( DA11.LE.SMIN ) THEN A11 = SMIN DA11 = SMIN INFO = 1 END IF DB = ABS( VEC( 1, 1 ) ) IF( DA11.LT.ONE .AND. DB.GT.ONE ) THEN IF( DB.GT.BIGNUM*DA11 ) $ SCALOC = ONE / DB END IF X( 1, 1 ) = ( VEC( 1, 1 )*SCALOC ) / A11 * IF( SCALOC.NE.ONE ) THEN DO 70 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 70 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) * ELSE IF( L1.EQ.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, A( K1, K1 ), $ LDA, ONE, ONE, VEC, 2, -SGN*B( L1, L1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 80 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 80 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K2, L1 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.EQ.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = SGN*( C( K1, L1 )-( SUML+SGN*SUMR ) ) * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 2, 1 ) = SGN*( C( K1, L2 )-( SUML+SGN*SUMR ) ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, B( L1, L1 ), $ LDB, ONE, ONE, VEC, 2, -SGN*A( K1, K1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 90 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 90 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( L1-1, C( K1, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 1, 2 ) = C( K1, L2 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L1 ), 1 ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( L1-1, C( K2, 1 ), LDC, B( 1, L2 ), 1 ) VEC( 2, 2 ) = C( K2, L2 ) - ( SUML+SGN*SUMR ) * CALL DLASY2( .TRUE., .FALSE., ISGN, 2, 2, A( K1, K1 ), $ LDA, B( L1, L1 ), LDB, VEC, 2, SCALOC, X, $ 2, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 100 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 100 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 1, 2 ) C( K2, L1 ) = X( 2, 1 ) C( K2, L2 ) = X( 2, 2 ) END IF * 110 CONTINUE 120 CONTINUE * ELSE IF( .NOT.NOTRNA .AND. .NOT.NOTRNB ) THEN * * Solve A'*X + ISGN*X*B' = scale*C. * * The (K,L)th block of X is determined starting from * top-right corner column by column by * * A(K,K)'*X(K,L) + ISGN*X(K,L)*B(L,L)' = C(K,L) - R(K,L) * * Where * K-1 N * R(K,L) = SUM [A(I,K)'*X(I,L)] + ISGN*SUM [X(K,J)*B(L,J)']. * I=1 J=L+1 * * Start column loop (index = L) * L1 (L2): column index of the first (last) row of X(K,L) * LNEXT = N DO 180 L = N, 1, -1 IF( L.GT.LNEXT ) $ GO TO 180 IF( L.EQ.1 ) THEN L1 = L L2 = L ELSE IF( B( L, L-1 ).NE.ZERO ) THEN L1 = L - 1 L2 = L LNEXT = L - 2 ELSE L1 = L L2 = L LNEXT = L - 1 END IF END IF * * Start row loop (index = K) * K1 (K2): row index of the first (last) row of X(K,L) * KNEXT = 1 DO 170 K = 1, M IF( K.LT.KNEXT ) $ GO TO 170 IF( K.EQ.M ) THEN K1 = K K2 = K ELSE IF( A( K+1, K ).NE.ZERO ) THEN K1 = K K2 = K + 1 KNEXT = K + 2 ELSE K1 = K K2 = K KNEXT = K + 1 END IF END IF * IF( L1.EQ.L2 .AND. K1.EQ.K2 ) THEN SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L1, C( K1, MIN( L1+1, N ) ), LDC, $ B( L1, MIN( L1+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) SCALOC = ONE * A11 = A( K1, K1 ) + SGN*B( L1, L1 ) DA11 = ABS( A11 ) IF( DA11.LE.SMIN ) THEN A11 = SMIN DA11 = SMIN INFO = 1 END IF DB = ABS( VEC( 1, 1 ) ) IF( DA11.LT.ONE .AND. DB.GT.ONE ) THEN IF( DB.GT.BIGNUM*DA11 ) $ SCALOC = ONE / DB END IF X( 1, 1 ) = ( VEC( 1, 1 )*SCALOC ) / A11 * IF( SCALOC.NE.ONE ) THEN DO 130 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 130 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) * ELSE IF( L1.EQ.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * CALL DLALN2( .TRUE., 2, 1, SMIN, ONE, A( K1, K1 ), $ LDA, ONE, ONE, VEC, 2, -SGN*B( L1, L1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 140 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 140 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K2, L1 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.EQ.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = SGN*( C( K1, L1 )-( SUML+SGN*SUMR ) ) * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = SGN*( C( K1, L2 )-( SUML+SGN*SUMR ) ) * CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, B( L1, L1 ), $ LDB, ONE, ONE, VEC, 2, -SGN*A( K1, K1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 150 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 150 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K1 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 1, 2 ) = C( K1, L2 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L1 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( K1-1, A( 1, K2 ), 1, C( 1, L2 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 2, 2 ) = C( K2, L2 ) - ( SUML+SGN*SUMR ) * CALL DLASY2( .TRUE., .TRUE., ISGN, 2, 2, A( K1, K1 ), $ LDA, B( L1, L1 ), LDB, VEC, 2, SCALOC, X, $ 2, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 160 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 160 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 1, 2 ) C( K2, L1 ) = X( 2, 1 ) C( K2, L2 ) = X( 2, 2 ) END IF * 170 CONTINUE 180 CONTINUE * ELSE IF( NOTRNA .AND. .NOT.NOTRNB ) THEN * * Solve A*X + ISGN*X*B' = scale*C. * * The (K,L)th block of X is determined starting from * bottom-right corner column by column by * * A(K,K)*X(K,L) + ISGN*X(K,L)*B(L,L)' = C(K,L) - R(K,L) * * Where * M N * R(K,L) = SUM [A(K,I)*X(I,L)] + ISGN*SUM [X(K,J)*B(L,J)']. * I=K+1 J=L+1 * * Start column loop (index = L) * L1 (L2): column index of the first (last) row of X(K,L) * LNEXT = N DO 240 L = N, 1, -1 IF( L.GT.LNEXT ) $ GO TO 240 IF( L.EQ.1 ) THEN L1 = L L2 = L ELSE IF( B( L, L-1 ).NE.ZERO ) THEN L1 = L - 1 L2 = L LNEXT = L - 2 ELSE L1 = L L2 = L LNEXT = L - 1 END IF END IF * * Start row loop (index = K) * K1 (K2): row index of the first (last) row of X(K,L) * KNEXT = M DO 230 K = M, 1, -1 IF( K.GT.KNEXT ) $ GO TO 230 IF( K.EQ.1 ) THEN K1 = K K2 = K ELSE IF( A( K, K-1 ).NE.ZERO ) THEN K1 = K - 1 K2 = K KNEXT = K - 2 ELSE K1 = K K2 = K KNEXT = K - 1 END IF END IF * IF( L1.EQ.L2 .AND. K1.EQ.K2 ) THEN SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L1 ), 1 ) SUMR = DDOT( N-L1, C( K1, MIN( L1+1, N ) ), LDC, $ B( L1, MIN( L1+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) SCALOC = ONE * A11 = A( K1, K1 ) + SGN*B( L1, L1 ) DA11 = ABS( A11 ) IF( DA11.LE.SMIN ) THEN A11 = SMIN DA11 = SMIN INFO = 1 END IF DB = ABS( VEC( 1, 1 ) ) IF( DA11.LT.ONE .AND. DB.GT.ONE ) THEN IF( DB.GT.BIGNUM*DA11 ) $ SCALOC = ONE / DB END IF X( 1, 1 ) = ( VEC( 1, 1 )*SCALOC ) / A11 * IF( SCALOC.NE.ONE ) THEN DO 190 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 190 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) * ELSE IF( L1.EQ.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, A( K1, K1 ), $ LDA, ONE, ONE, VEC, 2, -SGN*B( L1, L1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 200 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 200 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K2, L1 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.EQ.K2 ) THEN * SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = SGN*( C( K1, L1 )-( SUML+SGN*SUMR ) ) * SUML = DDOT( M-K1, A( K1, MIN( K1+1, M ) ), LDA, $ C( MIN( K1+1, M ), L2 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = SGN*( C( K1, L2 )-( SUML+SGN*SUMR ) ) * CALL DLALN2( .FALSE., 2, 1, SMIN, ONE, B( L1, L1 ), $ LDB, ONE, ONE, VEC, 2, -SGN*A( K1, K1 ), $ ZERO, X, 2, SCALOC, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 210 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 210 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 2, 1 ) * ELSE IF( L1.NE.L2 .AND. K1.NE.K2 ) THEN * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 1, 1 ) = C( K1, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K1, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L2 ), 1 ) SUMR = DDOT( N-L2, C( K1, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 1, 2 ) = C( K1, L2 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L1 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L1, MIN( L2+1, N ) ), LDB ) VEC( 2, 1 ) = C( K2, L1 ) - ( SUML+SGN*SUMR ) * SUML = DDOT( M-K2, A( K2, MIN( K2+1, M ) ), LDA, $ C( MIN( K2+1, M ), L2 ), 1 ) SUMR = DDOT( N-L2, C( K2, MIN( L2+1, N ) ), LDC, $ B( L2, MIN( L2+1, N ) ), LDB ) VEC( 2, 2 ) = C( K2, L2 ) - ( SUML+SGN*SUMR ) * CALL DLASY2( .FALSE., .TRUE., ISGN, 2, 2, A( K1, K1 ), $ LDA, B( L1, L1 ), LDB, VEC, 2, SCALOC, X, $ 2, XNORM, IERR ) IF( IERR.NE.0 ) $ INFO = 1 * IF( SCALOC.NE.ONE ) THEN DO 220 J = 1, N CALL DSCAL( M, SCALOC, C( 1, J ), 1 ) 220 CONTINUE SCALE = SCALE*SCALOC END IF C( K1, L1 ) = X( 1, 1 ) C( K1, L2 ) = X( 1, 2 ) C( K2, L1 ) = X( 2, 1 ) C( K2, L2 ) = X( 2, 2 ) END IF * 230 CONTINUE 240 CONTINUE * END IF * RETURN * * End of DTRSYL * END INTEGER FUNCTION IEEECK( ISPEC, ZERO, ONE ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1998 * * .. Scalar Arguments .. INTEGER ISPEC REAL ONE, ZERO * .. * * Purpose * ======= * * IEEECK is called from the ILAENV to verify that Infinity and * possibly NaN arithmetic is safe (i.e. will not trap). * * Arguments * ========= * * ISPEC (input) INTEGER * Specifies whether to test just for inifinity arithmetic * or whether to test for infinity and NaN arithmetic. * = 0: Verify infinity arithmetic only. * = 1: Verify infinity and NaN arithmetic. * * ZERO (input) REAL * Must contain the value 0.0 * This is passed to prevent the compiler from optimizing * away this code. * * ONE (input) REAL * Must contain the value 1.0 * This is passed to prevent the compiler from optimizing * away this code. * * RETURN VALUE: INTEGER * = 0: Arithmetic failed to produce the correct answers * = 1: Arithmetic produced the correct answers * * .. Local Scalars .. REAL NAN1, NAN2, NAN3, NAN4, NAN5, NAN6, NEGINF, $ NEGZRO, NEWZRO, POSINF * .. * .. Executable Statements .. IEEECK = 1 * POSINF = ONE / ZERO IF( POSINF.LE.ONE ) THEN IEEECK = 0 RETURN END IF * NEGINF = -ONE / ZERO IF( NEGINF.GE.ZERO ) THEN IEEECK = 0 RETURN END IF * NEGZRO = ONE / ( NEGINF+ONE ) IF( NEGZRO.NE.ZERO ) THEN IEEECK = 0 RETURN END IF * NEGINF = ONE / NEGZRO IF( NEGINF.GE.ZERO ) THEN IEEECK = 0 RETURN END IF * NEWZRO = NEGZRO + ZERO IF( NEWZRO.NE.ZERO ) THEN IEEECK = 0 RETURN END IF * POSINF = ONE / NEWZRO IF( POSINF.LE.ONE ) THEN IEEECK = 0 RETURN END IF * NEGINF = NEGINF*POSINF IF( NEGINF.GE.ZERO ) THEN IEEECK = 0 RETURN END IF * POSINF = POSINF*POSINF IF( POSINF.LE.ONE ) THEN IEEECK = 0 RETURN END IF * * * * * Return if we were only asked to check infinity arithmetic * IF( ISPEC.EQ.0 ) $ RETURN * NAN1 = POSINF + NEGINF * NAN2 = POSINF / NEGINF * NAN3 = POSINF / POSINF * NAN4 = POSINF*ZERO * NAN5 = NEGINF*NEGZRO * NAN6 = NAN5*0.0 * IF( NAN1.EQ.NAN1 ) THEN IEEECK = 0 RETURN END IF * IF( NAN2.EQ.NAN2 ) THEN IEEECK = 0 RETURN END IF * IF( NAN3.EQ.NAN3 ) THEN IEEECK = 0 RETURN END IF * IF( NAN4.EQ.NAN4 ) THEN IEEECK = 0 RETURN END IF * IF( NAN5.EQ.NAN5 ) THEN IEEECK = 0 RETURN END IF * IF( NAN6.EQ.NAN6 ) THEN IEEECK = 0 RETURN END IF * RETURN END INTEGER FUNCTION ILAENV( ISPEC, NAME, OPTS, N1, N2, N3, $ N4 ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER*( * ) NAME, OPTS INTEGER ISPEC, N1, N2, N3, N4 * .. * * Purpose * ======= * * ILAENV is called from the LAPACK routines to choose problem-dependent * parameters for the local environment. See ISPEC for a description of * the parameters. * * This version provides a set of parameters which should give good, * but not optimal, performance on many of the currently available * computers. Users are encouraged to modify this subroutine to set * the tuning parameters for their particular machine using the option * and problem size information in the arguments. * * This routine will not function correctly if it is converted to all * lower case. Converting it to all upper case is allowed. * * Arguments * ========= * * ISPEC (input) INTEGER * Specifies the parameter to be returned as the value of * ILAENV. * = 1: the optimal blocksize; if this value is 1, an unblocked * algorithm will give the best performance. * = 2: the minimum block size for which the block routine * should be used; if the usable block size is less than * this value, an unblocked routine should be used. * = 3: the crossover point (in a block routine, for N less * than this value, an unblocked routine should be used) * = 4: the number of shifts, used in the nonsymmetric * eigenvalue routines * = 5: the minimum column dimension for blocking to be used; * rectangular blocks must have dimension at least k by m, * where k is given by ILAENV(2,...) and m by ILAENV(5,...) * = 6: the crossover point for the SVD (when reducing an m by n * matrix to bidiagonal form, if max(m,n)/min(m,n) exceeds * this value, a QR factorization is used first to reduce * the matrix to a triangular form.) * = 7: the number of processors * = 8: the crossover point for the multishift QR and QZ methods * for nonsymmetric eigenvalue problems. * = 9: maximum size of the subproblems at the bottom of the * computation tree in the divide-and-conquer algorithm * (used by xGELSD and xGESDD) * =10: ieee NaN arithmetic can be trusted not to trap * =11: infinity arithmetic can be trusted not to trap * * NAME (input) CHARACTER*(*) * The name of the calling subroutine, in either upper case or * lower case. * * OPTS (input) CHARACTER*(*) * The character options to the subroutine NAME, concatenated * into a single character string. For example, UPLO = 'U', * TRANS = 'T', and DIAG = 'N' for a triangular routine would * be specified as OPTS = 'UTN'. * * N1 (input) INTEGER * N2 (input) INTEGER * N3 (input) INTEGER * N4 (input) INTEGER * Problem dimensions for the subroutine NAME; these may not all * be required. * * (ILAENV) (output) INTEGER * >= 0: the value of the parameter specified by ISPEC * < 0: if ILAENV = -k, the k-th argument had an illegal value. * * Further Details * =============== * * The following conventions have been used when calling ILAENV from the * LAPACK routines: * 1) OPTS is a concatenation of all of the character options to * subroutine NAME, in the same order that they appear in the * argument list for NAME, even if they are not used in determining * the value of the parameter specified by ISPEC. * 2) The problem dimensions N1, N2, N3, N4 are specified in the order * that they appear in the argument list for NAME. N1 is used * first, N2 second, and so on, and unused problem dimensions are * passed a value of -1. * 3) The parameter value returned by ILAENV is checked for validity in * the calling subroutine. For example, ILAENV is used to retrieve * the optimal blocksize for STRTRI as follows: * * NB = ILAENV( 1, 'STRTRI', UPLO // DIAG, N, -1, -1, -1 ) * IF( NB.LE.1 ) NB = MAX( 1, N ) * * ===================================================================== * * .. Local Scalars .. LOGICAL CNAME, SNAME CHARACTER*1 C1 CHARACTER*2 C2, C4 CHARACTER*3 C3 CHARACTER*6 SUBNAM INTEGER I, IC, IZ, NB, NBMIN, NX * .. * .. Intrinsic Functions .. INTRINSIC CHAR, ICHAR, INT, MIN, REAL * .. * .. External Functions .. INTEGER IEEECK EXTERNAL IEEECK * .. * .. Executable Statements .. * GO TO ( 100, 100, 100, 400, 500, 600, 700, 800, 900, 1000, $ 1100 ) ISPEC * * Invalid value for ISPEC * ILAENV = -1 RETURN * 100 CONTINUE * * Convert NAME to upper case if the first character is lower case. * ILAENV = 1 SUBNAM = NAME IC = ICHAR( SUBNAM( 1:1 ) ) IZ = ICHAR( 'Z' ) IF( IZ.EQ.90 .OR. IZ.EQ.122 ) THEN * * ASCII character set * IF( IC.GE.97 .AND. IC.LE.122 ) THEN SUBNAM( 1:1 ) = CHAR( IC-32 ) DO 10 I = 2, 6 IC = ICHAR( SUBNAM( I:I ) ) IF( IC.GE.97 .AND. IC.LE.122 ) $ SUBNAM( I:I ) = CHAR( IC-32 ) 10 CONTINUE END IF * ELSE IF( IZ.EQ.233 .OR. IZ.EQ.169 ) THEN * * EBCDIC character set * IF( ( IC.GE.129 .AND. IC.LE.137 ) .OR. $ ( IC.GE.145 .AND. IC.LE.153 ) .OR. $ ( IC.GE.162 .AND. IC.LE.169 ) ) THEN SUBNAM( 1:1 ) = CHAR( IC+64 ) DO 20 I = 2, 6 IC = ICHAR( SUBNAM( I:I ) ) IF( ( IC.GE.129 .AND. IC.LE.137 ) .OR. $ ( IC.GE.145 .AND. IC.LE.153 ) .OR. $ ( IC.GE.162 .AND. IC.LE.169 ) ) $ SUBNAM( I:I ) = CHAR( IC+64 ) 20 CONTINUE END IF * ELSE IF( IZ.EQ.218 .OR. IZ.EQ.250 ) THEN * * Prime machines: ASCII+128 * IF( IC.GE.225 .AND. IC.LE.250 ) THEN SUBNAM( 1:1 ) = CHAR( IC-32 ) DO 30 I = 2, 6 IC = ICHAR( SUBNAM( I:I ) ) IF( IC.GE.225 .AND. IC.LE.250 ) $ SUBNAM( I:I ) = CHAR( IC-32 ) 30 CONTINUE END IF END IF * C1 = SUBNAM( 1:1 ) SNAME = C1.EQ.'S' .OR. C1.EQ.'D' CNAME = C1.EQ.'C' .OR. C1.EQ.'Z' IF( .NOT.( CNAME .OR. SNAME ) ) $ RETURN C2 = SUBNAM( 2:3 ) C3 = SUBNAM( 4:6 ) C4 = C3( 2:3 ) * GO TO ( 110, 200, 300 ) ISPEC * 110 CONTINUE * * ISPEC = 1: block size * * In these examples, separate code is provided for setting NB for * real and complex. We assume that NB will take the same value in * single or double precision. * NB = 1 * IF( C2.EQ.'GE' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF ELSE IF( C3.EQ.'QRF' .OR. C3.EQ.'RQF' .OR. C3.EQ.'LQF' .OR. $ C3.EQ.'QLF' ) THEN IF( SNAME ) THEN NB = 32 ELSE NB = 32 END IF ELSE IF( C3.EQ.'HRD' ) THEN IF( SNAME ) THEN NB = 32 ELSE NB = 32 END IF ELSE IF( C3.EQ.'BRD' ) THEN IF( SNAME ) THEN NB = 32 ELSE NB = 32 END IF ELSE IF( C3.EQ.'TRI' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF END IF ELSE IF( C2.EQ.'PO' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF END IF ELSE IF( C2.EQ.'SY' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF ELSE IF( SNAME .AND. C3.EQ.'TRD' ) THEN NB = 32 ELSE IF( SNAME .AND. C3.EQ.'GST' ) THEN NB = 64 END IF ELSE IF( CNAME .AND. C2.EQ.'HE' ) THEN IF( C3.EQ.'TRF' ) THEN NB = 64 ELSE IF( C3.EQ.'TRD' ) THEN NB = 32 ELSE IF( C3.EQ.'GST' ) THEN NB = 64 END IF ELSE IF( SNAME .AND. C2.EQ.'OR' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NB = 32 END IF ELSE IF( C3( 1:1 ).EQ.'M' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NB = 32 END IF END IF ELSE IF( CNAME .AND. C2.EQ.'UN' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NB = 32 END IF ELSE IF( C3( 1:1 ).EQ.'M' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NB = 32 END IF END IF ELSE IF( C2.EQ.'GB' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN IF( N4.LE.64 ) THEN NB = 1 ELSE NB = 32 END IF ELSE IF( N4.LE.64 ) THEN NB = 1 ELSE NB = 32 END IF END IF END IF ELSE IF( C2.EQ.'PB' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN IF( N2.LE.64 ) THEN NB = 1 ELSE NB = 32 END IF ELSE IF( N2.LE.64 ) THEN NB = 1 ELSE NB = 32 END IF END IF END IF ELSE IF( C2.EQ.'TR' ) THEN IF( C3.EQ.'TRI' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF END IF ELSE IF( C2.EQ.'LA' ) THEN IF( C3.EQ.'UUM' ) THEN IF( SNAME ) THEN NB = 64 ELSE NB = 64 END IF END IF ELSE IF( SNAME .AND. C2.EQ.'ST' ) THEN IF( C3.EQ.'EBZ' ) THEN NB = 1 END IF END IF ILAENV = NB RETURN * 200 CONTINUE * * ISPEC = 2: minimum block size * NBMIN = 2 IF( C2.EQ.'GE' ) THEN IF( C3.EQ.'QRF' .OR. C3.EQ.'RQF' .OR. C3.EQ.'LQF' .OR. $ C3.EQ.'QLF' ) THEN IF( SNAME ) THEN NBMIN = 2 ELSE NBMIN = 2 END IF ELSE IF( C3.EQ.'HRD' ) THEN IF( SNAME ) THEN NBMIN = 2 ELSE NBMIN = 2 END IF ELSE IF( C3.EQ.'BRD' ) THEN IF( SNAME ) THEN NBMIN = 2 ELSE NBMIN = 2 END IF ELSE IF( C3.EQ.'TRI' ) THEN IF( SNAME ) THEN NBMIN = 2 ELSE NBMIN = 2 END IF END IF ELSE IF( C2.EQ.'SY' ) THEN IF( C3.EQ.'TRF' ) THEN IF( SNAME ) THEN NBMIN = 8 ELSE NBMIN = 8 END IF ELSE IF( SNAME .AND. C3.EQ.'TRD' ) THEN NBMIN = 2 END IF ELSE IF( CNAME .AND. C2.EQ.'HE' ) THEN IF( C3.EQ.'TRD' ) THEN NBMIN = 2 END IF ELSE IF( SNAME .AND. C2.EQ.'OR' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NBMIN = 2 END IF ELSE IF( C3( 1:1 ).EQ.'M' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NBMIN = 2 END IF END IF ELSE IF( CNAME .AND. C2.EQ.'UN' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NBMIN = 2 END IF ELSE IF( C3( 1:1 ).EQ.'M' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NBMIN = 2 END IF END IF END IF ILAENV = NBMIN RETURN * 300 CONTINUE * * ISPEC = 3: crossover point * NX = 0 IF( C2.EQ.'GE' ) THEN IF( C3.EQ.'QRF' .OR. C3.EQ.'RQF' .OR. C3.EQ.'LQF' .OR. $ C3.EQ.'QLF' ) THEN IF( SNAME ) THEN NX = 128 ELSE NX = 128 END IF ELSE IF( C3.EQ.'HRD' ) THEN IF( SNAME ) THEN NX = 128 ELSE NX = 128 END IF ELSE IF( C3.EQ.'BRD' ) THEN IF( SNAME ) THEN NX = 128 ELSE NX = 128 END IF END IF ELSE IF( C2.EQ.'SY' ) THEN IF( SNAME .AND. C3.EQ.'TRD' ) THEN NX = 32 END IF ELSE IF( CNAME .AND. C2.EQ.'HE' ) THEN IF( C3.EQ.'TRD' ) THEN NX = 32 END IF ELSE IF( SNAME .AND. C2.EQ.'OR' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NX = 128 END IF END IF ELSE IF( CNAME .AND. C2.EQ.'UN' ) THEN IF( C3( 1:1 ).EQ.'G' ) THEN IF( C4.EQ.'QR' .OR. C4.EQ.'RQ' .OR. C4.EQ.'LQ' .OR. $ C4.EQ.'QL' .OR. C4.EQ.'HR' .OR. C4.EQ.'TR' .OR. $ C4.EQ.'BR' ) THEN NX = 128 END IF END IF END IF ILAENV = NX RETURN * 400 CONTINUE * * ISPEC = 4: number of shifts (used by xHSEQR) * ILAENV = 6 RETURN * 500 CONTINUE * * ISPEC = 5: minimum column dimension (not used) * ILAENV = 2 RETURN * 600 CONTINUE * * ISPEC = 6: crossover point for SVD (used by xGELSS and xGESVD) * ILAENV = INT( REAL( MIN( N1, N2 ) )*1.6E0 ) RETURN * 700 CONTINUE * * ISPEC = 7: number of processors (not used) * ILAENV = 1 RETURN * 800 CONTINUE * * ISPEC = 8: crossover point for multishift (used by xHSEQR) * ILAENV = 50 RETURN * 900 CONTINUE * * ISPEC = 9: maximum size of the subproblems at the bottom of the * computation tree in the divide-and-conquer algorithm * (used by xGELSD and xGESDD) * ILAENV = 25 RETURN * 1000 CONTINUE * * ISPEC = 10: ieee NaN arithmetic can be trusted not to trap * C ILAENV = 0 ILAENV = 1 IF( ILAENV.EQ.1 ) THEN ILAENV = IEEECK( 0, 0.0, 1.0 ) END IF RETURN * 1100 CONTINUE * * ISPEC = 11: infinity arithmetic can be trusted not to trap * C ILAENV = 0 ILAENV = 1 IF( ILAENV.EQ.1 ) THEN ILAENV = IEEECK( 1, 0.0, 1.0 ) END IF RETURN * * End of ILAENV * END SUBROUTINE DGESDD( JOBZ, M, N, A, LDA, S, U, LDU, VT, LDVT, WORK, $ LWORK, IWORK, INFO ) * * -- LAPACK driver routine (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 JOBZ INTEGER INFO, LDA, LDU, LDVT, LWORK, M, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION A( LDA, * ), S( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DGESDD computes the singular value decomposition (SVD) of a real * M-by-N matrix A, optionally computing the left and right singular * vectors. If singular vectors are desired, it uses a * divide-and-conquer algorithm. * * The SVD is written * * A = U * SIGMA * transpose(V) * * where SIGMA is an M-by-N matrix which is zero except for its * min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and * V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA * are the singular values of A; they are real and non-negative, and * are returned in descending order. The first min(m,n) columns of * U and V are the left and right singular vectors of A. * * Note that the routine returns VT = V**T, not V. * * The divide and conquer algorithm 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. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * Specifies options for computing all or part of the matrix U: * = 'A': all M columns of U and all N rows of V**T are * returned in the arrays U and VT; * = 'S': the first min(M,N) columns of U and the first * min(M,N) rows of V**T are returned in the arrays U * and VT; * = 'O': If M >= N, the first N columns of U are overwritten * on the array A and all rows of V**T are returned in * the array VT; * otherwise, all columns of U are returned in the * array U and the first M rows of V**T are overwritten * in the array VT; * = 'N': no columns of U or rows of V**T are computed. * * 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. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA,N) * On entry, the M-by-N matrix A. * On exit, * if JOBZ = 'O', A is overwritten with the first N columns * of U (the left singular vectors, stored * columnwise) if M >= N; * A is overwritten with the first M rows * of V**T (the right singular vectors, stored * rowwise) otherwise. * if JOBZ .ne. 'O', the contents of A are destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * S (output) DOUBLE PRECISION array, dimension (min(M,N)) * The singular values of A, sorted so that S(i) >= S(i+1). * * U (output) DOUBLE PRECISION array, dimension (LDU,UCOL) * UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N; * UCOL = min(M,N) if JOBZ = 'S'. * If JOBZ = 'A' or JOBZ = 'O' and M < N, U contains the M-by-M * orthogonal matrix U; * if JOBZ = 'S', U contains the first min(M,N) columns of U * (the left singular vectors, stored columnwise); * if JOBZ = 'O' and M >= N, or JOBZ = 'N', U is not referenced. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= 1; if * JOBZ = 'S' or 'A' or JOBZ = 'O' and M < N, LDU >= M. * * VT (output) DOUBLE PRECISION array, dimension (LDVT,N) * If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the * N-by-N orthogonal matrix V**T; * if JOBZ = 'S', VT contains the first min(M,N) rows of * V**T (the right singular vectors, stored rowwise); * if JOBZ = 'O' and M < N, or JOBZ = 'N', VT is not referenced. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= 1; if * JOBZ = 'A' or JOBZ = 'O' and M >= N, LDVT >= N; * if JOBZ = 'S', LDVT >= min(M,N). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK; * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= 1. * If JOBZ = 'N', * LWORK >= 3*min(M,N) + max(max(M,N),6*min(M,N)). * If JOBZ = 'O', * LWORK >= 3*min(M,N)*min(M,N) + * max(max(M,N),5*min(M,N)*min(M,N)+4*min(M,N)). * If JOBZ = 'S' or 'A' * LWORK >= 3*min(M,N)*min(M,N) + * max(max(M,N),4*min(M,N)*min(M,N)+4*min(M,N)). * For good performance, LWORK should generally be larger. * If LWORK < 0 but other input arguments are legal, WORK(1) * returns the optimal LWORK. * * IWORK (workspace) INTEGER array, dimension (8*min(M,N)) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: DBDSDC did not converge, updating process 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 PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL LQUERY, WNTQA, WNTQAS, WNTQN, WNTQO, WNTQS INTEGER BDSPAC, BLK, CHUNK, I, IE, IERR, IL, $ IR, ISCL, ITAU, ITAUP, ITAUQ, IU, IVT, LDWKVT, $ LDWRKL, LDWRKR, LDWRKU, MAXWRK, MINMN, MINWRK, $ MNTHR, NWORK, WRKBL DOUBLE PRECISION ANRM, BIGNUM, EPS, SMLNUM * .. * .. Local Arrays .. INTEGER IDUM( 1 ) DOUBLE PRECISION DUM( 1 ) * .. * .. External Subroutines .. EXTERNAL DBDSDC, DGEBRD, DGELQF, DGEMM, DGEQRF, DLACPY, $ DLASCL, DLASET, DORGBR, DORGLQ, DORGQR, DORMBR, $ XERBLA * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANGE EXTERNAL DLAMCH, DLANGE, ILAENV, LSAME * .. * .. Intrinsic Functions .. INTRINSIC DBLE, INT, MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 MINMN = MIN( M, N ) MNTHR = INT( MINMN*11.0D0 / 6.0D0 ) WNTQA = LSAME( JOBZ, 'A' ) WNTQS = LSAME( JOBZ, 'S' ) WNTQAS = WNTQA .OR. WNTQS WNTQO = LSAME( JOBZ, 'O' ) WNTQN = LSAME( JOBZ, 'N' ) MINWRK = 1 MAXWRK = 1 LQUERY = ( LWORK.EQ.-1 ) * IF( .NOT.( WNTQA .OR. WNTQS .OR. WNTQO .OR. WNTQN ) ) THEN INFO = -1 ELSE IF( M.LT.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( LDA.LT.MAX( 1, M ) ) THEN INFO = -5 ELSE IF( LDU.LT.1 .OR. ( WNTQAS .AND. LDU.LT.M ) .OR. $ ( WNTQO .AND. M.LT.N .AND. LDU.LT.M ) ) THEN INFO = -8 ELSE IF( LDVT.LT.1 .OR. ( WNTQA .AND. LDVT.LT.N ) .OR. $ ( WNTQS .AND. LDVT.LT.MINMN ) .OR. $ ( WNTQO .AND. M.GE.N .AND. LDVT.LT.N ) ) THEN INFO = -10 END IF * * Compute workspace * (Note: Comments in the code beginning "Workspace:" describe the * minimal amount of workspace needed at that point in the code, * as well as the preferred amount for good performance. * NB refers to the optimal block size for the immediately * following subroutine, as returned by ILAENV.) * IF( INFO.EQ.0 .AND. M.GT.0 .AND. N.GT.0 ) THEN IF( M.GE.N ) THEN * * Compute space needed for DBDSDC * IF( WNTQN ) THEN BDSPAC = 7*N ELSE BDSPAC = 3*N*N + 4*N END IF IF( M.GE.MNTHR ) THEN IF( WNTQN ) THEN * * Path 1 (M much larger than N, JOBZ='N') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, $ -1 ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+N ) MINWRK = BDSPAC + N ELSE IF( WNTQO ) THEN * * Path 2 (M much larger than N, JOBZ='O') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + 2*N*N MINWRK = BDSPAC + 2*N*N + 3*N ELSE IF( WNTQS ) THEN * * Path 3 (M much larger than N, JOBZ='S') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+N*ILAENV( 1, 'DORGQR', ' ', M, $ N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + N*N MINWRK = BDSPAC + N*N + 3*N ELSE IF( WNTQA ) THEN * * Path 4 (M much larger than N, JOBZ='A') * WRKBL = N + N*ILAENV( 1, 'DGEQRF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, N+M*ILAENV( 1, 'DORGQR', ' ', M, $ M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+2*N* $ ILAENV( 1, 'DGEBRD', ' ', N, N, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + N*N MINWRK = BDSPAC + N*N + 3*N END IF ELSE * * Path 5 (M at least N, but not much larger) * WRKBL = 3*N + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, -1, $ -1 ) IF( WNTQN ) THEN MAXWRK = MAX( WRKBL, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) ELSE IF( WNTQO ) THEN WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', M, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*N ) MAXWRK = WRKBL + M*N MINWRK = 3*N + MAX( M, N*N+BDSPAC ) ELSE IF( WNTQS ) THEN WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'QLN', M, N, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) ELSE IF( WNTQA ) THEN WRKBL = MAX( WRKBL, 3*N+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*N+N* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, N, -1 ) ) MAXWRK = MAX( MAXWRK, BDSPAC+3*N ) MINWRK = 3*N + MAX( M, BDSPAC ) END IF END IF ELSE * * Compute space needed for DBDSDC * IF( WNTQN ) THEN BDSPAC = 7*M ELSE BDSPAC = 3*M*M + 4*M END IF IF( N.GE.MNTHR ) THEN IF( WNTQN ) THEN * * Path 1t (N much larger than M, JOBZ='N') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, $ -1 ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+M ) MINWRK = BDSPAC + M ELSE IF( WNTQO ) THEN * * Path 2t (N much larger than M, JOBZ='O') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + 2*M*M MINWRK = BDSPAC + 2*M*M + 3*M ELSE IF( WNTQS ) THEN * * Path 3t (N much larger than M, JOBZ='S') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+M*ILAENV( 1, 'DORGLQ', ' ', M, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*M MINWRK = BDSPAC + M*M + 3*M ELSE IF( WNTQA ) THEN * * Path 4t (N much larger than M, JOBZ='A') * WRKBL = M + M*ILAENV( 1, 'DGELQF', ' ', M, N, -1, -1 ) WRKBL = MAX( WRKBL, M+N*ILAENV( 1, 'DORGLQ', ' ', N, $ N, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+2*M* $ ILAENV( 1, 'DGEBRD', ' ', M, M, -1, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, M, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*M MINWRK = BDSPAC + M*M + 3*M END IF ELSE * * Path 5t (N greater than M, but not much larger) * WRKBL = 3*M + ( M+N )*ILAENV( 1, 'DGEBRD', ' ', M, N, -1, $ -1 ) IF( WNTQN ) THEN MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) ELSE IF( WNTQO ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, N, M, -1 ) ) WRKBL = MAX( WRKBL, BDSPAC+3*M ) MAXWRK = WRKBL + M*N MINWRK = 3*M + MAX( N, M*M+BDSPAC ) ELSE IF( WNTQS ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', M, N, M, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) ELSE IF( WNTQA ) THEN WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'QLN', M, M, N, -1 ) ) WRKBL = MAX( WRKBL, 3*M+M* $ ILAENV( 1, 'DORMBR', 'PRT', N, N, M, -1 ) ) MAXWRK = MAX( WRKBL, BDSPAC+3*M ) MINWRK = 3*M + MAX( N, BDSPAC ) END IF END IF END IF WORK( 1 ) = MAXWRK END IF * IF( LWORK.LT.MINWRK .AND. .NOT.LQUERY ) THEN INFO = -12 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGESDD', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 ) THEN IF( LWORK.GE.1 ) $ WORK( 1 ) = ONE RETURN END IF * * Get machine constants * EPS = DLAMCH( 'P' ) SMLNUM = SQRT( DLAMCH( 'S' ) ) / EPS BIGNUM = ONE / SMLNUM * * Scale A if max element outside range [SMLNUM,BIGNUM] * ANRM = DLANGE( 'M', M, N, A, LDA, DUM ) ISCL = 0 IF( ANRM.GT.ZERO .AND. ANRM.LT.SMLNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, SMLNUM, M, N, A, LDA, IERR ) ELSE IF( ANRM.GT.BIGNUM ) THEN ISCL = 1 CALL DLASCL( 'G', 0, 0, ANRM, BIGNUM, M, N, A, LDA, IERR ) END IF * IF( M.GE.N ) THEN * * A has at least as many rows as columns. If A has sufficiently * more rows than columns, first reduce using the QR * decomposition (if sufficient workspace available) * IF( M.GE.MNTHR ) THEN * IF( WNTQN ) THEN * * Path 1 (M much larger than N, JOBZ='N') * No singular vectors to be computed * ITAU = 1 NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need 2*N, prefer N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Zero out below R * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need 4*N, prefer 3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) NWORK = IE + N * * Perform bidiagonal SVD, computing singular values only * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'N', N, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) * ELSE IF( WNTQO ) THEN * * Path 2 (M much larger than N, JOBZ = 'O') * N left singular vectors to be overwritten on A and * N right singular vectors to be computed in VT * IR = 1 * * WORK(IR) is LDWRKR by N * IF( LWORK.GE.LDA*N+N*N+3*N+BDSPAC ) THEN LDWRKR = LDA ELSE LDWRKR = ( LWORK-N*N-3*N-BDSPAC ) / N END IF ITAU = IR + LDWRKR*N NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in VT, copying result to WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * WORK(IU) is N by N * IU = NWORK NWORK = IU + N*N * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), N, $ VT, LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite WORK(IU) by left singular vectors of R * and VT by right singular vectors of R * (Workspace: need 2*N*N+3*N, prefer 2*N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), WORK( IU ), N, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of R in * WORK(IU), storing result in WORK(IR) and copying to A * (Workspace: need 2*N*N, prefer N*N+M*N) * DO 10 I = 1, M, LDWRKR CHUNK = MIN( M-I+1, LDWRKR ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IU ), N, ZERO, WORK( IR ), $ LDWRKR ) CALL DLACPY( 'F', CHUNK, N, WORK( IR ), LDWRKR, $ A( I, 1 ), LDA ) 10 CONTINUE * ELSE IF( WNTQS ) THEN * * Path 3 (M much larger than N, JOBZ='S') * N left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IR = 1 * * WORK(IR) is N by N * LDWRKR = N ITAU = IR + LDWRKR*N NWORK = ITAU + N * * Compute A=Q*R * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy R to WORK(IR), zeroing out below it * CALL DLACPY( 'U', N, N, A, LDA, WORK( IR ), LDWRKR ) CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, WORK( IR+1 ), $ LDWRKR ) * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGQR( M, N, N, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in WORK(IR) * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, WORK( IR ), LDWRKR, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagoal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of R and VT * by right singular vectors of R * (Workspace: need N*N+3*N, prefer N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * CALL DORMBR( 'P', 'R', 'T', N, N, N, WORK( IR ), LDWRKR, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of R in * WORK(IR), storing result in U * (Workspace: need N*N) * CALL DLACPY( 'F', N, N, U, LDU, WORK( IR ), LDWRKR ) CALL DGEMM( 'N', 'N', M, N, N, ONE, A, LDA, WORK( IR ), $ LDWRKR, ZERO, U, LDU ) * ELSE IF( WNTQA ) THEN * * Path 4 (M much larger than N, JOBZ='A') * M left singular vectors to be computed in U and * N right singular vectors to be computed in VT * IU = 1 * * WORK(IU) is N by N * LDWRKU = N ITAU = IU + LDWRKU*N NWORK = ITAU + N * * Compute A=Q*R, copying result to U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DGEQRF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DLACPY( 'L', M, N, A, LDA, U, LDU ) * * Generate Q in U * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) CALL DORGQR( M, M, N, U, LDU, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Produce R in A, zeroing out other entries * CALL DLASET( 'L', N-1, N-1, ZERO, ZERO, A( 2, 1 ), LDA ) IE = ITAU ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize R in A * (Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB) * CALL DGEBRD( N, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), N, $ VT, LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite WORK(IU) by left singular vectors of R and VT * by right singular vectors of R * (Workspace: need N*N+3*N, prefer N*N+2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', N, N, N, A, LDA, $ WORK( ITAUQ ), WORK( IU ), LDWRKU, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply Q in U by left singular vectors of R in * WORK(IU), storing result in A * (Workspace: need N*N) * CALL DGEMM( 'N', 'N', M, N, N, ONE, U, LDU, WORK( IU ), $ LDWRKU, ZERO, A, LDA ) * * Copy left singular vectors of A from A to U * CALL DLACPY( 'F', M, N, A, LDA, U, LDU ) * END IF * ELSE * * M .LT. MNTHR * * Path 5 (M at least N, but not much larger) * Reduce to bidiagonal form without QR decomposition * IE = 1 ITAUQ = IE + N ITAUP = ITAUQ + N NWORK = ITAUP + N * * Bidiagonalize A * (Workspace: need 3*N+M, prefer 3*N+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) IF( WNTQN ) THEN * * Perform bidiagonal SVD, only computing singular values * (Workspace: need N+BDSPAC) * CALL DBDSDC( 'U', 'N', N, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) ELSE IF( WNTQO ) THEN IU = NWORK IF( LWORK.GE.M*N+3*N+BDSPAC ) THEN * * WORK( IU ) is M by N * LDWRKU = M NWORK = IU + LDWRKU*N CALL DLASET( 'F', M, N, ZERO, ZERO, WORK( IU ), $ LDWRKU ) ELSE * * WORK( IU ) is N by N * LDWRKU = N NWORK = IU + LDWRKU*N * * WORK(IR) is LDWRKR by N * IR = NWORK LDWRKR = ( LWORK-N*N-3*N ) / N END IF NWORK = IU + LDWRKU*N * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in WORK(IU) and computing right * singular vectors of bidiagonal matrix in VT * (Workspace: need N+N*N+BDSPAC) * CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), WORK( IU ), $ LDWRKU, VT, LDVT, DUM, IDUM, WORK( NWORK ), $ IWORK, INFO ) * * Overwrite VT by right singular vectors of A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * IF( LWORK.GE.M*N+3*N+BDSPAC ) THEN * * Overwrite WORK(IU) by left singular vectors of A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), WORK( IU ), LDWRKU, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Copy left singular vectors of A from WORK(IU) to A * CALL DLACPY( 'F', M, N, WORK( IU ), LDWRKU, A, LDA ) ELSE * * Generate Q in A * (Workspace: need N*N+2*N, prefer N*N+N+N*NB) * CALL DORGBR( 'Q', M, N, N, A, LDA, WORK( ITAUQ ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply Q in A by left singular vectors of * bidiagonal matrix in WORK(IU), storing result in * WORK(IR) and copying to A * (Workspace: need 2*N*N, prefer N*N+M*N) * DO 20 I = 1, M, LDWRKR CHUNK = MIN( M-I+1, LDWRKR ) CALL DGEMM( 'N', 'N', CHUNK, N, N, ONE, A( I, 1 ), $ LDA, WORK( IU ), LDWRKU, ZERO, $ WORK( IR ), LDWRKR ) CALL DLACPY( 'F', CHUNK, N, WORK( IR ), LDWRKR, $ A( I, 1 ), LDA ) 20 CONTINUE END IF * ELSE IF( WNTQS ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DLASET( 'F', M, N, ZERO, ZERO, U, LDU ) CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 3*N, prefer 2*N+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, N, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, N, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) ELSE IF( WNTQA ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need N+BDSPAC) * CALL DLASET( 'F', M, M, ZERO, ZERO, U, LDU ) CALL DBDSDC( 'U', 'I', N, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Set the right corner of U to identity matrix * CALL DLASET( 'F', M-N, M-N, ZERO, ONE, U( N+1, N+1 ), $ LDU ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need N*N+2*N+M, prefer N*N+2*N+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) END IF * END IF * ELSE * * A has more columns than rows. If A has sufficiently more * columns than rows, first reduce using the LQ decomposition (if * sufficient workspace available) * IF( N.GE.MNTHR ) THEN * IF( WNTQN ) THEN * * Path 1t (N much larger than M, JOBZ='N') * No singular vectors to be computed * ITAU = 1 NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need 2*M, prefer M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Zero out above L * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need 4*M, prefer 3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) NWORK = IE + M * * Perform bidiagonal SVD, computing singular values only * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'U', 'N', M, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) * ELSE IF( WNTQO ) THEN * * Path 2t (N much larger than M, JOBZ='O') * M right singular vectors to be overwritten on A and * M left singular vectors to be computed in U * IVT = 1 * * IVT is M by M * IL = IVT + M*M IF( LWORK.GE.M*N+M*M+3*M+BDSPAC ) THEN * * WORK(IL) is M by N * LDWRKL = M CHUNK = N ELSE LDWRKL = M CHUNK = ( LWORK-M*M ) / M END IF ITAU = IL + LDWRKL*M NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy L to WORK(IL), zeroing about above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWRKL ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IL+LDWRKL ), LDWRKL ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in WORK(IL) * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWRKL, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U, and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M+M*M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), M, DUM, IDUM, WORK( NWORK ), $ IWORK, INFO ) * * Overwrite U by left singular vectors of L and WORK(IVT) * by right singular vectors of L * (Workspace: need 2*M*M+3*M, prefer 2*M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUP ), WORK( IVT ), M, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IVT) by Q * in A, storing result in WORK(IL) and copying to A * (Workspace: need 2*M*M, prefer M*M+M*N) * DO 30 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IVT ), M, $ A( 1, I ), LDA, ZERO, WORK( IL ), LDWRKL ) CALL DLACPY( 'F', M, BLK, WORK( IL ), LDWRKL, $ A( 1, I ), LDA ) 30 CONTINUE * ELSE IF( WNTQS ) THEN * * Path 3t (N much larger than M, JOBZ='S') * M right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IL = 1 * * WORK(IL) is M by M * LDWRKL = M ITAU = IL + LDWRKL*M NWORK = ITAU + M * * Compute A=L*Q * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Copy L to WORK(IL), zeroing out above it * CALL DLACPY( 'L', M, M, A, LDA, WORK( IL ), LDWRKL ) CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, $ WORK( IL+LDWRKL ), LDWRKL ) * * Generate Q in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( M, N, M, A, LDA, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in WORK(IU), copying result to U * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, WORK( IL ), LDWRKL, S, WORK( IE ), $ WORK( ITAUQ ), WORK( ITAUP ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of L and VT * by right singular vectors of L * (Workspace: need M*M+3*M, prefer M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, WORK( IL ), LDWRKL, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IL) by * Q in A, storing result in VT * (Workspace: need M*M) * CALL DLACPY( 'F', M, M, VT, LDVT, WORK( IL ), LDWRKL ) CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IL ), LDWRKL, $ A, LDA, ZERO, VT, LDVT ) * ELSE IF( WNTQA ) THEN * * Path 4t (N much larger than M, JOBZ='A') * N right singular vectors to be computed in VT and * M left singular vectors to be computed in U * IVT = 1 * * WORK(IVT) is M by M * LDWKVT = M ITAU = IVT + LDWKVT*M NWORK = ITAU + M * * Compute A=L*Q, copying result to VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DGELQF( M, N, A, LDA, WORK( ITAU ), WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DLACPY( 'U', M, N, A, LDA, VT, LDVT ) * * Generate Q in VT * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGLQ( N, N, M, VT, LDVT, WORK( ITAU ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Produce L in A, zeroing out other entries * CALL DLASET( 'U', M-1, M-1, ZERO, ZERO, A( 1, 2 ), LDA ) IE = ITAU ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize L in A * (Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB) * CALL DGEBRD( M, M, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M+M*M+BDSPAC) * CALL DBDSDC( 'U', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), LDWKVT, DUM, IDUM, $ WORK( NWORK ), IWORK, INFO ) * * Overwrite U by left singular vectors of L and WORK(IVT) * by right singular vectors of L * (Workspace: need M*M+3*M, prefer M*M+2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, M, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, M, M, A, LDA, $ WORK( ITAUP ), WORK( IVT ), LDWKVT, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply right singular vectors of L in WORK(IVT) by * Q in VT, storing result in A * (Workspace: need M*M) * CALL DGEMM( 'N', 'N', M, N, M, ONE, WORK( IVT ), LDWKVT, $ VT, LDVT, ZERO, A, LDA ) * * Copy right singular vectors of A from A to VT * CALL DLACPY( 'F', M, N, A, LDA, VT, LDVT ) * END IF * ELSE * * N .LT. MNTHR * * Path 5t (N greater than M, but not much larger) * Reduce to bidiagonal form without LQ decomposition * IE = 1 ITAUQ = IE + M ITAUP = ITAUQ + M NWORK = ITAUP + M * * Bidiagonalize A * (Workspace: need 3*M+N, prefer 3*M+(M+N)*NB) * CALL DGEBRD( M, N, A, LDA, S, WORK( IE ), WORK( ITAUQ ), $ WORK( ITAUP ), WORK( NWORK ), LWORK-NWORK+1, $ IERR ) IF( WNTQN ) THEN * * Perform bidiagonal SVD, only computing singular values * (Workspace: need M+BDSPAC) * CALL DBDSDC( 'L', 'N', M, S, WORK( IE ), DUM, 1, DUM, 1, $ DUM, IDUM, WORK( NWORK ), IWORK, INFO ) ELSE IF( WNTQO ) THEN LDWKVT = M IVT = NWORK IF( LWORK.GE.M*N+3*M+BDSPAC ) THEN * * WORK( IVT ) is M by N * CALL DLASET( 'F', M, N, ZERO, ZERO, WORK( IVT ), $ LDWKVT ) NWORK = IVT + LDWKVT*N ELSE * * WORK( IVT ) is M by M * NWORK = IVT + LDWKVT*M IL = NWORK * * WORK(IL) is M by CHUNK * CHUNK = ( LWORK-M*M-3*M ) / M END IF * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in WORK(IVT) * (Workspace: need M*M+BDSPAC) * CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, $ WORK( IVT ), LDWKVT, DUM, IDUM, $ WORK( NWORK ), IWORK, INFO ) * * Overwrite U by left singular vectors of A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) * IF( LWORK.GE.M*N+3*M+BDSPAC ) THEN * * Overwrite WORK(IVT) by left singular vectors of A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORMBR( 'P', 'R', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), WORK( IVT ), LDWKVT, $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Copy right singular vectors of A from WORK(IVT) to A * CALL DLACPY( 'F', M, N, WORK( IVT ), LDWKVT, A, LDA ) ELSE * * Generate P**T in A * (Workspace: need M*M+2*M, prefer M*M+M+M*NB) * CALL DORGBR( 'P', M, N, M, A, LDA, WORK( ITAUP ), $ WORK( NWORK ), LWORK-NWORK+1, IERR ) * * Multiply Q in A by right singular vectors of * bidiagonal matrix in WORK(IVT), storing result in * WORK(IL) and copying to A * (Workspace: need 2*M*M, prefer M*M+M*N) * DO 40 I = 1, N, CHUNK BLK = MIN( N-I+1, CHUNK ) CALL DGEMM( 'N', 'N', M, BLK, M, ONE, WORK( IVT ), $ LDWKVT, A( 1, I ), LDA, ZERO, $ WORK( IL ), M ) CALL DLACPY( 'F', M, BLK, WORK( IL ), M, A( 1, I ), $ LDA ) 40 CONTINUE END IF ELSE IF( WNTQS ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DLASET( 'F', M, N, ZERO, ZERO, VT, LDVT ) CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 3*M, prefer 2*M+M*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', M, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) ELSE IF( WNTQA ) THEN * * Perform bidiagonal SVD, computing left singular vectors * of bidiagonal matrix in U and computing right singular * vectors of bidiagonal matrix in VT * (Workspace: need M+BDSPAC) * CALL DLASET( 'F', N, N, ZERO, ZERO, VT, LDVT ) CALL DBDSDC( 'L', 'I', M, S, WORK( IE ), U, LDU, VT, $ LDVT, DUM, IDUM, WORK( NWORK ), IWORK, $ INFO ) * * Set the right corner of VT to identity matrix * CALL DLASET( 'F', N-M, N-M, ZERO, ONE, VT( M+1, M+1 ), $ LDVT ) * * Overwrite U by left singular vectors of A and VT * by right singular vectors of A * (Workspace: need 2*M+N, prefer 2*M+N*NB) * CALL DORMBR( 'Q', 'L', 'N', M, M, N, A, LDA, $ WORK( ITAUQ ), U, LDU, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) CALL DORMBR( 'P', 'R', 'T', N, N, M, A, LDA, $ WORK( ITAUP ), VT, LDVT, WORK( NWORK ), $ LWORK-NWORK+1, IERR ) END IF * END IF * END IF * * Undo scaling if necessary * IF( ISCL.EQ.1 ) THEN IF( ANRM.GT.BIGNUM ) $ CALL DLASCL( 'G', 0, 0, BIGNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) IF( ANRM.LT.SMLNUM ) $ CALL DLASCL( 'G', 0, 0, SMLNUM, ANRM, MINMN, 1, S, MINMN, $ IERR ) END IF * * Return optimal workspace in WORK(1) * WORK( 1 ) = DBLE( MAXWRK ) * RETURN * * End of DGESDD * END SUBROUTINE DBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, $ WORK, IWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * December 1, 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( * ) * .. * * 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 (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 * * ===================================================================== * * .. 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 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 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 * 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 ) ) $ CALL DLASR( 'L', 'V', 'B', N, N, WORK( 1 ), WORK( N ), U, LDU ) * RETURN * * End of DBDSDC * END SUBROUTINE DLASDQ( UPLO, SQRE, N, NCVT, NRU, NCC, D, E, VT, LDVT, $ U, LDU, C, LDC, WORK, INFO ) * * -- LAPACK auxiliary routine (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 UPLO INTEGER INFO, LDC, LDU, LDVT, N, NCC, NCVT, NRU, SQRE * .. * .. Array Arguments .. DOUBLE PRECISION C( LDC, * ), D( * ), E( * ), U( LDU, * ), $ VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DLASDQ computes the singular value decomposition (SVD) of a real * (upper or lower) bidiagonal matrix with diagonal D and offdiagonal * E, accumulating the transformations if desired. Letting B denote * the input bidiagonal matrix, the algorithm computes orthogonal * matrices Q and P such that B = Q * S * P' (P' denotes the transpose * of P). The singular values S are overwritten on D. * * The input matrix U is changed to U * Q if desired. * The input matrix VT is changed to P' * VT if desired. * The input matrix C is changed to Q' * C if desired. * * See "Computing Small Singular Values of Bidiagonal Matrices With * Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan, * LAPACK Working Note #3, for a detailed description of the algorithm. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * On entry, UPLO specifies whether the input bidiagonal matrix * is upper or lower bidiagonal, and wether it is square are * not. * UPLO = 'U' or 'u' B is upper bidiagonal. * UPLO = 'L' or 'l' B is lower bidiagonal. * * SQRE (input) INTEGER * = 0: then the input matrix is N-by-N. * = 1: then the input matrix is N-by-(N+1) if UPLU = 'U' and * (N+1)-by-N if UPLU = 'L'. * * The bidiagonal matrix has * N = NL + NR + 1 rows and * M = N + SQRE >= N columns. * * N (input) INTEGER * On entry, N specifies the number of rows and columns * in the matrix. N must be at least 0. * * NCVT (input) INTEGER * On entry, NCVT specifies the number of columns of * the matrix VT. NCVT must be at least 0. * * NRU (input) INTEGER * On entry, NRU specifies the number of rows of * the matrix U. NRU must be at least 0. * * NCC (input) INTEGER * On entry, NCC specifies the number of columns of * the matrix C. NCC must be at least 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, D contains the diagonal entries of the * bidiagonal matrix whose SVD is desired. On normal exit, * D contains the singular values in ascending order. * * E (input/output) DOUBLE PRECISION array. * dimension is (N-1) if SQRE = 0 and N if SQRE = 1. * On entry, the entries of E contain the offdiagonal entries * of the bidiagonal matrix whose SVD is desired. On normal * exit, E will contain 0. If the algorithm does not converge, * D and E will contain the diagonal and superdiagonal entries * of a bidiagonal matrix orthogonally equivalent to the one * given as input. * * VT (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT) * On entry, contains a matrix which on exit has been * premultiplied by P', dimension N-by-NCVT if SQRE = 0 * and (N+1)-by-NCVT if SQRE = 1 (not referenced if NCVT=0). * * LDVT (input) INTEGER * On entry, LDVT specifies the leading dimension of VT as * declared in the calling (sub) program. LDVT must be at * least 1. If NCVT is nonzero LDVT must also be at least N. * * U (input/output) DOUBLE PRECISION array, dimension (LDU, N) * On entry, contains a matrix which on exit has been * postmultiplied by Q, dimension NRU-by-N if SQRE = 0 * and NRU-by-(N+1) if SQRE = 1 (not referenced if NRU=0). * * LDU (input) INTEGER * On entry, LDU specifies the leading dimension of U as * declared in the calling (sub) program. LDU must be at * least max( 1, NRU ) . * * C (input/output) DOUBLE PRECISION array, dimension (LDC, NCC) * On entry, contains an N-by-NCC matrix which on exit * has been premultiplied by Q' dimension N-by-NCC if SQRE = 0 * and (N+1)-by-NCC if SQRE = 1 (not referenced if NCC=0). * * LDC (input) INTEGER * On entry, LDC specifies the leading dimension of C as * declared in the calling (sub) program. LDC must be at * least 1. If NCC is nonzero, LDC must also be at least N. * * WORK (workspace) DOUBLE PRECISION array, dimension (4*N) * Workspace. Only referenced if one of NCVT, NRU, or NCC is * nonzero, and if N is at least 2. * * INFO (output) INTEGER * On exit, a value of 0 indicates a successful exit. * If INFO < 0, argument number -INFO is illegal. * If INFO > 0, the algorithm did not converge, and INFO * specifies how many superdiagonals did not converge. * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. LOGICAL ROTATE INTEGER I, ISUB, IUPLO, J, NP1, SQRE1 DOUBLE PRECISION CS, R, SMIN, SN * .. * .. External Subroutines .. EXTERNAL DBDSQR, DLARTG, DLASR, DSWAP, XERBLA * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 IUPLO = 0 IF( LSAME( UPLO, 'U' ) ) $ IUPLO = 1 IF( LSAME( UPLO, 'L' ) ) $ IUPLO = 2 IF( IUPLO.EQ.0 ) THEN INFO = -1 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( NCVT.LT.0 ) THEN INFO = -4 ELSE IF( NRU.LT.0 ) THEN INFO = -5 ELSE IF( NCC.LT.0 ) THEN INFO = -6 ELSE IF( ( NCVT.EQ.0 .AND. LDVT.LT.1 ) .OR. $ ( NCVT.GT.0 .AND. LDVT.LT.MAX( 1, N ) ) ) THEN INFO = -10 ELSE IF( LDU.LT.MAX( 1, NRU ) ) THEN INFO = -12 ELSE IF( ( NCC.EQ.0 .AND. LDC.LT.1 ) .OR. $ ( NCC.GT.0 .AND. LDC.LT.MAX( 1, N ) ) ) THEN INFO = -14 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASDQ', -INFO ) RETURN END IF IF( N.EQ.0 ) $ RETURN * * ROTATE is true if any singular vectors desired, false otherwise * ROTATE = ( NCVT.GT.0 ) .OR. ( NRU.GT.0 ) .OR. ( NCC.GT.0 ) NP1 = N + 1 SQRE1 = SQRE * * If matrix non-square upper bidiagonal, rotate to be lower * bidiagonal. The rotations are on the right. * IF( ( IUPLO.EQ.1 ) .AND. ( SQRE1.EQ.1 ) ) THEN 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( ROTATE ) THEN WORK( I ) = CS WORK( N+I ) = SN END IF 10 CONTINUE CALL DLARTG( D( N ), E( N ), CS, SN, R ) D( N ) = R E( N ) = ZERO IF( ROTATE ) THEN WORK( N ) = CS WORK( N+N ) = SN END IF IUPLO = 2 SQRE1 = 0 * * Update singular vectors if desired. * IF( NCVT.GT.0 ) $ CALL DLASR( 'L', 'V', 'F', NP1, NCVT, WORK( 1 ), $ WORK( NP1 ), VT, LDVT ) END IF * * If matrix lower bidiagonal, rotate to be upper bidiagonal * by applying Givens rotations on the left. * IF( IUPLO.EQ.2 ) THEN DO 20 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( ROTATE ) THEN WORK( I ) = CS WORK( N+I ) = SN END IF 20 CONTINUE * * If matrix (N+1)-by-N lower bidiagonal, one additional * rotation is needed. * IF( SQRE1.EQ.1 ) THEN CALL DLARTG( D( N ), E( N ), CS, SN, R ) D( N ) = R IF( ROTATE ) THEN WORK( N ) = CS WORK( N+N ) = SN END IF END IF * * Update singular vectors if desired. * IF( NRU.GT.0 ) THEN IF( SQRE1.EQ.0 ) THEN CALL DLASR( 'R', 'V', 'F', NRU, N, WORK( 1 ), $ WORK( NP1 ), U, LDU ) ELSE CALL DLASR( 'R', 'V', 'F', NRU, NP1, WORK( 1 ), $ WORK( NP1 ), U, LDU ) END IF END IF IF( NCC.GT.0 ) THEN IF( SQRE1.EQ.0 ) THEN CALL DLASR( 'L', 'V', 'F', N, NCC, WORK( 1 ), $ WORK( NP1 ), C, LDC ) ELSE CALL DLASR( 'L', 'V', 'F', NP1, NCC, WORK( 1 ), $ WORK( NP1 ), C, LDC ) END IF END IF END IF * * Call DBDSQR to compute the SVD of the reduced real * N-by-N upper bidiagonal matrix. * CALL DBDSQR( 'U', N, NCVT, NRU, NCC, D, E, VT, LDVT, U, LDU, C, $ LDC, WORK, INFO ) * * Sort the singular values into ascending order (insertion sort on * singular values, but only one transposition per singular vector) * DO 40 I = 1, N * * Scan for smallest D(I). * ISUB = I SMIN = D( I ) DO 30 J = I + 1, N IF( D( J ).LT.SMIN ) THEN ISUB = J SMIN = D( J ) END IF 30 CONTINUE IF( ISUB.NE.I ) THEN * * Swap singular values and vectors. * D( ISUB ) = D( I ) D( I ) = SMIN IF( NCVT.GT.0 ) $ CALL DSWAP( NCVT, VT( ISUB, 1 ), LDVT, VT( I, 1 ), LDVT ) IF( NRU.GT.0 ) $ CALL DSWAP( NRU, U( 1, ISUB ), 1, U( 1, I ), 1 ) IF( NCC.GT.0 ) $ CALL DSWAP( NCC, C( ISUB, 1 ), LDC, C( I, 1 ), LDC ) END IF 40 CONTINUE * RETURN * * End of DLASDQ * END SUBROUTINE DLASD0( N, SQRE, D, E, U, LDU, VT, LDVT, SMLSIZ, IWORK, $ WORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDU, LDVT, N, SMLSIZ, SQRE * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION D( * ), E( * ), U( LDU, * ), VT( LDVT, * ), $ WORK( * ) * .. * * Purpose * ======= * * Using a divide and conquer approach, DLASD0 computes the singular * value decomposition (SVD) of a real upper bidiagonal N-by-M * matrix B with diagonal D and offdiagonal E, where M = N + SQRE. * The algorithm computes orthogonal matrices U and VT such that * B = U * S * VT. The singular values S are overwritten on D. * * A related subroutine, DLASDA, computes only the singular values, * and optionally, the singular vectors in compact form. * * Arguments * ========= * * N (input) INTEGER * On entry, the row dimension of the upper bidiagonal matrix. * This is also the dimension of the main diagonal array D. * * SQRE (input) INTEGER * Specifies the column dimension of the bidiagonal matrix. * = 0: The bidiagonal matrix has column dimension M = N; * = 1: The bidiagonal matrix has column dimension M = N+1; * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry D contains the main diagonal of the bidiagonal * matrix. * On exit D, if INFO = 0, contains its singular values. * * E (input) DOUBLE PRECISION array, dimension (M-1) * Contains the subdiagonal entries of the bidiagonal matrix. * On exit, E has been destroyed. * * U (output) DOUBLE PRECISION array, dimension at least (LDQ, N) * On exit, U contains the left singular vectors. * * LDU (input) INTEGER * On entry, leading dimension of U. * * VT (output) DOUBLE PRECISION array, dimension at least (LDVT, M) * On exit, VT' contains the right singular vectors. * * LDVT (input) INTEGER * On entry, leading dimension of VT. * * SMLSIZ (input) INTEGER * On entry, maximum size of the subproblems at the * bottom of the computation tree. * * IWORK INTEGER work array. * Dimension must be at least (8 * N) * * WORK DOUBLE PRECISION work array. * Dimension must be at least (3 * M**2 + 2 * M) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Local Scalars .. INTEGER I, I1, IC, IDXQ, IDXQC, IM1, INODE, ITEMP, IWK, $ J, LF, LL, LVL, M, NCC, ND, NDB1, NDIML, NDIMR, $ NL, NLF, NLP1, NLVL, NR, NRF, NRP1, SQREI DOUBLE PRECISION ALPHA, BETA * .. * .. External Subroutines .. EXTERNAL DLASD1, DLASDQ, DLASDT, XERBLA * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( N.LT.0 ) THEN INFO = -1 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -2 END IF * M = N + SQRE * IF( LDU.LT.N ) THEN INFO = -6 ELSE IF( LDVT.LT.M ) THEN INFO = -8 ELSE IF( SMLSIZ.LT.3 ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD0', -INFO ) RETURN END IF * * If the input matrix is too small, call DLASDQ to find the SVD. * IF( N.LE.SMLSIZ ) THEN CALL DLASDQ( 'U', SQRE, N, M, N, 0, D, E, VT, LDVT, U, LDU, U, $ LDU, WORK, INFO ) RETURN END IF * * Set up the computation tree. * INODE = 1 NDIML = INODE + N NDIMR = NDIML + N IDXQ = NDIMR + N IWK = IDXQ + N CALL DLASDT( N, NLVL, ND, IWORK( INODE ), IWORK( NDIML ), $ IWORK( NDIMR ), SMLSIZ ) * * For the nodes on bottom level of the tree, solve * their subproblems by DLASDQ. * NDB1 = ( ND+1 ) / 2 NCC = 0 DO 30 I = NDB1, ND * * IC : center row of each node * NL : number of rows of left subproblem * NR : number of rows of right subproblem * NLF: starting row of the left subproblem * NRF: starting row of the right subproblem * I1 = I - 1 IC = IWORK( INODE+I1 ) NL = IWORK( NDIML+I1 ) NLP1 = NL + 1 NR = IWORK( NDIMR+I1 ) NRP1 = NR + 1 NLF = IC - NL NRF = IC + 1 SQREI = 1 CALL DLASDQ( 'U', SQREI, NL, NLP1, NL, NCC, D( NLF ), E( NLF ), $ VT( NLF, NLF ), LDVT, U( NLF, NLF ), LDU, $ U( NLF, NLF ), LDU, WORK, INFO ) IF( INFO.NE.0 ) THEN RETURN END IF ITEMP = IDXQ + NLF - 2 DO 10 J = 1, NL IWORK( ITEMP+J ) = J 10 CONTINUE IF( I.EQ.ND ) THEN SQREI = SQRE ELSE SQREI = 1 END IF NRP1 = NR + SQREI CALL DLASDQ( 'U', SQREI, NR, NRP1, NR, NCC, D( NRF ), E( NRF ), $ VT( NRF, NRF ), LDVT, U( NRF, NRF ), LDU, $ U( NRF, NRF ), LDU, WORK, INFO ) IF( INFO.NE.0 ) THEN RETURN END IF ITEMP = IDXQ + IC DO 20 J = 1, NR IWORK( ITEMP+J-1 ) = J 20 CONTINUE 30 CONTINUE * * Now conquer each subproblem bottom-up. * DO 50 LVL = NLVL, 1, -1 * * Find the first node LF and last node LL on the * current level LVL. * IF( LVL.EQ.1 ) THEN LF = 1 LL = 1 ELSE LF = 2**( LVL-1 ) LL = 2*LF - 1 END IF DO 40 I = LF, LL IM1 = I - 1 IC = IWORK( INODE+IM1 ) NL = IWORK( NDIML+IM1 ) NR = IWORK( NDIMR+IM1 ) NLF = IC - NL IF( ( SQRE.EQ.0 ) .AND. ( I.EQ.LL ) ) THEN SQREI = SQRE ELSE SQREI = 1 END IF IDXQC = IDXQ + NLF - 1 ALPHA = D( IC ) BETA = E( IC ) CALL DLASD1( NL, NR, SQREI, D( NLF ), ALPHA, BETA, $ U( NLF, NLF ), LDU, VT( NLF, NLF ), LDVT, $ IWORK( IDXQC ), IWORK( IWK ), WORK, INFO ) IF( INFO.NE.0 ) THEN RETURN END IF 40 CONTINUE 50 CONTINUE * RETURN * * End of DLASD0 * END SUBROUTINE DLASDA( ICOMPQ, SMLSIZ, N, SQRE, D, E, U, LDU, VT, K, $ DIFL, DIFR, Z, POLES, GIVPTR, GIVCOL, LDGCOL, $ PERM, GIVNUM, C, S, WORK, IWORK, INFO ) * * -- LAPACK auxiliary routine (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 .. INTEGER ICOMPQ, INFO, LDGCOL, LDU, N, SMLSIZ, SQRE * .. * .. Array Arguments .. INTEGER GIVCOL( LDGCOL, * ), GIVPTR( * ), IWORK( * ), $ K( * ), PERM( LDGCOL, * ) DOUBLE PRECISION C( * ), D( * ), DIFL( LDU, * ), DIFR( LDU, * ), $ E( * ), GIVNUM( LDU, * ), POLES( LDU, * ), $ S( * ), U( LDU, * ), VT( LDU, * ), WORK( * ), $ Z( LDU, * ) * .. * * Purpose * ======= * * Using a divide and conquer approach, DLASDA computes the singular * value decomposition (SVD) of a real upper bidiagonal N-by-M matrix * B with diagonal D and offdiagonal E, where M = N + SQRE. The * algorithm computes the singular values in the SVD B = U * S * VT. * The orthogonal matrices U and VT are optionally computed in * compact form. * * A related subroutine, DLASD0, computes the singular values and * the singular vectors in explicit form. * * Arguments * ========= * * ICOMPQ (input) INTEGER * Specifies whether singular vectors are to be computed * in compact form, as follows * = 0: Compute singular values only. * = 1: Compute singular vectors of upper bidiagonal * matrix in compact form. * * SMLSIZ (input) INTEGER * The maximum size of the subproblems at the bottom of the * computation tree. * * N (input) INTEGER * The row dimension of the upper bidiagonal matrix. This is * also the dimension of the main diagonal array D. * * SQRE (input) INTEGER * Specifies the column dimension of the bidiagonal matrix. * = 0: The bidiagonal matrix has column dimension M = N; * = 1: The bidiagonal matrix has column dimension M = N + 1. * * D (input/output) DOUBLE PRECISION array, dimension ( N ) * On entry D contains the main diagonal of the bidiagonal * matrix. On exit D, if INFO = 0, contains its singular values. * * E (input) DOUBLE PRECISION array, dimension ( M-1 ) * Contains the subdiagonal entries of the bidiagonal matrix. * On exit, E has been destroyed. * * U (output) DOUBLE PRECISION array, * dimension ( LDU, SMLSIZ ) if ICOMPQ = 1, and not referenced * if ICOMPQ = 0. If ICOMPQ = 1, on exit, U contains the left * singular vector matrices of all subproblems at the bottom * level. * * LDU (input) INTEGER, LDU = > N. * The leading dimension of arrays U, VT, DIFL, DIFR, POLES, * GIVNUM, and Z. * * VT (output) DOUBLE PRECISION array, * dimension ( LDU, SMLSIZ+1 ) if ICOMPQ = 1, and not referenced * if ICOMPQ = 0. If ICOMPQ = 1, on exit, VT' contains the right * singular vector matrices of all subproblems at the bottom * level. * * K (output) INTEGER array, * dimension ( N ) if ICOMPQ = 1 and dimension 1 if ICOMPQ = 0. * If ICOMPQ = 1, on exit, K(I) is the dimension of the I-th * secular equation on the computation tree. * * DIFL (output) DOUBLE PRECISION array, dimension ( LDU, NLVL ), * where NLVL = floor(log_2 (N/SMLSIZ))). * * DIFR (output) DOUBLE PRECISION array, * dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1 and * dimension ( N ) if ICOMPQ = 0. * If ICOMPQ = 1, on exit, DIFL(1:N, I) and DIFR(1:N, 2 * I - 1) * record distances between singular values on the I-th * level and singular values on the (I -1)-th level, and * DIFR(1:N, 2 * I ) contains the normalizing factors for * the right singular vector matrix. See DLASD8 for details. * * Z (output) DOUBLE PRECISION array, * dimension ( LDU, NLVL ) if ICOMPQ = 1 and * dimension ( N ) if ICOMPQ = 0. * The first K elements of Z(1, I) contain the components of * the deflation-adjusted updating row vector for subproblems * on the I-th level. * * POLES (output) DOUBLE PRECISION array, * dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1, and not referenced * if ICOMPQ = 0. If ICOMPQ = 1, on exit, POLES(1, 2*I - 1) and * POLES(1, 2*I) contain the new and old singular values * involved in the secular equations on the I-th level. * * GIVPTR (output) INTEGER array, * dimension ( N ) if ICOMPQ = 1, and not referenced if * ICOMPQ = 0. If ICOMPQ = 1, on exit, GIVPTR( I ) records * the number of Givens rotations performed on the I-th * problem on the computation tree. * * GIVCOL (output) INTEGER array, * dimension ( LDGCOL, 2 * NLVL ) if ICOMPQ = 1, and not * referenced if ICOMPQ = 0. If ICOMPQ = 1, on exit, for each I, * GIVCOL(1, 2 *I - 1) and GIVCOL(1, 2 *I) record the locations * of Givens rotations performed on the I-th level on the * computation tree. * * LDGCOL (input) INTEGER, LDGCOL = > N. * The leading dimension of arrays GIVCOL and PERM. * * PERM (output) INTEGER array, * dimension ( LDGCOL, NLVL ) if ICOMPQ = 1, and not referenced * if ICOMPQ = 0. If ICOMPQ = 1, on exit, PERM(1, I) records * permutations done on the I-th level of the computation tree. * * GIVNUM (output) DOUBLE PRECISION array, * dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1, and not * referenced if ICOMPQ = 0. If ICOMPQ = 1, on exit, for each I, * GIVNUM(1, 2 *I - 1) and GIVNUM(1, 2 *I) record the C- and S- * values of Givens rotations performed on the I-th level on * the computation tree. * * C (output) DOUBLE PRECISION array, * dimension ( N ) if ICOMPQ = 1, and dimension 1 if ICOMPQ = 0. * If ICOMPQ = 1 and the I-th subproblem is not square, on exit, * C( I ) contains the C-value of a Givens rotation related to * the right null space of the I-th subproblem. * * S (output) DOUBLE PRECISION array, dimension ( N ) if * ICOMPQ = 1, and dimension 1 if ICOMPQ = 0. If ICOMPQ = 1 * and the I-th subproblem is not square, on exit, S( I ) * contains the S-value of a Givens rotation related to * the right null space of the I-th subproblem. * * WORK (workspace) DOUBLE PRECISION array, dimension * (6 * N + (SMLSIZ + 1)*(SMLSIZ + 1)). * * IWORK (workspace) INTEGER array. * Dimension must be at least (7 * N). * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * 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 PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I, I1, IC, IDXQ, IDXQI, IM1, INODE, ITEMP, IWK, $ J, LF, LL, LVL, LVL2, M, NCC, ND, NDB1, NDIML, $ NDIMR, NL, NLF, NLP1, NLVL, NR, NRF, NRP1, NRU, $ NWORK1, NWORK2, SMLSZP, SQREI, VF, VFI, VL, VLI DOUBLE PRECISION ALPHA, BETA * .. * .. External Subroutines .. EXTERNAL DCOPY, DLASD6, DLASDQ, DLASDT, DLASET, XERBLA * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( ( ICOMPQ.LT.0 ) .OR. ( ICOMPQ.GT.1 ) ) THEN INFO = -1 ELSE IF( SMLSIZ.LT.3 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -4 ELSE IF( LDU.LT.( N+SQRE ) ) THEN INFO = -8 ELSE IF( LDGCOL.LT.N ) THEN INFO = -17 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASDA', -INFO ) RETURN END IF * M = N + SQRE * * If the input matrix is too small, call DLASDQ to find the SVD. * IF( N.LE.SMLSIZ ) THEN IF( ICOMPQ.EQ.0 ) THEN CALL DLASDQ( 'U', SQRE, N, 0, 0, 0, D, E, VT, LDU, U, LDU, $ U, LDU, WORK, INFO ) ELSE CALL DLASDQ( 'U', SQRE, N, M, N, 0, D, E, VT, LDU, U, LDU, $ U, LDU, WORK, INFO ) END IF RETURN END IF * * Book-keeping and set up the computation tree. * INODE = 1 NDIML = INODE + N NDIMR = NDIML + N IDXQ = NDIMR + N IWK = IDXQ + N * NCC = 0 NRU = 0 * SMLSZP = SMLSIZ + 1 VF = 1 VL = VF + M NWORK1 = VL + M NWORK2 = NWORK1 + SMLSZP*SMLSZP * CALL DLASDT( N, NLVL, ND, IWORK( INODE ), IWORK( NDIML ), $ IWORK( NDIMR ), SMLSIZ ) * * for the nodes on bottom level of the tree, solve * their subproblems by DLASDQ. * NDB1 = ( ND+1 ) / 2 DO 30 I = NDB1, ND * * IC : center row of each node * NL : number of rows of left subproblem * NR : number of rows of right subproblem * NLF: starting row of the left subproblem * NRF: starting row of the right subproblem * I1 = I - 1 IC = IWORK( INODE+I1 ) NL = IWORK( NDIML+I1 ) NLP1 = NL + 1 NR = IWORK( NDIMR+I1 ) NLF = IC - NL NRF = IC + 1 IDXQI = IDXQ + NLF - 2 VFI = VF + NLF - 1 VLI = VL + NLF - 1 SQREI = 1 IF( ICOMPQ.EQ.0 ) THEN CALL DLASET( 'A', NLP1, NLP1, ZERO, ONE, WORK( NWORK1 ), $ SMLSZP ) CALL DLASDQ( 'U', SQREI, NL, NLP1, NRU, NCC, D( NLF ), $ E( NLF ), WORK( NWORK1 ), SMLSZP, $ WORK( NWORK2 ), NL, WORK( NWORK2 ), NL, $ WORK( NWORK2 ), INFO ) ITEMP = NWORK1 + NL*SMLSZP CALL DCOPY( NLP1, WORK( NWORK1 ), 1, WORK( VFI ), 1 ) CALL DCOPY( NLP1, WORK( ITEMP ), 1, WORK( VLI ), 1 ) ELSE CALL DLASET( 'A', NL, NL, ZERO, ONE, U( NLF, 1 ), LDU ) CALL DLASET( 'A', NLP1, NLP1, ZERO, ONE, VT( NLF, 1 ), LDU ) CALL DLASDQ( 'U', SQREI, NL, NLP1, NL, NCC, D( NLF ), $ E( NLF ), VT( NLF, 1 ), LDU, U( NLF, 1 ), LDU, $ U( NLF, 1 ), LDU, WORK( NWORK1 ), INFO ) CALL DCOPY( NLP1, VT( NLF, 1 ), 1, WORK( VFI ), 1 ) CALL DCOPY( NLP1, VT( NLF, NLP1 ), 1, WORK( VLI ), 1 ) END IF IF( INFO.NE.0 ) THEN RETURN END IF DO 10 J = 1, NL IWORK( IDXQI+J ) = J 10 CONTINUE IF( ( I.EQ.ND ) .AND. ( SQRE.EQ.0 ) ) THEN SQREI = 0 ELSE SQREI = 1 END IF IDXQI = IDXQI + NLP1 VFI = VFI + NLP1 VLI = VLI + NLP1 NRP1 = NR + SQREI IF( ICOMPQ.EQ.0 ) THEN CALL DLASET( 'A', NRP1, NRP1, ZERO, ONE, WORK( NWORK1 ), $ SMLSZP ) CALL DLASDQ( 'U', SQREI, NR, NRP1, NRU, NCC, D( NRF ), $ E( NRF ), WORK( NWORK1 ), SMLSZP, $ WORK( NWORK2 ), NR, WORK( NWORK2 ), NR, $ WORK( NWORK2 ), INFO ) ITEMP = NWORK1 + ( NRP1-1 )*SMLSZP CALL DCOPY( NRP1, WORK( NWORK1 ), 1, WORK( VFI ), 1 ) CALL DCOPY( NRP1, WORK( ITEMP ), 1, WORK( VLI ), 1 ) ELSE CALL DLASET( 'A', NR, NR, ZERO, ONE, U( NRF, 1 ), LDU ) CALL DLASET( 'A', NRP1, NRP1, ZERO, ONE, VT( NRF, 1 ), LDU ) CALL DLASDQ( 'U', SQREI, NR, NRP1, NR, NCC, D( NRF ), $ E( NRF ), VT( NRF, 1 ), LDU, U( NRF, 1 ), LDU, $ U( NRF, 1 ), LDU, WORK( NWORK1 ), INFO ) CALL DCOPY( NRP1, VT( NRF, 1 ), 1, WORK( VFI ), 1 ) CALL DCOPY( NRP1, VT( NRF, NRP1 ), 1, WORK( VLI ), 1 ) END IF IF( INFO.NE.0 ) THEN RETURN END IF DO 20 J = 1, NR IWORK( IDXQI+J ) = J 20 CONTINUE 30 CONTINUE * * Now conquer each subproblem bottom-up. * J = 2**NLVL DO 50 LVL = NLVL, 1, -1 LVL2 = LVL*2 - 1 * * Find the first node LF and last node LL on * the current level LVL. * IF( LVL.EQ.1 ) THEN LF = 1 LL = 1 ELSE LF = 2**( LVL-1 ) LL = 2*LF - 1 END IF DO 40 I = LF, LL IM1 = I - 1 IC = IWORK( INODE+IM1 ) NL = IWORK( NDIML+IM1 ) NR = IWORK( NDIMR+IM1 ) NLF = IC - NL NRF = IC + 1 IF( I.EQ.LL ) THEN SQREI = SQRE ELSE SQREI = 1 END IF VFI = VF + NLF - 1 VLI = VL + NLF - 1 IDXQI = IDXQ + NLF - 1 ALPHA = D( IC ) BETA = E( IC ) IF( ICOMPQ.EQ.0 ) THEN CALL DLASD6( ICOMPQ, NL, NR, SQREI, D( NLF ), $ WORK( VFI ), WORK( VLI ), ALPHA, BETA, $ IWORK( IDXQI ), PERM, GIVPTR( 1 ), GIVCOL, $ LDGCOL, GIVNUM, LDU, POLES, DIFL, DIFR, Z, $ K( 1 ), C( 1 ), S( 1 ), WORK( NWORK1 ), $ IWORK( IWK ), INFO ) ELSE J = J - 1 CALL DLASD6( ICOMPQ, NL, NR, SQREI, D( NLF ), $ WORK( VFI ), WORK( VLI ), ALPHA, BETA, $ IWORK( IDXQI ), PERM( NLF, LVL ), $ GIVPTR( J ), GIVCOL( NLF, LVL2 ), LDGCOL, $ GIVNUM( NLF, LVL2 ), LDU, $ POLES( NLF, LVL2 ), DIFL( NLF, LVL ), $ DIFR( NLF, LVL2 ), Z( NLF, LVL ), K( J ), $ C( J ), S( J ), WORK( NWORK1 ), $ IWORK( IWK ), INFO ) END IF IF( INFO.NE.0 ) THEN RETURN END IF 40 CONTINUE 50 CONTINUE * RETURN * * End of DLASDA * END SUBROUTINE DLASDT( N, LVL, ND, INODE, NDIML, NDIMR, MSUB ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER LVL, MSUB, N, ND * .. * .. Array Arguments .. INTEGER INODE( * ), NDIML( * ), NDIMR( * ) * .. * * Purpose * ======= * * DLASDT creates a tree of subproblems for bidiagonal divide and * conquer. * * Arguments * ========= * * N (input) INTEGER * On entry, the number of diagonal elements of the * bidiagonal matrix. * * LVL (output) INTEGER * On exit, the number of levels on the computation tree. * * ND (output) INTEGER * On exit, the number of nodes on the tree. * * INODE (output) INTEGER array, dimension ( N ) * On exit, centers of subproblems. * * NDIML (output) INTEGER array, dimension ( N ) * On exit, row dimensions of left children. * * NDIMR (output) INTEGER array, dimension ( N ) * On exit, row dimensions of right children. * * MSUB (input) INTEGER. * On entry, the maximum row dimension each subproblem at the * bottom of the tree can be of. * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION TWO PARAMETER ( TWO = 2.0D+0 ) * .. * .. Local Scalars .. INTEGER I, IL, IR, LLST, MAXN, NCRNT, NLVL DOUBLE PRECISION TEMP * .. * .. Intrinsic Functions .. INTRINSIC DBLE, INT, LOG, MAX * .. * .. Executable Statements .. * * Find the number of levels on the tree. * MAXN = MAX( 1, N ) TEMP = LOG( DBLE( MAXN ) / DBLE( MSUB+1 ) ) / LOG( TWO ) LVL = INT( TEMP ) + 1 * I = N / 2 INODE( 1 ) = I + 1 NDIML( 1 ) = I NDIMR( 1 ) = N - I - 1 IL = 0 IR = 1 LLST = 1 DO 20 NLVL = 1, LVL - 1 * * Constructing the tree at (NLVL+1)-st level. The number of * nodes created on this level is LLST * 2. * DO 10 I = 0, LLST - 1 IL = IL + 2 IR = IR + 2 NCRNT = LLST + I NDIML( IL ) = NDIML( NCRNT ) / 2 NDIMR( IL ) = NDIML( NCRNT ) - NDIML( IL ) - 1 INODE( IL ) = INODE( NCRNT ) - NDIMR( IL ) - 1 NDIML( IR ) = NDIMR( NCRNT ) / 2 NDIMR( IR ) = NDIMR( NCRNT ) - NDIML( IR ) - 1 INODE( IR ) = INODE( NCRNT ) + NDIML( IR ) + 1 10 CONTINUE LLST = LLST*2 20 CONTINUE ND = LLST*2 - 1 * RETURN * * End of DLASDT * END SUBROUTINE DLASD1( NL, NR, SQRE, D, ALPHA, BETA, U, LDU, VT, LDVT, $ IDXQ, IWORK, WORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDU, LDVT, NL, NR, SQRE DOUBLE PRECISION ALPHA, BETA * .. * .. Array Arguments .. INTEGER IDXQ( * ), IWORK( * ) DOUBLE PRECISION D( * ), U( LDU, * ), VT( LDVT, * ), WORK( * ) * .. * * Purpose * ======= * * DLASD1 computes the SVD of an upper bidiagonal N-by-M matrix B, * where N = NL + NR + 1 and M = N + SQRE. DLASD1 is called from DLASD0. * * A related subroutine DLASD7 handles the case in which the singular * values (and the singular vectors in factored form) are desired. * * DLASD1 computes the SVD as follows: * * ( D1(in) 0 0 0 ) * B = U(in) * ( Z1' a Z2' b ) * VT(in) * ( 0 0 D2(in) 0 ) * * = U(out) * ( D(out) 0) * VT(out) * * where Z' = (Z1' a Z2' b) = u' VT', and u is a vector of dimension M * with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros * elsewhere; and the entry b is empty if SQRE = 0. * * The left singular vectors of the original matrix are stored in U, and * the transpose of the right singular vectors are stored in VT, and the * singular values are in D. The algorithm consists of three stages: * * The first stage consists of deflating the size of the problem * when there are multiple singular values or when there are zeros in * the Z vector. For each such occurence the dimension of the * secular equation problem is reduced by one. This stage is * performed by the routine DLASD2. * * The second stage consists of calculating the updated * singular values. This is done by finding the square roots of the * roots of the secular equation via the routine DLASD4 (as called * by DLASD3). This routine also calculates the singular vectors of * the current problem. * * The final stage consists of computing the updated singular vectors * directly using the updated singular values. The singular vectors * for the current problem are multiplied with the singular vectors * from the overall problem. * * Arguments * ========= * * NL (input) INTEGER * The row dimension of the upper block. NL >= 1. * * NR (input) INTEGER * The row dimension of the lower block. NR >= 1. * * SQRE (input) INTEGER * = 0: the lower block is an NR-by-NR square matrix. * = 1: the lower block is an NR-by-(NR+1) rectangular matrix. * * The bidiagonal matrix has row dimension N = NL + NR + 1, * and column dimension M = N + SQRE. * * D (input/output) DOUBLE PRECISION array, * dimension (N = NL+NR+1). * On entry D(1:NL,1:NL) contains the singular values of the * upper block; and D(NL+2:N) contains the singular values of * the lower block. On exit D(1:N) contains the singular values * of the modified matrix. * * ALPHA (input) DOUBLE PRECISION * Contains the diagonal element associated with the added row. * * BETA (input) DOUBLE PRECISION * Contains the off-diagonal element associated with the added * row. * * U (input/output) DOUBLE PRECISION array, dimension(LDU,N) * On entry U(1:NL, 1:NL) contains the left singular vectors of * the upper block; U(NL+2:N, NL+2:N) contains the left singular * vectors of the lower block. On exit U contains the left * singular vectors of the bidiagonal matrix. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= max( 1, N ). * * VT (input/output) DOUBLE PRECISION array, dimension(LDVT,M) * where M = N + SQRE. * On entry VT(1:NL+1, 1:NL+1)' contains the right singular * vectors of the upper block; VT(NL+2:M, NL+2:M)' contains * the right singular vectors of the lower block. On exit * VT' contains the right singular vectors of the * bidiagonal matrix. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= max( 1, M ). * * IDXQ (output) INTEGER array, dimension(N) * This contains the permutation which will reintegrate the * subproblem just solved back into sorted order, i.e. * D( IDXQ( I = 1, N ) ) will be in ascending order. * * IWORK (workspace) INTEGER array, dimension( 4 * N ) * * WORK (workspace) DOUBLE PRECISION array, dimension( 3*M**2 + 2*M ) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. * DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER COLTYP, I, IDX, IDXC, IDXP, IQ, ISIGMA, IU2, $ IVT2, IZ, K, LDQ, LDU2, LDVT2, M, N, N1, N2 DOUBLE PRECISION ORGNRM * .. * .. External Subroutines .. EXTERNAL DLAMRG, DLASCL, DLASD2, DLASD3, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( NL.LT.1 ) THEN INFO = -1 ELSE IF( NR.LT.1 ) THEN INFO = -2 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -3 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD1', -INFO ) RETURN END IF * N = NL + NR + 1 M = N + SQRE * * The following values are for bookkeeping purposes only. They are * integer pointers which indicate the portion of the workspace * used by a particular array in DLASD2 and DLASD3. * LDU2 = N LDVT2 = M * IZ = 1 ISIGMA = IZ + M IU2 = ISIGMA + N IVT2 = IU2 + LDU2*N IQ = IVT2 + LDVT2*M * IDX = 1 IDXC = IDX + N COLTYP = IDXC + N IDXP = COLTYP + N * * Scale. * ORGNRM = MAX( ABS( ALPHA ), ABS( BETA ) ) D( NL+1 ) = ZERO DO 10 I = 1, N IF( ABS( D( I ) ).GT.ORGNRM ) THEN ORGNRM = ABS( D( I ) ) END IF 10 CONTINUE CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, INFO ) ALPHA = ALPHA / ORGNRM BETA = BETA / ORGNRM * * Deflate singular values. * CALL DLASD2( NL, NR, SQRE, K, D, WORK( IZ ), ALPHA, BETA, U, LDU, $ VT, LDVT, WORK( ISIGMA ), WORK( IU2 ), LDU2, $ WORK( IVT2 ), LDVT2, IWORK( IDXP ), IWORK( IDX ), $ IWORK( IDXC ), IDXQ, IWORK( COLTYP ), INFO ) * * Solve Secular Equation and update singular vectors. * LDQ = K CALL DLASD3( NL, NR, SQRE, K, D, WORK( IQ ), LDQ, WORK( ISIGMA ), $ U, LDU, WORK( IU2 ), LDU2, VT, LDVT, WORK( IVT2 ), $ LDVT2, IWORK( IDXC ), IWORK( COLTYP ), WORK( IZ ), $ INFO ) IF( INFO.NE.0 ) THEN RETURN END IF * * Unscale. * CALL DLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, INFO ) * * Prepare the IDXQ sorting permutation. * N1 = K N2 = N - K CALL DLAMRG( N1, N2, D, 1, -1, IDXQ ) * RETURN * * End of DLASD1 * END SUBROUTINE DLASD6( ICOMPQ, NL, NR, SQRE, D, VF, VL, ALPHA, BETA, $ IDXQ, PERM, GIVPTR, GIVCOL, LDGCOL, GIVNUM, $ LDGNUM, POLES, DIFL, DIFR, Z, K, C, S, WORK, $ IWORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER GIVPTR, ICOMPQ, INFO, K, LDGCOL, LDGNUM, NL, $ NR, SQRE DOUBLE PRECISION ALPHA, BETA, C, S * .. * .. Array Arguments .. INTEGER GIVCOL( LDGCOL, * ), IDXQ( * ), IWORK( * ), $ PERM( * ) DOUBLE PRECISION D( * ), DIFL( * ), DIFR( * ), $ GIVNUM( LDGNUM, * ), POLES( LDGNUM, * ), $ VF( * ), VL( * ), WORK( * ), Z( * ) * .. * * Purpose * ======= * * DLASD6 computes the SVD of an updated upper bidiagonal matrix B * obtained by merging two smaller ones by appending a row. This * routine is used only for the problem which requires all singular * values and optionally singular vector matrices in factored form. * B is an N-by-M matrix with N = NL + NR + 1 and M = N + SQRE. * A related subroutine, DLASD1, handles the case in which all singular * values and singular vectors of the bidiagonal matrix are desired. * * DLASD6 computes the SVD as follows: * * ( D1(in) 0 0 0 ) * B = U(in) * ( Z1' a Z2' b ) * VT(in) * ( 0 0 D2(in) 0 ) * * = U(out) * ( D(out) 0) * VT(out) * * where Z' = (Z1' a Z2' b) = u' VT', and u is a vector of dimension M * with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros * elsewhere; and the entry b is empty if SQRE = 0. * * The singular values of B can be computed using D1, D2, the first * components of all the right singular vectors of the lower block, and * the last components of all the right singular vectors of the upper * block. These components are stored and updated in VF and VL, * respectively, in DLASD6. Hence U and VT are not explicitly * referenced. * * The singular values are stored in D. The algorithm consists of two * stages: * * The first stage consists of deflating the size of the problem * when there are multiple singular values or if there is a zero * in the Z vector. For each such occurence the dimension of the * secular equation problem is reduced by one. This stage is * performed by the routine DLASD7. * * The second stage consists of calculating the updated * singular values. This is done by finding the roots of the * secular equation via the routine DLASD4 (as called by DLASD8). * This routine also updates VF and VL and computes the distances * between the updated singular values and the old singular * values. * * DLASD6 is called from DLASDA. * * Arguments * ========= * * ICOMPQ (input) INTEGER * Specifies whether singular vectors are to be computed in * factored form: * = 0: Compute singular values only. * = 1: Compute singular vectors in factored form as well. * * NL (input) INTEGER * The row dimension of the upper block. NL >= 1. * * NR (input) INTEGER * The row dimension of the lower block. NR >= 1. * * SQRE (input) INTEGER * = 0: the lower block is an NR-by-NR square matrix. * = 1: the lower block is an NR-by-(NR+1) rectangular matrix. * * The bidiagonal matrix has row dimension N = NL + NR + 1, * and column dimension M = N + SQRE. * * D (input/output) DOUBLE PRECISION array, dimension ( NL+NR+1 ). * On entry D(1:NL,1:NL) contains the singular values of the * upper block, and D(NL+2:N) contains the singular values * of the lower block. On exit D(1:N) contains the singular * values of the modified matrix. * * VF (input/output) DOUBLE PRECISION array, dimension ( M ) * On entry, VF(1:NL+1) contains the first components of all * right singular vectors of the upper block; and VF(NL+2:M) * contains the first components of all right singular vectors * of the lower block. On exit, VF contains the first components * of all right singular vectors of the bidiagonal matrix. * * VL (input/output) DOUBLE PRECISION array, dimension ( M ) * On entry, VL(1:NL+1) contains the last components of all * right singular vectors of the upper block; and VL(NL+2:M) * contains the last components of all right singular vectors of * the lower block. On exit, VL contains the last components of * all right singular vectors of the bidiagonal matrix. * * ALPHA (input) DOUBLE PRECISION * Contains the diagonal element associated with the added row. * * BETA (input) DOUBLE PRECISION * Contains the off-diagonal element associated with the added * row. * * IDXQ (output) INTEGER array, dimension ( N ) * This contains the permutation which will reintegrate the * subproblem just solved back into sorted order, i.e. * D( IDXQ( I = 1, N ) ) will be in ascending order. * * PERM (output) INTEGER array, dimension ( N ) * The permutations (from deflation and sorting) to be applied * to each block. Not referenced if ICOMPQ = 0. * * GIVPTR (output) INTEGER * The number of Givens rotations which took place in this * subproblem. Not referenced if ICOMPQ = 0. * * GIVCOL (output) INTEGER array, dimension ( LDGCOL, 2 ) * Each pair of numbers indicates a pair of columns to take place * in a Givens rotation. Not referenced if ICOMPQ = 0. * * LDGCOL (input) INTEGER * leading dimension of GIVCOL, must be at least N. * * GIVNUM (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 ) * Each number indicates the C or S value to be used in the * corresponding Givens rotation. Not referenced if ICOMPQ = 0. * * LDGNUM (input) INTEGER * The leading dimension of GIVNUM and POLES, must be at least N. * * POLES (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 ) * On exit, POLES(1,*) is an array containing the new singular * values obtained from solving the secular equation, and * POLES(2,*) is an array containing the poles in the secular * equation. Not referenced if ICOMPQ = 0. * * DIFL (output) DOUBLE PRECISION array, dimension ( N ) * On exit, DIFL(I) is the distance between I-th updated * (undeflated) singular value and the I-th (undeflated) old * singular value. * * DIFR (output) DOUBLE PRECISION array, * dimension ( LDGNUM, 2 ) if ICOMPQ = 1 and * dimension ( N ) if ICOMPQ = 0. * On exit, DIFR(I, 1) is the distance between I-th updated * (undeflated) singular value and the I+1-th (undeflated) old * singular value. * * If ICOMPQ = 1, DIFR(1:K,2) is an array containing the * normalizing factors for the right singular vector matrix. * * See DLASD8 for details on DIFL and DIFR. * * Z (output) DOUBLE PRECISION array, dimension ( M ) * The first elements of this array contain the components * of the deflation-adjusted updating row vector. * * K (output) INTEGER * Contains the dimension of the non-deflated matrix, * This is the order of the related secular equation. 1 <= K <=N. * * C (output) DOUBLE PRECISION * C contains garbage if SQRE =0 and the C-value of a Givens * rotation related to the right null space if SQRE = 1. * * S (output) DOUBLE PRECISION * S contains garbage if SQRE =0 and the S-value of a Givens * rotation related to the right null space if SQRE = 1. * * WORK (workspace) DOUBLE PRECISION array, dimension ( 4 * M ) * * IWORK (workspace) INTEGER array, dimension ( 3 * N ) * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER I, IDX, IDXC, IDXP, ISIGMA, IVFW, IVLW, IW, M, $ N, N1, N2 DOUBLE PRECISION ORGNRM * .. * .. External Subroutines .. EXTERNAL DCOPY, DLAMRG, DLASCL, DLASD7, DLASD8, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 N = NL + NR + 1 M = N + SQRE * IF( ( ICOMPQ.LT.0 ) .OR. ( ICOMPQ.GT.1 ) ) THEN INFO = -1 ELSE IF( NL.LT.1 ) THEN INFO = -2 ELSE IF( NR.LT.1 ) THEN INFO = -3 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -4 ELSE IF( LDGCOL.LT.N ) THEN INFO = -14 ELSE IF( LDGNUM.LT.N ) THEN INFO = -16 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD6', -INFO ) RETURN END IF * * The following values are for bookkeeping purposes only. They are * integer pointers which indicate the portion of the workspace * used by a particular array in DLASD7 and DLASD8. * ISIGMA = 1 IW = ISIGMA + N IVFW = IW + M IVLW = IVFW + M * IDX = 1 IDXC = IDX + N IDXP = IDXC + N * * Scale. * ORGNRM = MAX( ABS( ALPHA ), ABS( BETA ) ) D( NL+1 ) = ZERO DO 10 I = 1, N IF( ABS( D( I ) ).GT.ORGNRM ) THEN ORGNRM = ABS( D( I ) ) END IF 10 CONTINUE CALL DLASCL( 'G', 0, 0, ORGNRM, ONE, N, 1, D, N, INFO ) ALPHA = ALPHA / ORGNRM BETA = BETA / ORGNRM * * Sort and Deflate singular values. * CALL DLASD7( ICOMPQ, NL, NR, SQRE, K, D, Z, WORK( IW ), VF, $ WORK( IVFW ), VL, WORK( IVLW ), ALPHA, BETA, $ WORK( ISIGMA ), IWORK( IDX ), IWORK( IDXP ), IDXQ, $ PERM, GIVPTR, GIVCOL, LDGCOL, GIVNUM, LDGNUM, C, S, $ INFO ) * * Solve Secular Equation, compute DIFL, DIFR, and update VF, VL. * CALL DLASD8( ICOMPQ, K, D, Z, VF, VL, DIFL, DIFR, LDGNUM, $ WORK( ISIGMA ), WORK( IW ), INFO ) * * Save the poles if ICOMPQ = 1. * IF( ICOMPQ.EQ.1 ) THEN CALL DCOPY( K, D, 1, POLES( 1, 1 ), 1 ) CALL DCOPY( K, WORK( ISIGMA ), 1, POLES( 1, 2 ), 1 ) END IF * * Unscale. * CALL DLASCL( 'G', 0, 0, ONE, ORGNRM, N, 1, D, N, INFO ) * * Prepare the IDXQ sorting permutation. * N1 = K N2 = N - K CALL DLAMRG( N1, N2, D, 1, -1, IDXQ ) * RETURN * * End of DLASD6 * END SUBROUTINE DLASD2( NL, NR, SQRE, K, D, Z, ALPHA, BETA, U, LDU, VT, $ LDVT, DSIGMA, U2, LDU2, VT2, LDVT2, IDXP, IDX, $ IDXC, IDXQ, COLTYP, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * October 31, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDU, LDU2, LDVT, LDVT2, NL, NR, SQRE DOUBLE PRECISION ALPHA, BETA * .. * .. Array Arguments .. INTEGER COLTYP( * ), IDX( * ), IDXC( * ), IDXP( * ), $ IDXQ( * ) DOUBLE PRECISION D( * ), DSIGMA( * ), U( LDU, * ), $ U2( LDU2, * ), VT( LDVT, * ), VT2( LDVT2, * ), $ Z( * ) * .. * * Purpose * ======= * * DLASD2 merges the two sets of singular values together into a single * sorted set. Then it tries to deflate the size of the problem. * There are two ways in which deflation can occur: when two or more * singular values are close together or if there is a tiny entry in the * Z vector. For each such occurrence the order of the related secular * equation problem is reduced by one. * * DLASD2 is called from DLASD1. * * Arguments * ========= * * NL (input) INTEGER * The row dimension of the upper block. NL >= 1. * * NR (input) INTEGER * The row dimension of the lower block. NR >= 1. * * SQRE (input) INTEGER * = 0: the lower block is an NR-by-NR square matrix. * = 1: the lower block is an NR-by-(NR+1) rectangular matrix. * * The bidiagonal matrix has N = NL + NR + 1 rows and * M = N + SQRE >= N columns. * * K (output) INTEGER * Contains the dimension of the non-deflated matrix, * This is the order of the related secular equation. 1 <= K <=N. * * D (input/output) DOUBLE PRECISION array, dimension(N) * On entry D contains the singular values of the two submatrices * to be combined. On exit D contains the trailing (N-K) updated * singular values (those which were deflated) sorted into * increasing order. * * ALPHA (input) DOUBLE PRECISION * Contains the diagonal element associated with the added row. * * BETA (input) DOUBLE PRECISION * Contains the off-diagonal element associated with the added * row. * * U (input/output) DOUBLE PRECISION array, dimension(LDU,N) * On entry U contains the left singular vectors of two * submatrices in the two square blocks with corners at (1,1), * (NL, NL), and (NL+2, NL+2), (N,N). * On exit U contains the trailing (N-K) updated left singular * vectors (those which were deflated) in its last N-K columns. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= N. * * Z (output) DOUBLE PRECISION array, dimension(N) * On exit Z contains the updating row vector in the secular * equation. * * DSIGMA (output) DOUBLE PRECISION array, dimension (N) * Contains a copy of the diagonal elements (K-1 singular values * and one zero) in the secular equation. * * U2 (output) DOUBLE PRECISION array, dimension(LDU2,N) * Contains a copy of the first K-1 left singular vectors which * will be used by DLASD3 in a matrix multiply (DGEMM) to solve * for the new left singular vectors. U2 is arranged into four * blocks. The first block contains a column with 1 at NL+1 and * zero everywhere else; the second block contains non-zero * entries only at and above NL; the third contains non-zero * entries only below NL+1; and the fourth is dense. * * LDU2 (input) INTEGER * The leading dimension of the array U2. LDU2 >= N. * * VT (input/output) DOUBLE PRECISION array, dimension(LDVT,M) * On entry VT' contains the right singular vectors of two * submatrices in the two square blocks with corners at (1,1), * (NL+1, NL+1), and (NL+2, NL+2), (M,M). * On exit VT' contains the trailing (N-K) updated right singular * vectors (those which were deflated) in its last N-K columns. * In case SQRE =1, the last row of VT spans the right null * space. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= M. * * VT2 (output) DOUBLE PRECISION array, dimension(LDVT2,N) * VT2' contains a copy of the first K right singular vectors * which will be used by DLASD3 in a matrix multiply (DGEMM) to * solve for the new right singular vectors. VT2 is arranged into * three blocks. The first block contains a row that corresponds * to the special 0 diagonal element in SIGMA; the second block * contains non-zeros only at and before NL +1; the third block * contains non-zeros only at and after NL +2. * * LDVT2 (input) INTEGER * The leading dimension of the array VT2. LDVT2 >= M. * * IDXP (workspace) INTEGER array, dimension(N) * This will contain the permutation used to place deflated * values of D at the end of the array. On output IDXP(2:K) * points to the nondeflated D-values and IDXP(K+1:N) * points to the deflated singular values. * * IDX (workspace) INTEGER array, dimension(N) * This will contain the permutation used to sort the contents of * D into ascending order. * * IDXC (output) INTEGER array, dimension(N) * This will contain the permutation used to arrange the columns * of the deflated U matrix into three groups: the first group * contains non-zero entries only at and above NL, the second * contains non-zero entries only below NL+2, and the third is * dense. * * COLTYP (workspace/output) INTEGER array, dimension(N) * As workspace, this will contain a label which will indicate * which of the following types a column in the U2 matrix or a * row in the VT2 matrix is: * 1 : non-zero in the upper half only * 2 : non-zero in the lower half only * 3 : dense * 4 : deflated * * On exit, it is an array of dimension 4, with COLTYP(I) being * the dimension of the I-th type columns. * * IDXQ (input) INTEGER array, dimension(N) * This contains the permutation which separately sorts the two * sub-problems in D into ascending order. Note that entries in * the first hlaf of this permutation must first be moved one * position backward; and entries in the second half * must first have NL+1 added to their values. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * 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, EIGHT PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0, $ EIGHT = 8.0D+0 ) * .. * .. Local Arrays .. INTEGER CTOT( 4 ), PSM( 4 ) * .. * .. Local Scalars .. INTEGER CT, I, IDXI, IDXJ, IDXJP, J, JP, JPREV, K2, M, $ N, NLP1, NLP2 DOUBLE PRECISION C, EPS, HLFTOL, S, TAU, TOL, Z1 * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLAPY2 EXTERNAL DLAMCH, DLAPY2 * .. * .. External Subroutines .. EXTERNAL DCOPY, DLACPY, DLAMRG, DLASET, DROT, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( NL.LT.1 ) THEN INFO = -1 ELSE IF( NR.LT.1 ) THEN INFO = -2 ELSE IF( ( SQRE.NE.1 ) .AND. ( SQRE.NE.0 ) ) THEN INFO = -3 END IF * N = NL + NR + 1 M = N + SQRE * IF( LDU.LT.N ) THEN INFO = -10 ELSE IF( LDVT.LT.M ) THEN INFO = -12 ELSE IF( LDU2.LT.N ) THEN INFO = -15 ELSE IF( LDVT2.LT.M ) THEN INFO = -17 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD2', -INFO ) RETURN END IF * NLP1 = NL + 1 NLP2 = NL + 2 * * Generate the first part of the vector Z; and move the singular * values in the first part of D one position backward. * Z1 = ALPHA*VT( NLP1, NLP1 ) Z( 1 ) = Z1 DO 10 I = NL, 1, -1 Z( I+1 ) = ALPHA*VT( I, NLP1 ) D( I+1 ) = D( I ) IDXQ( I+1 ) = IDXQ( I ) + 1 10 CONTINUE * * Generate the second part of the vector Z. * DO 20 I = NLP2, M Z( I ) = BETA*VT( I, NLP2 ) 20 CONTINUE * * Initialize some reference arrays. * DO 30 I = 2, NLP1 COLTYP( I ) = 1 30 CONTINUE DO 40 I = NLP2, N COLTYP( I ) = 2 40 CONTINUE * * Sort the singular values into increasing order * DO 50 I = NLP2, N IDXQ( I ) = IDXQ( I ) + NLP1 50 CONTINUE * * DSIGMA, IDXC, IDXC, and the first column of U2 * are used as storage space. * DO 60 I = 2, N DSIGMA( I ) = D( IDXQ( I ) ) U2( I, 1 ) = Z( IDXQ( I ) ) IDXC( I ) = COLTYP( IDXQ( I ) ) 60 CONTINUE * CALL DLAMRG( NL, NR, DSIGMA( 2 ), 1, 1, IDX( 2 ) ) * DO 70 I = 2, N IDXI = 1 + IDX( I ) D( I ) = DSIGMA( IDXI ) Z( I ) = U2( IDXI, 1 ) COLTYP( I ) = IDXC( IDXI ) 70 CONTINUE * * Calculate the allowable deflation tolerance * EPS = DLAMCH( 'Epsilon' ) TOL = MAX( ABS( ALPHA ), ABS( BETA ) ) TOL = EIGHT*EPS*MAX( ABS( D( N ) ), TOL ) * * There are 2 kinds of deflation -- first a value in the z-vector * is small, second two (or more) singular values are very close * together (their difference is small). * * If the value in the z-vector is small, we simply permute the * array so that the corresponding singular value is moved to the * end. * * If two values in the D-vector are close, we perform a two-sided * rotation designed to make one of the corresponding z-vector * entries zero, and then permute the array so that the deflated * singular value is moved to the end. * * If there are multiple singular values then the problem deflates. * Here the number of equal singular values are found. As each equal * singular value is found, an elementary reflector is computed to * rotate the corresponding singular subspace so that the * corresponding components of Z are zero in this new basis. * K = 1 K2 = N + 1 DO 80 J = 2, N IF( ABS( Z( J ) ).LE.TOL ) THEN * * Deflate due to small z component. * K2 = K2 - 1 IDXP( K2 ) = J COLTYP( J ) = 4 IF( J.EQ.N ) $ GO TO 120 ELSE JPREV = J GO TO 90 END IF 80 CONTINUE 90 CONTINUE J = JPREV 100 CONTINUE J = J + 1 IF( J.GT.N ) $ GO TO 110 IF( ABS( Z( J ) ).LE.TOL ) THEN * * Deflate due to small z component. * K2 = K2 - 1 IDXP( K2 ) = J COLTYP( J ) = 4 ELSE * * Check if singular values are close enough to allow deflation. * IF( ABS( D( J )-D( JPREV ) ).LE.TOL ) THEN * * Deflation is possible. * S = Z( JPREV ) C = Z( J ) * * Find sqrt(a**2+b**2) without overflow or * destructive underflow. * TAU = DLAPY2( C, S ) C = C / TAU S = -S / TAU Z( J ) = TAU Z( JPREV ) = ZERO * * Apply back the Givens rotation to the left and right * singular vector matrices. * IDXJP = IDXQ( IDX( JPREV )+1 ) IDXJ = IDXQ( IDX( J )+1 ) IF( IDXJP.LE.NLP1 ) THEN IDXJP = IDXJP - 1 END IF IF( IDXJ.LE.NLP1 ) THEN IDXJ = IDXJ - 1 END IF CALL DROT( N, U( 1, IDXJP ), 1, U( 1, IDXJ ), 1, C, S ) CALL DROT( M, VT( IDXJP, 1 ), LDVT, VT( IDXJ, 1 ), LDVT, C, $ S ) IF( COLTYP( J ).NE.COLTYP( JPREV ) ) THEN COLTYP( J ) = 3 END IF COLTYP( JPREV ) = 4 K2 = K2 - 1 IDXP( K2 ) = JPREV JPREV = J ELSE K = K + 1 U2( K, 1 ) = Z( JPREV ) DSIGMA( K ) = D( JPREV ) IDXP( K ) = JPREV JPREV = J END IF END IF GO TO 100 110 CONTINUE * * Record the last singular value. * K = K + 1 U2( K, 1 ) = Z( JPREV ) DSIGMA( K ) = D( JPREV ) IDXP( K ) = JPREV * 120 CONTINUE * * Count up the total number of the various types of columns, then * form a permutation which positions the four column types into * four groups of uniform structure (although one or more of these * groups may be empty). * DO 130 J = 1, 4 CTOT( J ) = 0 130 CONTINUE DO 140 J = 2, N CT = COLTYP( J ) CTOT( CT ) = CTOT( CT ) + 1 140 CONTINUE * * PSM(*) = Position in SubMatrix (of types 1 through 4) * PSM( 1 ) = 2 PSM( 2 ) = 2 + CTOT( 1 ) PSM( 3 ) = PSM( 2 ) + CTOT( 2 ) PSM( 4 ) = PSM( 3 ) + CTOT( 3 ) * * Fill out the IDXC array so that the permutation which it induces * will place all type-1 columns first, all type-2 columns next, * then all type-3's, and finally all type-4's, starting from the * second column. This applies similarly to the rows of VT. * DO 150 J = 2, N JP = IDXP( J ) CT = COLTYP( JP ) IDXC( PSM( CT ) ) = J PSM( CT ) = PSM( CT ) + 1 150 CONTINUE * * Sort the singular values and corresponding singular vectors into * DSIGMA, U2, and VT2 respectively. The singular values/vectors * which were not deflated go into the first K slots of DSIGMA, U2, * and VT2 respectively, while those which were deflated go into the * last N - K slots, except that the first column/row will be treated * separately. * DO 160 J = 2, N JP = IDXP( J ) DSIGMA( J ) = D( JP ) IDXJ = IDXQ( IDX( IDXP( IDXC( J ) ) )+1 ) IF( IDXJ.LE.NLP1 ) THEN IDXJ = IDXJ - 1 END IF CALL DCOPY( N, U( 1, IDXJ ), 1, U2( 1, J ), 1 ) CALL DCOPY( M, VT( IDXJ, 1 ), LDVT, VT2( J, 1 ), LDVT2 ) 160 CONTINUE * * Determine DSIGMA(1), DSIGMA(2) and Z(1) * DSIGMA( 1 ) = ZERO HLFTOL = TOL / TWO IF( ABS( DSIGMA( 2 ) ).LE.HLFTOL ) $ DSIGMA( 2 ) = HLFTOL IF( M.GT.N ) THEN Z( 1 ) = DLAPY2( Z1, Z( M ) ) IF( Z( 1 ).LE.TOL ) THEN C = ONE S = ZERO Z( 1 ) = TOL ELSE C = Z1 / Z( 1 ) S = Z( M ) / Z( 1 ) END IF ELSE IF( ABS( Z1 ).LE.TOL ) THEN Z( 1 ) = TOL ELSE Z( 1 ) = Z1 END IF END IF * * Move the rest of the updating row to Z. * CALL DCOPY( K-1, U2( 2, 1 ), 1, Z( 2 ), 1 ) * * Determine the first column of U2, the first row of VT2 and the * last row of VT. * CALL DLASET( 'A', N, 1, ZERO, ZERO, U2, LDU2 ) U2( NLP1, 1 ) = ONE IF( M.GT.N ) THEN DO 170 I = 1, NLP1 VT( M, I ) = -S*VT( NLP1, I ) VT2( 1, I ) = C*VT( NLP1, I ) 170 CONTINUE DO 180 I = NLP2, M VT2( 1, I ) = S*VT( M, I ) VT( M, I ) = C*VT( M, I ) 180 CONTINUE ELSE CALL DCOPY( M, VT( NLP1, 1 ), LDVT, VT2( 1, 1 ), LDVT2 ) END IF IF( M.GT.N ) THEN CALL DCOPY( M, VT( M, 1 ), LDVT, VT2( M, 1 ), LDVT2 ) END IF * * The deflated singular values and their corresponding vectors go * into the back of D, U, and V respectively. * IF( N.GT.K ) THEN CALL DCOPY( N-K, DSIGMA( K+1 ), 1, D( K+1 ), 1 ) CALL DLACPY( 'A', N, N-K, U2( 1, K+1 ), LDU2, U( 1, K+1 ), $ LDU ) CALL DLACPY( 'A', N-K, M, VT2( K+1, 1 ), LDVT2, VT( K+1, 1 ), $ LDVT ) END IF * * Copy CTOT into COLTYP for referencing in DLASD3. * DO 190 J = 1, 4 COLTYP( J ) = CTOT( J ) 190 CONTINUE * RETURN * * End of DLASD2 * END SUBROUTINE DLASD3( NL, NR, SQRE, K, D, Q, LDQ, DSIGMA, U, LDU, U2, $ LDU2, VT, LDVT, VT2, LDVT2, IDXC, CTOT, Z, $ INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * October 31, 1999 * * .. Scalar Arguments .. INTEGER INFO, K, LDQ, LDU, LDU2, LDVT, LDVT2, NL, NR, $ SQRE * .. * .. Array Arguments .. INTEGER CTOT( * ), IDXC( * ) DOUBLE PRECISION D( * ), DSIGMA( * ), Q( LDQ, * ), U( LDU, * ), $ U2( LDU2, * ), VT( LDVT, * ), VT2( LDVT2, * ), $ Z( * ) * .. * * Purpose * ======= * * DLASD3 finds all the square roots of the roots of the secular * equation, as defined by the values in D and Z. It makes the * appropriate calls to DLASD4 and then updates the singular * vectors by matrix multiplication. * * 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. * * DLASD3 is called from DLASD1. * * Arguments * ========= * * NL (input) INTEGER * The row dimension of the upper block. NL >= 1. * * NR (input) INTEGER * The row dimension of the lower block. NR >= 1. * * SQRE (input) INTEGER * = 0: the lower block is an NR-by-NR square matrix. * = 1: the lower block is an NR-by-(NR+1) rectangular matrix. * * The bidiagonal matrix has N = NL + NR + 1 rows and * M = N + SQRE >= N columns. * * K (input) INTEGER * The size of the secular equation, 1 =< K = < N. * * D (output) DOUBLE PRECISION array, dimension(K) * On exit the square roots of the roots of the secular equation, * in ascending order. * * Q (workspace) DOUBLE PRECISION array, * dimension at least (LDQ,K). * * LDQ (input) INTEGER * The leading dimension of the array Q. LDQ >= K. * * DSIGMA (input) DOUBLE PRECISION array, dimension(K) * The first K elements of this array contain the old roots * of the deflated updating problem. These are the poles * of the secular equation. * * U (input) DOUBLE PRECISION array, dimension (LDU, N) * The last N - K columns of this matrix contain the deflated * left singular vectors. * * LDU (input) INTEGER * The leading dimension of the array U. LDU >= N. * * U2 (input) DOUBLE PRECISION array, dimension (LDU2, N) * The first K columns of this matrix contain the non-deflated * left singular vectors for the split problem. * * LDU2 (input) INTEGER * The leading dimension of the array U2. LDU2 >= N. * * VT (input) DOUBLE PRECISION array, dimension (LDVT, M) * The last M - K columns of VT' contain the deflated * right singular vectors. * * LDVT (input) INTEGER * The leading dimension of the array VT. LDVT >= N. * * VT2 (input) DOUBLE PRECISION array, dimension (LDVT2, N) * The first K columns of VT2' contain the non-deflated * right singular vectors for the split problem. * * LDVT2 (input) INTEGER * The leading dimension of the array VT2. LDVT2 >= N. * * IDXC (input) INTEGER array, dimension ( N ) * The permutation used to arrange the columns of U (and rows of * VT) into three groups: the first group contains non-zero * entries only at and above (or before) NL +1; the second * contains non-zero entries only at and below (or after) NL+2; * and the third is dense. The first column of U and the row of * VT are treated separately, however. * * The rows of the singular vectors found by DLASD4 * must be likewise permuted before the matrix multiplies can * take place. * * CTOT (input) INTEGER array, dimension ( 4 ) * A count of the total number of the various types of columns * in U (or rows in VT), as described in IDXC. The fourth column * type is any column which has been deflated. * * Z (input) DOUBLE PRECISION array, dimension (K) * The first K elements of this array contain the components * of the deflation-adjusted updating row vector. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO, NEGONE PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0, $ NEGONE = -1.0D+0 ) * .. * .. Local Scalars .. INTEGER CTEMP, I, J, JC, KTEMP, M, N, NLP1, NLP2, NRP1 DOUBLE PRECISION RHO, TEMP * .. * .. External Functions .. DOUBLE PRECISION DLAMC3, DNRM2 EXTERNAL DLAMC3, DNRM2 * .. * .. External Subroutines .. EXTERNAL DCOPY, DGEMM, DLACPY, DLASCL, DLASD4, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( NL.LT.1 ) THEN INFO = -1 ELSE IF( NR.LT.1 ) THEN INFO = -2 ELSE IF( ( SQRE.NE.1 ) .AND. ( SQRE.NE.0 ) ) THEN INFO = -3 END IF * N = NL + NR + 1 M = N + SQRE NLP1 = NL + 1 NLP2 = NL + 2 * IF( ( K.LT.1 ) .OR. ( K.GT.N ) ) THEN INFO = -4 ELSE IF( LDQ.LT.K ) THEN INFO = -7 ELSE IF( LDU.LT.N ) THEN INFO = -10 ELSE IF( LDU2.LT.N ) THEN INFO = -12 ELSE IF( LDVT.LT.M ) THEN INFO = -14 ELSE IF( LDVT2.LT.M ) THEN INFO = -16 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD3', -INFO ) RETURN END IF * * Quick return if possible * IF( K.EQ.1 ) THEN D( 1 ) = ABS( Z( 1 ) ) CALL DCOPY( M, VT2( 1, 1 ), LDVT2, VT( 1, 1 ), LDVT ) IF( Z( 1 ).GT.ZERO ) THEN CALL DCOPY( N, U2( 1, 1 ), 1, U( 1, 1 ), 1 ) ELSE DO 10 I = 1, N U( I, 1 ) = -U2( I, 1 ) 10 CONTINUE END IF RETURN END IF * * Modify values DSIGMA(i) to make sure all DSIGMA(i)-DSIGMA(j) can * be computed with high relative accuracy (barring over/underflow). * This is a problem on machines without a guard digit in * add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2). * The following code replaces DSIGMA(I) by 2*DSIGMA(I)-DSIGMA(I), * which on any of these machines zeros out the bottommost * bit of DSIGMA(I) if it is 1; this makes the subsequent * subtractions DSIGMA(I)-DSIGMA(J) unproblematic when cancellation * occurs. On binary machines with a guard digit (almost all * machines) it does not change DSIGMA(I) at all. On hexadecimal * and decimal machines with a guard digit, it slightly * changes the bottommost bits of DSIGMA(I). It does not account * for hexadecimal or decimal machines without guard digits * (we know of none). We use a subroutine call to compute * 2*DLAMBDA(I) to prevent optimizing compilers from eliminating * this code. * DO 20 I = 1, K DSIGMA( I ) = DLAMC3( DSIGMA( I ), DSIGMA( I ) ) - DSIGMA( I ) 20 CONTINUE * * Keep a copy of Z. * CALL DCOPY( K, Z, 1, Q, 1 ) * * Normalize Z. * RHO = DNRM2( K, Z, 1 ) CALL DLASCL( 'G', 0, 0, RHO, ONE, K, 1, Z, K, INFO ) RHO = RHO*RHO * * Find the new singular values. * DO 30 J = 1, K CALL DLASD4( K, J, DSIGMA, Z, U( 1, J ), RHO, D( J ), $ VT( 1, J ), INFO ) * * If the zero finder fails, the computation is terminated. * IF( INFO.NE.0 ) THEN RETURN END IF 30 CONTINUE * * Compute updated Z. * DO 60 I = 1, K Z( I ) = U( I, K )*VT( I, K ) DO 40 J = 1, I - 1 Z( I ) = Z( I )*( U( I, J )*VT( I, J ) / $ ( DSIGMA( I )-DSIGMA( J ) ) / $ ( DSIGMA( I )+DSIGMA( J ) ) ) 40 CONTINUE DO 50 J = I, K - 1 Z( I ) = Z( I )*( U( I, J )*VT( I, J ) / $ ( DSIGMA( I )-DSIGMA( J+1 ) ) / $ ( DSIGMA( I )+DSIGMA( J+1 ) ) ) 50 CONTINUE Z( I ) = SIGN( SQRT( ABS( Z( I ) ) ), Q( I, 1 ) ) 60 CONTINUE * * Compute left singular vectors of the modified diagonal matrix, * and store related information for the right singular vectors. * DO 90 I = 1, K VT( 1, I ) = Z( 1 ) / U( 1, I ) / VT( 1, I ) U( 1, I ) = NEGONE DO 70 J = 2, K VT( J, I ) = Z( J ) / U( J, I ) / VT( J, I ) U( J, I ) = DSIGMA( J )*VT( J, I ) 70 CONTINUE TEMP = DNRM2( K, U( 1, I ), 1 ) Q( 1, I ) = U( 1, I ) / TEMP DO 80 J = 2, K JC = IDXC( J ) Q( J, I ) = U( JC, I ) / TEMP 80 CONTINUE 90 CONTINUE * * Update the left singular vector matrix. * IF( K.EQ.2 ) THEN CALL DGEMM( 'N', 'N', N, K, K, ONE, U2, LDU2, Q, LDQ, ZERO, U, $ LDU ) GO TO 100 END IF IF( CTOT( 1 ).GT.0 ) THEN CALL DGEMM( 'N', 'N', NL, K, CTOT( 1 ), ONE, U2( 1, 2 ), LDU2, $ Q( 2, 1 ), LDQ, ZERO, U( 1, 1 ), LDU ) IF( CTOT( 3 ).GT.0 ) THEN KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) CALL DGEMM( 'N', 'N', NL, K, CTOT( 3 ), ONE, U2( 1, KTEMP ), $ LDU2, Q( KTEMP, 1 ), LDQ, ONE, U( 1, 1 ), LDU ) END IF ELSE IF( CTOT( 3 ).GT.0 ) THEN KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) CALL DGEMM( 'N', 'N', NL, K, CTOT( 3 ), ONE, U2( 1, KTEMP ), $ LDU2, Q( KTEMP, 1 ), LDQ, ZERO, U( 1, 1 ), LDU ) ELSE CALL DLACPY( 'F', NL, K, U2, LDU2, U, LDU ) END IF CALL DCOPY( K, Q( 1, 1 ), LDQ, U( NLP1, 1 ), LDU ) KTEMP = 2 + CTOT( 1 ) CTEMP = CTOT( 2 ) + CTOT( 3 ) CALL DGEMM( 'N', 'N', NR, K, CTEMP, ONE, U2( NLP2, KTEMP ), LDU2, $ Q( KTEMP, 1 ), LDQ, ZERO, U( NLP2, 1 ), LDU ) * * Generate the right singular vectors. * 100 CONTINUE DO 120 I = 1, K TEMP = DNRM2( K, VT( 1, I ), 1 ) Q( I, 1 ) = VT( 1, I ) / TEMP DO 110 J = 2, K JC = IDXC( J ) Q( I, J ) = VT( JC, I ) / TEMP 110 CONTINUE 120 CONTINUE * * Update the right singular vector matrix. * IF( K.EQ.2 ) THEN CALL DGEMM( 'N', 'N', K, M, K, ONE, Q, LDQ, VT2, LDVT2, ZERO, $ VT, LDVT ) RETURN END IF KTEMP = 1 + CTOT( 1 ) CALL DGEMM( 'N', 'N', K, NLP1, KTEMP, ONE, Q( 1, 1 ), LDQ, $ VT2( 1, 1 ), LDVT2, ZERO, VT( 1, 1 ), LDVT ) KTEMP = 2 + CTOT( 1 ) + CTOT( 2 ) IF( KTEMP.LE.LDVT2 ) $ CALL DGEMM( 'N', 'N', K, NLP1, CTOT( 3 ), ONE, Q( 1, KTEMP ), $ LDQ, VT2( KTEMP, 1 ), LDVT2, ONE, VT( 1, 1 ), $ LDVT ) * KTEMP = CTOT( 1 ) + 1 NRP1 = NR + SQRE IF( KTEMP.GT.1 ) THEN DO 130 I = 1, K Q( I, KTEMP ) = Q( I, 1 ) 130 CONTINUE DO 140 I = NLP2, M VT2( KTEMP, I ) = VT2( 1, I ) 140 CONTINUE END IF CTEMP = 1 + CTOT( 2 ) + CTOT( 3 ) CALL DGEMM( 'N', 'N', K, NRP1, CTEMP, ONE, Q( 1, KTEMP ), LDQ, $ VT2( KTEMP, NLP2 ), LDVT2, ZERO, VT( 1, NLP2 ), LDVT ) * RETURN * * End of DLASD3 * END SUBROUTINE DLASD7( ICOMPQ, NL, NR, SQRE, K, D, Z, ZW, VF, VFW, VL, $ VLW, ALPHA, BETA, DSIGMA, IDX, IDXP, IDXQ, $ PERM, GIVPTR, GIVCOL, LDGCOL, GIVNUM, LDGNUM, $ C, S, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER GIVPTR, ICOMPQ, INFO, K, LDGCOL, LDGNUM, NL, $ NR, SQRE DOUBLE PRECISION ALPHA, BETA, C, S * .. * .. Array Arguments .. INTEGER GIVCOL( LDGCOL, * ), IDX( * ), IDXP( * ), $ IDXQ( * ), PERM( * ) DOUBLE PRECISION D( * ), DSIGMA( * ), GIVNUM( LDGNUM, * ), $ VF( * ), VFW( * ), VL( * ), VLW( * ), Z( * ), $ ZW( * ) * .. * * Purpose * ======= * * DLASD7 merges the two sets of singular values together into a single * sorted set. Then it tries to deflate the size of the problem. There * are two ways in which deflation can occur: when two or more singular * values are close together or if there is a tiny entry in the Z * vector. For each such occurrence the order of the related * secular equation problem is reduced by one. * * DLASD7 is called from DLASD6. * * Arguments * ========= * * ICOMPQ (input) INTEGER * Specifies whether singular vectors are to be computed * in compact form, as follows: * = 0: Compute singular values only. * = 1: Compute singular vectors of upper * bidiagonal matrix in compact form. * * NL (input) INTEGER * The row dimension of the upper block. NL >= 1. * * NR (input) INTEGER * The row dimension of the lower block. NR >= 1. * * SQRE (input) INTEGER * = 0: the lower block is an NR-by-NR square matrix. * = 1: the lower block is an NR-by-(NR+1) rectangular matrix. * * The bidiagonal matrix has * N = NL + NR + 1 rows and * M = N + SQRE >= N columns. * * K (output) INTEGER * Contains the dimension of the non-deflated matrix, this is * the order of the related secular equation. 1 <= K <=N. * * D (input/output) DOUBLE PRECISION array, dimension ( N ) * On entry D contains the singular values of the two submatrices * to be combined. On exit D contains the trailing (N-K) updated * singular values (those which were deflated) sorted into * increasing order. * * Z (output) DOUBLE PRECISION array, dimension ( M ) * On exit Z contains the updating row vector in the secular * equation. * * ZW (workspace) DOUBLE PRECISION array, dimension ( M ) * Workspace for Z. * * VF (input/output) DOUBLE PRECISION array, dimension ( M ) * On entry, VF(1:NL+1) contains the first components of all * right singular vectors of the upper block; and VF(NL+2:M) * contains the first components of all right singular vectors * of the lower block. On exit, VF contains the first components * of all right singular vectors of the bidiagonal matrix. * * VFW (workspace) DOUBLE PRECISION array, dimension ( M ) * Workspace for VF. * * VL (input/output) DOUBLE PRECISION array, dimension ( M ) * On entry, VL(1:NL+1) contains the last components of all * right singular vectors of the upper block; and VL(NL+2:M) * contains the last components of all right singular vectors * of the lower block. On exit, VL contains the last components * of all right singular vectors of the bidiagonal matrix. * * VLW (workspace) DOUBLE PRECISION array, dimension ( M ) * Workspace for VL. * * ALPHA (input) DOUBLE PRECISION * Contains the diagonal element associated with the added row. * * BETA (input) DOUBLE PRECISION * Contains the off-diagonal element associated with the added * row. * * DSIGMA (output) DOUBLE PRECISION array, dimension ( N ) * Contains a copy of the diagonal elements (K-1 singular values * and one zero) in the secular equation. * * IDX (workspace) INTEGER array, dimension ( N ) * This will contain the permutation used to sort the contents of * D into ascending order. * * IDXP (workspace) INTEGER array, dimension ( N ) * This will contain the permutation used to place deflated * values of D at the end of the array. On output IDXP(2:K) * points to the nondeflated D-values and IDXP(K+1:N) * points to the deflated singular values. * * IDXQ (input) INTEGER array, dimension ( N ) * This contains the permutation which separately sorts the two * sub-problems in D into ascending order. Note that entries in * the first half of this permutation must first be moved one * position backward; and entries in the second half * must first have NL+1 added to their values. * * PERM (output) INTEGER array, dimension ( N ) * The permutations (from deflation and sorting) to be applied * to each singular block. Not referenced if ICOMPQ = 0. * * GIVPTR (output) INTEGER * The number of Givens rotations which took place in this * subproblem. Not referenced if ICOMPQ = 0. * * GIVCOL (output) INTEGER array, dimension ( LDGCOL, 2 ) * Each pair of numbers indicates a pair of columns to take place * in a Givens rotation. Not referenced if ICOMPQ = 0. * * LDGCOL (input) INTEGER * The leading dimension of GIVCOL, must be at least N. * * GIVNUM (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 ) * Each number indicates the C or S value to be used in the * corresponding Givens rotation. Not referenced if ICOMPQ = 0. * * LDGNUM (input) INTEGER * The leading dimension of GIVNUM, must be at least N. * * C (output) DOUBLE PRECISION * C contains garbage if SQRE =0 and the C-value of a Givens * rotation related to the right null space if SQRE = 1. * * S (output) DOUBLE PRECISION * S contains garbage if SQRE =0 and the S-value of a Givens * rotation related to the right null space if SQRE = 1. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * * 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, EIGHT PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0, $ EIGHT = 8.0D+0 ) * .. * .. Local Scalars .. * INTEGER I, IDXI, IDXJ, IDXJP, J, JP, JPREV, K2, M, N, $ NLP1, NLP2 DOUBLE PRECISION EPS, HLFTOL, TAU, TOL, Z1 * .. * .. External Subroutines .. EXTERNAL DCOPY, DLAMRG, DROT, XERBLA * .. * .. External Functions .. DOUBLE PRECISION DLAMCH, DLAPY2 EXTERNAL DLAMCH, DLAPY2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 N = NL + NR + 1 M = N + SQRE * IF( ( ICOMPQ.LT.0 ) .OR. ( ICOMPQ.GT.1 ) ) THEN INFO = -1 ELSE IF( NL.LT.1 ) THEN INFO = -2 ELSE IF( NR.LT.1 ) THEN INFO = -3 ELSE IF( ( SQRE.LT.0 ) .OR. ( SQRE.GT.1 ) ) THEN INFO = -4 ELSE IF( LDGCOL.LT.N ) THEN INFO = -22 ELSE IF( LDGNUM.LT.N ) THEN INFO = -24 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD7', -INFO ) RETURN END IF * NLP1 = NL + 1 NLP2 = NL + 2 IF( ICOMPQ.EQ.1 ) THEN GIVPTR = 0 END IF * * Generate the first part of the vector Z and move the singular * values in the first part of D one position backward. * Z1 = ALPHA*VL( NLP1 ) VL( NLP1 ) = ZERO TAU = VF( NLP1 ) DO 10 I = NL, 1, -1 Z( I+1 ) = ALPHA*VL( I ) VL( I ) = ZERO VF( I+1 ) = VF( I ) D( I+1 ) = D( I ) IDXQ( I+1 ) = IDXQ( I ) + 1 10 CONTINUE VF( 1 ) = TAU * * Generate the second part of the vector Z. * DO 20 I = NLP2, M Z( I ) = BETA*VF( I ) VF( I ) = ZERO 20 CONTINUE * * Sort the singular values into increasing order * DO 30 I = NLP2, N IDXQ( I ) = IDXQ( I ) + NLP1 30 CONTINUE * * DSIGMA, IDXC, IDXC, and ZW are used as storage space. * DO 40 I = 2, N DSIGMA( I ) = D( IDXQ( I ) ) ZW( I ) = Z( IDXQ( I ) ) VFW( I ) = VF( IDXQ( I ) ) VLW( I ) = VL( IDXQ( I ) ) 40 CONTINUE * CALL DLAMRG( NL, NR, DSIGMA( 2 ), 1, 1, IDX( 2 ) ) * DO 50 I = 2, N IDXI = 1 + IDX( I ) D( I ) = DSIGMA( IDXI ) Z( I ) = ZW( IDXI ) VF( I ) = VFW( IDXI ) VL( I ) = VLW( IDXI ) 50 CONTINUE * * Calculate the allowable deflation tolerence * EPS = DLAMCH( 'Epsilon' ) TOL = MAX( ABS( ALPHA ), ABS( BETA ) ) TOL = EIGHT*EIGHT*EPS*MAX( ABS( D( N ) ), TOL ) * * There are 2 kinds of deflation -- first a value in the z-vector * is small, second two (or more) singular values are very close * together (their difference is small). * * If the value in the z-vector is small, we simply permute the * array so that the corresponding singular value is moved to the * end. * * If two values in the D-vector are close, we perform a two-sided * rotation designed to make one of the corresponding z-vector * entries zero, and then permute the array so that the deflated * singular value is moved to the end. * * If there are multiple singular values then the problem deflates. * Here the number of equal singular values are found. As each equal * singular value is found, an elementary reflector is computed to * rotate the corresponding singular subspace so that the * corresponding components of Z are zero in this new basis. * K = 1 K2 = N + 1 DO 60 J = 2, N IF( ABS( Z( J ) ).LE.TOL ) THEN * * Deflate due to small z component. * K2 = K2 - 1 IDXP( K2 ) = J IF( J.EQ.N ) $ GO TO 100 ELSE JPREV = J GO TO 70 END IF 60 CONTINUE 70 CONTINUE J = JPREV 80 CONTINUE J = J + 1 IF( J.GT.N ) $ GO TO 90 IF( ABS( Z( J ) ).LE.TOL ) THEN * * Deflate due to small z component. * K2 = K2 - 1 IDXP( K2 ) = J ELSE * * Check if singular values are close enough to allow deflation. * IF( ABS( D( J )-D( JPREV ) ).LE.TOL ) THEN * * Deflation is possible. * S = Z( JPREV ) C = Z( J ) * * Find sqrt(a**2+b**2) without overflow or * destructive underflow. * TAU = DLAPY2( C, S ) Z( J ) = TAU Z( JPREV ) = ZERO C = C / TAU S = -S / TAU * * Record the appropriate Givens rotation * IF( ICOMPQ.EQ.1 ) THEN GIVPTR = GIVPTR + 1 IDXJP = IDXQ( IDX( JPREV )+1 ) IDXJ = IDXQ( IDX( J )+1 ) IF( IDXJP.LE.NLP1 ) THEN IDXJP = IDXJP - 1 END IF IF( IDXJ.LE.NLP1 ) THEN IDXJ = IDXJ - 1 END IF GIVCOL( GIVPTR, 2 ) = IDXJP GIVCOL( GIVPTR, 1 ) = IDXJ GIVNUM( GIVPTR, 2 ) = C GIVNUM( GIVPTR, 1 ) = S END IF CALL DROT( 1, VF( JPREV ), 1, VF( J ), 1, C, S ) CALL DROT( 1, VL( JPREV ), 1, VL( J ), 1, C, S ) K2 = K2 - 1 IDXP( K2 ) = JPREV JPREV = J ELSE K = K + 1 ZW( K ) = Z( JPREV ) DSIGMA( K ) = D( JPREV ) IDXP( K ) = JPREV JPREV = J END IF END IF GO TO 80 90 CONTINUE * * Record the last singular value. * K = K + 1 ZW( K ) = Z( JPREV ) DSIGMA( K ) = D( JPREV ) IDXP( K ) = JPREV * 100 CONTINUE * * Sort the singular values into DSIGMA. The singular values which * were not deflated go into the first K slots of DSIGMA, except * that DSIGMA(1) is treated separately. * DO 110 J = 2, N JP = IDXP( J ) DSIGMA( J ) = D( JP ) VFW( J ) = VF( JP ) VLW( J ) = VL( JP ) 110 CONTINUE IF( ICOMPQ.EQ.1 ) THEN DO 120 J = 2, N JP = IDXP( J ) PERM( J ) = IDXQ( IDX( JP )+1 ) IF( PERM( J ).LE.NLP1 ) THEN PERM( J ) = PERM( J ) - 1 END IF 120 CONTINUE END IF * * The deflated singular values go back into the last N - K slots of * D. * CALL DCOPY( N-K, DSIGMA( K+1 ), 1, D( K+1 ), 1 ) * * Determine DSIGMA(1), DSIGMA(2), Z(1), VF(1), VL(1), VF(M), and * VL(M). * DSIGMA( 1 ) = ZERO HLFTOL = TOL / TWO IF( ABS( DSIGMA( 2 ) ).LE.HLFTOL ) $ DSIGMA( 2 ) = HLFTOL IF( M.GT.N ) THEN Z( 1 ) = DLAPY2( Z1, Z( M ) ) IF( Z( 1 ).LE.TOL ) THEN C = ONE S = ZERO Z( 1 ) = TOL ELSE C = Z1 / Z( 1 ) S = -Z( M ) / Z( 1 ) END IF CALL DROT( 1, VF( M ), 1, VF( 1 ), 1, C, S ) CALL DROT( 1, VL( M ), 1, VL( 1 ), 1, C, S ) ELSE IF( ABS( Z1 ).LE.TOL ) THEN Z( 1 ) = TOL ELSE Z( 1 ) = Z1 END IF END IF * * Restore Z, VF, and VL. * CALL DCOPY( K-1, ZW( 2 ), 1, Z( 2 ), 1 ) CALL DCOPY( N-1, VFW( 2 ), 1, VF( 2 ), 1 ) CALL DCOPY( N-1, VLW( 2 ), 1, VL( 2 ), 1 ) * RETURN * * End of DLASD7 * END SUBROUTINE DLASD8( ICOMPQ, K, D, Z, VF, VL, DIFL, DIFR, LDDIFR, $ DSIGMA, WORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER ICOMPQ, INFO, K, LDDIFR * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), DIFL( * ), DIFR( LDDIFR, * ), $ DSIGMA( * ), VF( * ), VL( * ), WORK( * ), $ Z( * ) * .. * * Purpose * ======= * * DLASD8 finds the square roots of the roots of the secular equation, * as defined by the values in DSIGMA and Z. It makes the appropriate * calls to DLASD4, and stores, for each element in D, the distance * to its two nearest poles (elements in DSIGMA). It also updates * the arrays VF and VL, the first and last components of all the * right singular vectors of the original bidiagonal matrix. * * DLASD8 is called from DLASD6. * * Arguments * ========= * * ICOMPQ (input) INTEGER * Specifies whether singular vectors are to be computed in * factored form in the calling routine: * = 0: Compute singular values only. * = 1: Compute singular vectors in factored form as well. * * K (input) INTEGER * The number of terms in the rational function to be solved * by DLASD4. K >= 1. * * D (output) DOUBLE PRECISION array, dimension ( K ) * On output, D contains the updated singular values. * * Z (input) DOUBLE PRECISION array, dimension ( K ) * The first K elements of this array contain the components * of the deflation-adjusted updating row vector. * * VF (input/output) DOUBLE PRECISION array, dimension ( K ) * On entry, VF contains information passed through DBEDE8. * On exit, VF contains the first K components of the first * components of all right singular vectors of the bidiagonal * matrix. * * VL (input/output) DOUBLE PRECISION array, dimension ( K ) * On entry, VL contains information passed through DBEDE8. * On exit, VL contains the first K components of the last * components of all right singular vectors of the bidiagonal * matrix. * * DIFL (output) DOUBLE PRECISION array, dimension ( K ) * On exit, DIFL(I) = D(I) - DSIGMA(I). * * DIFR (output) DOUBLE PRECISION array, * dimension ( LDDIFR, 2 ) if ICOMPQ = 1 and * dimension ( K ) if ICOMPQ = 0. * On exit, DIFR(I,1) = D(I) - DSIGMA(I+1), DIFR(K,1) is not * defined and will not be referenced. * * If ICOMPQ = 1, DIFR(1:K,2) is an array containing the * normalizing factors for the right singular vector matrix. * * LDDIFR (input) INTEGER * The leading dimension of DIFR, must be at least K. * * DSIGMA (input) DOUBLE PRECISION array, dimension ( K ) * The first K elements of this array contain the old roots * of the deflated updating problem. These are the poles * of the secular equation. * * WORK (workspace) DOUBLE PRECISION array, dimension at least 3 * K * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value. * > 0: if INFO = 1, an singular value did not converge * * Further Details * =============== * * Based on contributions by * Ming Gu and Huan Ren, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. INTEGER I, IWK1, IWK2, IWK2I, IWK3, IWK3I, J DOUBLE PRECISION DIFLJ, DIFRJ, DJ, DSIGJ, DSIGJP, RHO, TEMP * .. * .. External Subroutines .. EXTERNAL DCOPY, DLASCL, DLASD4, DLASET, XERBLA * .. * .. External Functions .. DOUBLE PRECISION DDOT, DLAMC3, DNRM2 EXTERNAL DDOT, DLAMC3, DNRM2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 * IF( ( ICOMPQ.LT.0 ) .OR. ( ICOMPQ.GT.1 ) ) THEN INFO = -1 ELSE IF( K.LT.1 ) THEN INFO = -2 ELSE IF( LDDIFR.LT.K ) THEN INFO = -9 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLASD8', -INFO ) RETURN END IF * * Quick return if possible * IF( K.EQ.1 ) THEN D( 1 ) = ABS( Z( 1 ) ) DIFL( 1 ) = D( 1 ) IF( ICOMPQ.EQ.1 ) THEN DIFL( 2 ) = ONE DIFR( 1, 2 ) = ONE END IF RETURN END IF * * Modify values DSIGMA(i) to make sure all DSIGMA(i)-DSIGMA(j) can * be computed with high relative accuracy (barring over/underflow). * This is a problem on machines without a guard digit in * add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2). * The following code replaces DSIGMA(I) by 2*DSIGMA(I)-DSIGMA(I), * which on any of these machines zeros out the bottommost * bit of DSIGMA(I) if it is 1; this makes the subsequent * subtractions DSIGMA(I)-DSIGMA(J) unproblematic when cancellation * occurs. On binary machines with a guard digit (almost all * machines) it does not change DSIGMA(I) at all. On hexadecimal * and decimal machines with a guard digit, it slightly * changes the bottommost bits of DSIGMA(I). It does not account * for hexadecimal or decimal machines without guard digits * (we know of none). We use a subroutine call to compute * 2*DLAMBDA(I) to prevent optimizing compilers from eliminating * this code. * DO 10 I = 1, K DSIGMA( I ) = DLAMC3( DSIGMA( I ), DSIGMA( I ) ) - DSIGMA( I ) 10 CONTINUE * * Book keeping. * IWK1 = 1 IWK2 = IWK1 + K IWK3 = IWK2 + K IWK2I = IWK2 - 1 IWK3I = IWK3 - 1 * * Normalize Z. * RHO = DNRM2( K, Z, 1 ) CALL DLASCL( 'G', 0, 0, RHO, ONE, K, 1, Z, K, INFO ) RHO = RHO*RHO * * Initialize WORK(IWK3). * CALL DLASET( 'A', K, 1, ONE, ONE, WORK( IWK3 ), K ) * * Compute the updated singular values, the arrays DIFL, DIFR, * and the updated Z. * DO 40 J = 1, K CALL DLASD4( K, J, DSIGMA, Z, WORK( IWK1 ), RHO, D( J ), $ WORK( IWK2 ), INFO ) * * If the root finder fails, the computation is terminated. * IF( INFO.NE.0 ) THEN RETURN END IF WORK( IWK3I+J ) = WORK( IWK3I+J )*WORK( J )*WORK( IWK2I+J ) DIFL( J ) = -WORK( J ) DIFR( J, 1 ) = -WORK( J+1 ) DO 20 I = 1, J - 1 WORK( IWK3I+I ) = WORK( IWK3I+I )*WORK( I )* $ WORK( IWK2I+I ) / ( DSIGMA( I )- $ DSIGMA( J ) ) / ( DSIGMA( I )+ $ DSIGMA( J ) ) 20 CONTINUE DO 30 I = J + 1, K WORK( IWK3I+I ) = WORK( IWK3I+I )*WORK( I )* $ WORK( IWK2I+I ) / ( DSIGMA( I )- $ DSIGMA( J ) ) / ( DSIGMA( I )+ $ DSIGMA( J ) ) 30 CONTINUE 40 CONTINUE * * Compute updated Z. * DO 50 I = 1, K Z( I ) = SIGN( SQRT( ABS( WORK( IWK3I+I ) ) ), Z( I ) ) 50 CONTINUE * * Update VF and VL. * DO 80 J = 1, K DIFLJ = DIFL( J ) DJ = D( J ) DSIGJ = -DSIGMA( J ) IF( J.LT.K ) THEN DIFRJ = -DIFR( J, 1 ) DSIGJP = -DSIGMA( J+1 ) END IF WORK( J ) = -Z( J ) / DIFLJ / ( DSIGMA( J )+DJ ) DO 60 I = 1, J - 1 WORK( I ) = Z( I ) / ( DLAMC3( DSIGMA( I ), DSIGJ )-DIFLJ ) $ / ( DSIGMA( I )+DJ ) 60 CONTINUE DO 70 I = J + 1, K WORK( I ) = Z( I ) / ( DLAMC3( DSIGMA( I ), DSIGJP )+DIFRJ ) $ / ( DSIGMA( I )+DJ ) 70 CONTINUE TEMP = DNRM2( K, WORK, 1 ) WORK( IWK2I+J ) = DDOT( K, WORK, 1, VF, 1 ) / TEMP WORK( IWK3I+J ) = DDOT( K, WORK, 1, VL, 1 ) / TEMP IF( ICOMPQ.EQ.1 ) THEN DIFR( J, 2 ) = TEMP END IF 80 CONTINUE * CALL DCOPY( K, WORK( IWK2 ), 1, VF, 1 ) CALL DCOPY( K, WORK( IWK3 ), 1, VL, 1 ) * RETURN * * End of DLASD8 * END SUBROUTINE DLAMRG( N1, N2, A, DTRD1, DTRD2, INDEX ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER DTRD1, DTRD2, N1, N2 * .. * .. Array Arguments .. INTEGER INDEX( * ) DOUBLE PRECISION A( * ) * .. * * Purpose * ======= * * DLAMRG will create a permutation list which will merge the elements * of A (which is composed of two independently sorted sets) into a * single set which is sorted in ascending order. * * Arguments * ========= * * N1 (input) INTEGER * N2 (input) INTEGER * These arguements contain the respective lengths of the two * sorted lists to be merged. * * A (input) DOUBLE PRECISION array, dimension (N1+N2) * The first N1 elements of A contain a list of numbers which * are sorted in either ascending or descending order. Likewise * for the final N2 elements. * * DTRD1 (input) INTEGER * DTRD2 (input) INTEGER * These are the strides to be taken through the array A. * Allowable strides are 1 and -1. They indicate whether a * subset of A is sorted in ascending (DTRDx = 1) or descending * (DTRDx = -1) order. * * INDEX (output) INTEGER array, dimension (N1+N2) * On exit this array will contain a permutation such that * if B( I ) = A( INDEX( I ) ) for I=1,N1+N2, then B will be * sorted in ascending order. * * ===================================================================== * * .. Local Scalars .. INTEGER I, IND1, IND2, N1SV, N2SV * .. * .. Executable Statements .. * N1SV = N1 N2SV = N2 IF( DTRD1.GT.0 ) THEN IND1 = 1 ELSE IND1 = N1 END IF IF( DTRD2.GT.0 ) THEN IND2 = 1 + N1 ELSE IND2 = N1 + N2 END IF I = 1 * while ( (N1SV > 0) & (N2SV > 0) ) 10 CONTINUE IF( N1SV.GT.0 .AND. N2SV.GT.0 ) THEN IF( A( IND1 ).LE.A( IND2 ) ) THEN INDEX( I ) = IND1 I = I + 1 IND1 = IND1 + DTRD1 N1SV = N1SV - 1 ELSE INDEX( I ) = IND2 I = I + 1 IND2 = IND2 + DTRD2 N2SV = N2SV - 1 END IF GO TO 10 END IF * end while IF( N1SV.EQ.0 ) THEN DO 20 N1SV = 1, N2SV INDEX( I ) = IND2 I = I + 1 IND2 = IND2 + DTRD2 20 CONTINUE ELSE * N2SV .EQ. 0 DO 30 N2SV = 1, N1SV INDEX( I ) = IND1 I = I + 1 IND1 = IND1 + DTRD1 30 CONTINUE END IF * RETURN * * End of DLAMRG * END SUBROUTINE DLASD4( N, I, D, Z, DELTA, RHO, SIGMA, WORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * October 31, 1999 * * .. Scalar Arguments .. INTEGER I, INFO, N DOUBLE PRECISION RHO, SIGMA * .. * .. Array Arguments .. DOUBLE PRECISION D( * ), DELTA( * ), WORK( * ), Z( * ) * .. * * Purpose * ======= * * This subroutine computes the square root of the I-th updated * eigenvalue of a positive symmetric rank-one modification to * a positive diagonal matrix whose entries are given as the squares * of the corresponding entries in the array d, and that * * 0 <= D(i) < D(j) for i < j * * and that RHO > 0. This is arranged by the calling routine, and is * no loss in generality. The rank-one modified system is thus * * diag( D ) * diag( D ) + RHO * Z * Z_transpose. * * where we assume the Euclidean norm of Z is 1. * * The method consists of approximating the rational functions in the * secular equation by simpler interpolating rational functions. * * Arguments * ========= * * N (input) INTEGER * The length of all arrays. * * I (input) INTEGER * The index of the eigenvalue to be computed. 1 <= I <= N. * * D (input) DOUBLE PRECISION array, dimension ( N ) * The original eigenvalues. It is assumed that they are in * order, 0 <= D(I) < D(J) for I < J. * * Z (input) DOUBLE PRECISION array, dimension ( N ) * The components of the updating vector. * * DELTA (output) DOUBLE PRECISION array, dimension ( N ) * If N .ne. 1, DELTA contains (D(j) - sigma_I) in its j-th * component. If N = 1, then DELTA(1) = 1. The vector DELTA * contains the information necessary to construct the * (singular) eigenvectors. * * RHO (input) DOUBLE PRECISION * The scalar in the symmetric updating formula. * * SIGMA (output) DOUBLE PRECISION * The computed lambda_I, the I-th updated eigenvalue. * * WORK (workspace) DOUBLE PRECISION array, dimension ( N ) * If N .ne. 1, WORK contains (D(j) + sigma_I) in its j-th * component. If N = 1, then WORK( 1 ) = 1. * * INFO (output) INTEGER * = 0: successful exit * > 0: if INFO = 1, the updating process failed. * * Internal Parameters * =================== * * Logical variable ORGATI (origin-at-i?) is used for distinguishing * whether D(i) or D(i+1) is treated as the origin. * * ORGATI = .true. origin at i * ORGATI = .false. origin at i+1 * * Logical variable SWTCH3 (switch-for-3-poles?) is for noting * if we are working with THREE poles! * * MAXIT is the maximum number of iterations allowed for each * eigenvalue. * * Further Details * =============== * * Based on contributions by * Ren-Cang Li, Computer Science Division, University of California * at Berkeley, USA * * ===================================================================== * * .. Parameters .. INTEGER MAXIT PARAMETER ( MAXIT = 20 ) DOUBLE PRECISION ZERO, ONE, TWO, THREE, FOUR, EIGHT, TEN PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0, $ THREE = 3.0D+0, FOUR = 4.0D+0, EIGHT = 8.0D+0, $ TEN = 10.0D+0 ) * .. * .. Local Scalars .. LOGICAL ORGATI, SWTCH, SWTCH3 INTEGER II, IIM1, IIP1, IP1, ITER, J, NITER DOUBLE PRECISION A, B, C, DELSQ, DELSQ2, DPHI, DPSI, DTIIM, $ DTIIP, DTIPSQ, DTISQ, DTNSQ, DTNSQ1, DW, EPS, $ ERRETM, ETA, PHI, PREW, PSI, RHOINV, SG2LB, $ SG2UB, TAU, TEMP, TEMP1, TEMP2, W * .. * .. Local Arrays .. DOUBLE PRECISION DD( 3 ), ZZ( 3 ) * .. * .. External Subroutines .. EXTERNAL DLAED6, DLASD5 * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Executable Statements .. * * Since this routine is called in an inner loop, we do no argument * checking. * * Quick return for N=1 and 2. * INFO = 0 IF( N.EQ.1 ) THEN * * Presumably, I=1 upon entry * SIGMA = SQRT( D( 1 )*D( 1 )+RHO*Z( 1 )*Z( 1 ) ) DELTA( 1 ) = ONE WORK( 1 ) = ONE RETURN END IF IF( N.EQ.2 ) THEN CALL DLASD5( I, D, Z, DELTA, RHO, SIGMA, WORK ) RETURN END IF * * Compute machine epsilon * EPS = DLAMCH( 'Epsilon' ) RHOINV = ONE / RHO * * The case I = N * IF( I.EQ.N ) THEN * * Initialize some basic variables * II = N - 1 NITER = 1 * * Calculate initial guess * TEMP = RHO / TWO * * If ||Z||_2 is not one, then TEMP should be set to * RHO * ||Z||_2^2 / TWO * TEMP1 = TEMP / ( D( N )+SQRT( D( N )*D( N )+TEMP ) ) DO 10 J = 1, N WORK( J ) = D( J ) + D( N ) + TEMP1 DELTA( J ) = ( D( J )-D( N ) ) - TEMP1 10 CONTINUE * PSI = ZERO DO 20 J = 1, N - 2 PSI = PSI + Z( J )*Z( J ) / ( DELTA( J )*WORK( J ) ) 20 CONTINUE * C = RHOINV + PSI W = C + Z( II )*Z( II ) / ( DELTA( II )*WORK( II ) ) + $ Z( N )*Z( N ) / ( DELTA( N )*WORK( N ) ) * IF( W.LE.ZERO ) THEN TEMP1 = SQRT( D( N )*D( N )+RHO ) TEMP = Z( N-1 )*Z( N-1 ) / ( ( D( N-1 )+TEMP1 )* $ ( D( N )-D( N-1 )+RHO / ( D( N )+TEMP1 ) ) ) + $ Z( N )*Z( N ) / RHO * * The following TAU is to approximate * SIGMA_n^2 - D( N )*D( N ) * IF( C.LE.TEMP ) THEN TAU = RHO ELSE DELSQ = ( D( N )-D( N-1 ) )*( D( N )+D( N-1 ) ) A = -C*DELSQ + Z( N-1 )*Z( N-1 ) + Z( N )*Z( N ) B = Z( N )*Z( N )*DELSQ IF( A.LT.ZERO ) THEN TAU = TWO*B / ( SQRT( A*A+FOUR*B*C )-A ) ELSE TAU = ( A+SQRT( A*A+FOUR*B*C ) ) / ( TWO*C ) END IF END IF * * It can be proved that * D(N)^2+RHO/2 <= SIGMA_n^2 < D(N)^2+TAU <= D(N)^2+RHO * ELSE DELSQ = ( D( N )-D( N-1 ) )*( D( N )+D( N-1 ) ) A = -C*DELSQ + Z( N-1 )*Z( N-1 ) + Z( N )*Z( N ) B = Z( N )*Z( N )*DELSQ * * The following TAU is to approximate * SIGMA_n^2 - D( N )*D( N ) * IF( A.LT.ZERO ) THEN TAU = TWO*B / ( SQRT( A*A+FOUR*B*C )-A ) ELSE TAU = ( A+SQRT( A*A+FOUR*B*C ) ) / ( TWO*C ) END IF * * It can be proved that * D(N)^2 < D(N)^2+TAU < SIGMA(N)^2 < D(N)^2+RHO/2 * END IF * * The following ETA is to approximate SIGMA_n - D( N ) * ETA = TAU / ( D( N )+SQRT( D( N )*D( N )+TAU ) ) * SIGMA = D( N ) + ETA DO 30 J = 1, N DELTA( J ) = ( D( J )-D( I ) ) - ETA WORK( J ) = D( J ) + D( I ) + ETA 30 CONTINUE * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 40 J = 1, II TEMP = Z( J ) / ( DELTA( J )*WORK( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 40 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * TEMP = Z( N ) / ( DELTA( N )*WORK( N ) ) PHI = Z( N )*TEMP DPHI = TEMP*TEMP ERRETM = EIGHT*( -PHI-PSI ) + ERRETM - PHI + RHOINV + $ ABS( TAU )*( DPSI+DPHI ) * W = RHOINV + PHI + PSI * * Test for convergence * IF( ABS( W ).LE.EPS*ERRETM ) THEN GO TO 240 END IF * * Calculate the new step * NITER = NITER + 1 DTNSQ1 = WORK( N-1 )*DELTA( N-1 ) DTNSQ = WORK( N )*DELTA( N ) C = W - DTNSQ1*DPSI - DTNSQ*DPHI A = ( DTNSQ+DTNSQ1 )*W - DTNSQ*DTNSQ1*( DPSI+DPHI ) B = DTNSQ*DTNSQ1*W IF( C.LT.ZERO ) $ C = ABS( C ) IF( C.EQ.ZERO ) THEN ETA = RHO - SIGMA*SIGMA ELSE IF( A.GE.ZERO ) THEN ETA = ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE ETA = TWO*B / ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF * * Note, eta should be positive if w is negative, and * eta should be negative otherwise. However, * if for some reason caused by roundoff, eta*w > 0, * we simply use one Newton step instead. This way * will guarantee eta*w < 0. * IF( W*ETA.GT.ZERO ) $ ETA = -W / ( DPSI+DPHI ) TEMP = ETA - DTNSQ IF( TEMP.GT.RHO ) $ ETA = RHO + DTNSQ * TAU = TAU + ETA ETA = ETA / ( SIGMA+SQRT( ETA+SIGMA*SIGMA ) ) DO 50 J = 1, N DELTA( J ) = DELTA( J ) - ETA WORK( J ) = WORK( J ) + ETA 50 CONTINUE * SIGMA = SIGMA + ETA * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 60 J = 1, II TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 60 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * TEMP = Z( N ) / ( WORK( N )*DELTA( N ) ) PHI = Z( N )*TEMP DPHI = TEMP*TEMP ERRETM = EIGHT*( -PHI-PSI ) + ERRETM - PHI + RHOINV + $ ABS( TAU )*( DPSI+DPHI ) * W = RHOINV + PHI + PSI * * Main loop to update the values of the array DELTA * ITER = NITER + 1 * DO 90 NITER = ITER, MAXIT * * Test for convergence * IF( ABS( W ).LE.EPS*ERRETM ) THEN GO TO 240 END IF * * Calculate the new step * DTNSQ1 = WORK( N-1 )*DELTA( N-1 ) DTNSQ = WORK( N )*DELTA( N ) C = W - DTNSQ1*DPSI - DTNSQ*DPHI A = ( DTNSQ+DTNSQ1 )*W - DTNSQ1*DTNSQ*( DPSI+DPHI ) B = DTNSQ1*DTNSQ*W IF( A.GE.ZERO ) THEN ETA = ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE ETA = TWO*B / ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF * * Note, eta should be positive if w is negative, and * eta should be negative otherwise. However, * if for some reason caused by roundoff, eta*w > 0, * we simply use one Newton step instead. This way * will guarantee eta*w < 0. * IF( W*ETA.GT.ZERO ) $ ETA = -W / ( DPSI+DPHI ) TEMP = ETA - DTNSQ IF( TEMP.LE.ZERO ) $ ETA = ETA / TWO * TAU = TAU + ETA ETA = ETA / ( SIGMA+SQRT( ETA+SIGMA*SIGMA ) ) DO 70 J = 1, N DELTA( J ) = DELTA( J ) - ETA WORK( J ) = WORK( J ) + ETA 70 CONTINUE * SIGMA = SIGMA + ETA * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 80 J = 1, II TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 80 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * TEMP = Z( N ) / ( WORK( N )*DELTA( N ) ) PHI = Z( N )*TEMP DPHI = TEMP*TEMP ERRETM = EIGHT*( -PHI-PSI ) + ERRETM - PHI + RHOINV + $ ABS( TAU )*( DPSI+DPHI ) * W = RHOINV + PHI + PSI 90 CONTINUE * * Return with INFO = 1, NITER = MAXIT and not converged * INFO = 1 GO TO 240 * * End for the case I = N * ELSE * * The case for I < N * NITER = 1 IP1 = I + 1 * * Calculate initial guess * DELSQ = ( D( IP1 )-D( I ) )*( D( IP1 )+D( I ) ) DELSQ2 = DELSQ / TWO TEMP = DELSQ2 / ( D( I )+SQRT( D( I )*D( I )+DELSQ2 ) ) DO 100 J = 1, N WORK( J ) = D( J ) + D( I ) + TEMP DELTA( J ) = ( D( J )-D( I ) ) - TEMP 100 CONTINUE * PSI = ZERO DO 110 J = 1, I - 1 PSI = PSI + Z( J )*Z( J ) / ( WORK( J )*DELTA( J ) ) 110 CONTINUE * PHI = ZERO DO 120 J = N, I + 2, -1 PHI = PHI + Z( J )*Z( J ) / ( WORK( J )*DELTA( J ) ) 120 CONTINUE C = RHOINV + PSI + PHI W = C + Z( I )*Z( I ) / ( WORK( I )*DELTA( I ) ) + $ Z( IP1 )*Z( IP1 ) / ( WORK( IP1 )*DELTA( IP1 ) ) * IF( W.GT.ZERO ) THEN * * d(i)^2 < the ith sigma^2 < (d(i)^2+d(i+1)^2)/2 * * We choose d(i) as origin. * ORGATI = .TRUE. SG2LB = ZERO SG2UB = DELSQ2 A = C*DELSQ + Z( I )*Z( I ) + Z( IP1 )*Z( IP1 ) B = Z( I )*Z( I )*DELSQ IF( A.GT.ZERO ) THEN TAU = TWO*B / ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) ELSE TAU = ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) END IF * * TAU now is an estimation of SIGMA^2 - D( I )^2. The * following, however, is the corresponding estimation of * SIGMA - D( I ). * ETA = TAU / ( D( I )+SQRT( D( I )*D( I )+TAU ) ) ELSE * * (d(i)^2+d(i+1)^2)/2 <= the ith sigma^2 < d(i+1)^2/2 * * We choose d(i+1) as origin. * ORGATI = .FALSE. SG2LB = -DELSQ2 SG2UB = ZERO A = C*DELSQ - Z( I )*Z( I ) - Z( IP1 )*Z( IP1 ) B = Z( IP1 )*Z( IP1 )*DELSQ IF( A.LT.ZERO ) THEN TAU = TWO*B / ( A-SQRT( ABS( A*A+FOUR*B*C ) ) ) ELSE TAU = -( A+SQRT( ABS( A*A+FOUR*B*C ) ) ) / ( TWO*C ) END IF * * TAU now is an estimation of SIGMA^2 - D( IP1 )^2. The * following, however, is the corresponding estimation of * SIGMA - D( IP1 ). * ETA = TAU / ( D( IP1 )+SQRT( ABS( D( IP1 )*D( IP1 )+ $ TAU ) ) ) END IF * IF( ORGATI ) THEN II = I SIGMA = D( I ) + ETA DO 130 J = 1, N WORK( J ) = D( J ) + D( I ) + ETA DELTA( J ) = ( D( J )-D( I ) ) - ETA 130 CONTINUE ELSE II = I + 1 SIGMA = D( IP1 ) + ETA DO 140 J = 1, N WORK( J ) = D( J ) + D( IP1 ) + ETA DELTA( J ) = ( D( J )-D( IP1 ) ) - ETA 140 CONTINUE END IF IIM1 = II - 1 IIP1 = II + 1 * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 150 J = 1, IIM1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 150 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * DPHI = ZERO PHI = ZERO DO 160 J = N, IIP1, -1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PHI = PHI + Z( J )*TEMP DPHI = DPHI + TEMP*TEMP ERRETM = ERRETM + PHI 160 CONTINUE * W = RHOINV + PHI + PSI * * W is the value of the secular function with * its ii-th element removed. * SWTCH3 = .FALSE. IF( ORGATI ) THEN IF( W.LT.ZERO ) $ SWTCH3 = .TRUE. ELSE IF( W.GT.ZERO ) $ SWTCH3 = .TRUE. END IF IF( II.EQ.1 .OR. II.EQ.N ) $ SWTCH3 = .FALSE. * TEMP = Z( II ) / ( WORK( II )*DELTA( II ) ) DW = DPSI + DPHI + TEMP*TEMP TEMP = Z( II )*TEMP W = W + TEMP ERRETM = EIGHT*( PHI-PSI ) + ERRETM + TWO*RHOINV + $ THREE*ABS( TEMP ) + ABS( TAU )*DW * * Test for convergence * IF( ABS( W ).LE.EPS*ERRETM ) THEN GO TO 240 END IF * IF( W.LE.ZERO ) THEN SG2LB = MAX( SG2LB, TAU ) ELSE SG2UB = MIN( SG2UB, TAU ) END IF * * Calculate the new step * NITER = NITER + 1 IF( .NOT.SWTCH3 ) THEN DTIPSQ = WORK( IP1 )*DELTA( IP1 ) DTISQ = WORK( I )*DELTA( I ) IF( ORGATI ) THEN C = W - DTIPSQ*DW + DELSQ*( Z( I ) / DTISQ )**2 ELSE C = W - DTISQ*DW - DELSQ*( Z( IP1 ) / DTIPSQ )**2 END IF A = ( DTIPSQ+DTISQ )*W - DTIPSQ*DTISQ*DW B = DTIPSQ*DTISQ*W IF( C.EQ.ZERO ) THEN IF( A.EQ.ZERO ) THEN IF( ORGATI ) THEN A = Z( I )*Z( I ) + DTIPSQ*DTIPSQ*( DPSI+DPHI ) ELSE A = Z( IP1 )*Z( IP1 ) + DTISQ*DTISQ*( DPSI+DPHI ) END IF END IF ETA = B / A ELSE IF( A.LE.ZERO ) THEN ETA = ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE ETA = TWO*B / ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF ELSE * * Interpolation using THREE most relevant poles * DTIIM = WORK( IIM1 )*DELTA( IIM1 ) DTIIP = WORK( IIP1 )*DELTA( IIP1 ) TEMP = RHOINV + PSI + PHI IF( ORGATI ) THEN TEMP1 = Z( IIM1 ) / DTIIM TEMP1 = TEMP1*TEMP1 C = ( TEMP - DTIIP*( DPSI+DPHI ) ) - $ ( D( IIM1 )-D( IIP1 ) )*( D( IIM1 )+D( IIP1 ) )*TEMP1 ZZ( 1 ) = Z( IIM1 )*Z( IIM1 ) IF( DPSI.LT.TEMP1 ) THEN ZZ( 3 ) = DTIIP*DTIIP*DPHI ELSE ZZ( 3 ) = DTIIP*DTIIP*( ( DPSI-TEMP1 )+DPHI ) END IF ELSE TEMP1 = Z( IIP1 ) / DTIIP TEMP1 = TEMP1*TEMP1 C = ( TEMP - DTIIM*( DPSI+DPHI ) ) - $ ( D( IIP1 )-D( IIM1 ) )*( D( IIM1 )+D( IIP1 ) )*TEMP1 IF( DPHI.LT.TEMP1 ) THEN ZZ( 1 ) = DTIIM*DTIIM*DPSI ELSE ZZ( 1 ) = DTIIM*DTIIM*( DPSI+( DPHI-TEMP1 ) ) END IF ZZ( 3 ) = Z( IIP1 )*Z( IIP1 ) END IF ZZ( 2 ) = Z( II )*Z( II ) DD( 1 ) = DTIIM DD( 2 ) = DELTA( II )*WORK( II ) DD( 3 ) = DTIIP CALL DLAED6( NITER, ORGATI, C, DD, ZZ, W, ETA, INFO ) IF( INFO.NE.0 ) $ GO TO 240 END IF * * Note, eta should be positive if w is negative, and * eta should be negative otherwise. However, * if for some reason caused by roundoff, eta*w > 0, * we simply use one Newton step instead. This way * will guarantee eta*w < 0. * IF( W*ETA.GE.ZERO ) $ ETA = -W / DW IF( ORGATI ) THEN TEMP1 = WORK( I )*DELTA( I ) TEMP = ETA - TEMP1 ELSE TEMP1 = WORK( IP1 )*DELTA( IP1 ) TEMP = ETA - TEMP1 END IF IF( TEMP.GT.SG2UB .OR. TEMP.LT.SG2LB ) THEN IF( W.LT.ZERO ) THEN ETA = ( SG2UB-TAU ) / TWO ELSE ETA = ( SG2LB-TAU ) / TWO END IF END IF * TAU = TAU + ETA ETA = ETA / ( SIGMA+SQRT( SIGMA*SIGMA+ETA ) ) * PREW = W * SIGMA = SIGMA + ETA DO 170 J = 1, N WORK( J ) = WORK( J ) + ETA DELTA( J ) = DELTA( J ) - ETA 170 CONTINUE * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 180 J = 1, IIM1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 180 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * DPHI = ZERO PHI = ZERO DO 190 J = N, IIP1, -1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PHI = PHI + Z( J )*TEMP DPHI = DPHI + TEMP*TEMP ERRETM = ERRETM + PHI 190 CONTINUE * TEMP = Z( II ) / ( WORK( II )*DELTA( II ) ) DW = DPSI + DPHI + TEMP*TEMP TEMP = Z( II )*TEMP W = RHOINV + PHI + PSI + TEMP ERRETM = EIGHT*( PHI-PSI ) + ERRETM + TWO*RHOINV + $ THREE*ABS( TEMP ) + ABS( TAU )*DW * IF( W.LE.ZERO ) THEN SG2LB = MAX( SG2LB, TAU ) ELSE SG2UB = MIN( SG2UB, TAU ) END IF * SWTCH = .FALSE. IF( ORGATI ) THEN IF( -W.GT.ABS( PREW ) / TEN ) $ SWTCH = .TRUE. ELSE IF( W.GT.ABS( PREW ) / TEN ) $ SWTCH = .TRUE. END IF * * Main loop to update the values of the array DELTA and WORK * ITER = NITER + 1 * DO 230 NITER = ITER, MAXIT * * Test for convergence * IF( ABS( W ).LE.EPS*ERRETM ) THEN GO TO 240 END IF * * Calculate the new step * IF( .NOT.SWTCH3 ) THEN DTIPSQ = WORK( IP1 )*DELTA( IP1 ) DTISQ = WORK( I )*DELTA( I ) IF( .NOT.SWTCH ) THEN IF( ORGATI ) THEN C = W - DTIPSQ*DW + DELSQ*( Z( I ) / DTISQ )**2 ELSE C = W - DTISQ*DW - DELSQ*( Z( IP1 ) / DTIPSQ )**2 END IF ELSE TEMP = Z( II ) / ( WORK( II )*DELTA( II ) ) IF( ORGATI ) THEN DPSI = DPSI + TEMP*TEMP ELSE DPHI = DPHI + TEMP*TEMP END IF C = W - DTISQ*DPSI - DTIPSQ*DPHI END IF A = ( DTIPSQ+DTISQ )*W - DTIPSQ*DTISQ*DW B = DTIPSQ*DTISQ*W IF( C.EQ.ZERO ) THEN IF( A.EQ.ZERO ) THEN IF( .NOT.SWTCH ) THEN IF( ORGATI ) THEN A = Z( I )*Z( I ) + DTIPSQ*DTIPSQ* $ ( DPSI+DPHI ) ELSE A = Z( IP1 )*Z( IP1 ) + $ DTISQ*DTISQ*( DPSI+DPHI ) END IF ELSE A = DTISQ*DTISQ*DPSI + DTIPSQ*DTIPSQ*DPHI END IF END IF ETA = B / A ELSE IF( A.LE.ZERO ) THEN ETA = ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE ETA = TWO*B / ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF ELSE * * Interpolation using THREE most relevant poles * DTIIM = WORK( IIM1 )*DELTA( IIM1 ) DTIIP = WORK( IIP1 )*DELTA( IIP1 ) TEMP = RHOINV + PSI + PHI IF( SWTCH ) THEN C = TEMP - DTIIM*DPSI - DTIIP*DPHI ZZ( 1 ) = DTIIM*DTIIM*DPSI ZZ( 3 ) = DTIIP*DTIIP*DPHI ELSE IF( ORGATI ) THEN TEMP1 = Z( IIM1 ) / DTIIM TEMP1 = TEMP1*TEMP1 TEMP2 = ( D( IIM1 )-D( IIP1 ) )* $ ( D( IIM1 )+D( IIP1 ) )*TEMP1 C = TEMP - DTIIP*( DPSI+DPHI ) - TEMP2 ZZ( 1 ) = Z( IIM1 )*Z( IIM1 ) IF( DPSI.LT.TEMP1 ) THEN ZZ( 3 ) = DTIIP*DTIIP*DPHI ELSE ZZ( 3 ) = DTIIP*DTIIP*( ( DPSI-TEMP1 )+DPHI ) END IF ELSE TEMP1 = Z( IIP1 ) / DTIIP TEMP1 = TEMP1*TEMP1 TEMP2 = ( D( IIP1 )-D( IIM1 ) )* $ ( D( IIM1 )+D( IIP1 ) )*TEMP1 C = TEMP - DTIIM*( DPSI+DPHI ) - TEMP2 IF( DPHI.LT.TEMP1 ) THEN ZZ( 1 ) = DTIIM*DTIIM*DPSI ELSE ZZ( 1 ) = DTIIM*DTIIM*( DPSI+( DPHI-TEMP1 ) ) END IF ZZ( 3 ) = Z( IIP1 )*Z( IIP1 ) END IF END IF DD( 1 ) = DTIIM DD( 2 ) = DELTA( II )*WORK( II ) DD( 3 ) = DTIIP CALL DLAED6( NITER, ORGATI, C, DD, ZZ, W, ETA, INFO ) IF( INFO.NE.0 ) $ GO TO 240 END IF * * Note, eta should be positive if w is negative, and * eta should be negative otherwise. However, * if for some reason caused by roundoff, eta*w > 0, * we simply use one Newton step instead. This way * will guarantee eta*w < 0. * IF( W*ETA.GE.ZERO ) $ ETA = -W / DW IF( ORGATI ) THEN TEMP1 = WORK( I )*DELTA( I ) TEMP = ETA - TEMP1 ELSE TEMP1 = WORK( IP1 )*DELTA( IP1 ) TEMP = ETA - TEMP1 END IF IF( TEMP.GT.SG2UB .OR. TEMP.LT.SG2LB ) THEN IF( W.LT.ZERO ) THEN ETA = ( SG2UB-TAU ) / TWO ELSE ETA = ( SG2LB-TAU ) / TWO END IF END IF * TAU = TAU + ETA ETA = ETA / ( SIGMA+SQRT( SIGMA*SIGMA+ETA ) ) * SIGMA = SIGMA + ETA DO 200 J = 1, N WORK( J ) = WORK( J ) + ETA DELTA( J ) = DELTA( J ) - ETA 200 CONTINUE * PREW = W * * Evaluate PSI and the derivative DPSI * DPSI = ZERO PSI = ZERO ERRETM = ZERO DO 210 J = 1, IIM1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PSI = PSI + Z( J )*TEMP DPSI = DPSI + TEMP*TEMP ERRETM = ERRETM + PSI 210 CONTINUE ERRETM = ABS( ERRETM ) * * Evaluate PHI and the derivative DPHI * DPHI = ZERO PHI = ZERO DO 220 J = N, IIP1, -1 TEMP = Z( J ) / ( WORK( J )*DELTA( J ) ) PHI = PHI + Z( J )*TEMP DPHI = DPHI + TEMP*TEMP ERRETM = ERRETM + PHI 220 CONTINUE * TEMP = Z( II ) / ( WORK( II )*DELTA( II ) ) DW = DPSI + DPHI + TEMP*TEMP TEMP = Z( II )*TEMP W = RHOINV + PHI + PSI + TEMP ERRETM = EIGHT*( PHI-PSI ) + ERRETM + TWO*RHOINV + $ THREE*ABS( TEMP ) + ABS( TAU )*DW IF( W*PREW.GT.ZERO .AND. ABS( W ).GT.ABS( PREW ) / TEN ) $ SWTCH = .NOT.SWTCH * IF( W.LE.ZERO ) THEN SG2LB = MAX( SG2LB, TAU ) ELSE SG2UB = MIN( SG2UB, TAU ) END IF * 230 CONTINUE * * Return with INFO = 1, NITER = MAXIT and not converged * INFO = 1 * END IF * 240 CONTINUE RETURN * * End of DLASD4 * END SUBROUTINE DLASD5( I, D, Z, DELTA, RHO, DSIGMA, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER I DOUBLE PRECISION DSIGMA, RHO * .. * .. Array Arguments .. DOUBLE PRECISION D( 2 ), DELTA( 2 ), WORK( 2 ), Z( 2 ) * .. * * Purpose * ======= * * This subroutine computes the square root of the I-th eigenvalue * of a positive symmetric rank-one modification of a 2-by-2 diagonal * matrix * * diag( D ) * diag( D ) + RHO * Z * transpose(Z) . * * The diagonal entries in the array D are assumed to satisfy * * 0 <= D(i) < D(j) for i < j . * * We also assume RHO > 0 and that the Euclidean norm of the vector * Z is one. * * Arguments * ========= * * I (input) INTEGER * The index of the eigenvalue to be computed. I = 1 or I = 2. * * D (input) DOUBLE PRECISION array, dimension ( 2 ) * The original eigenvalues. We assume 0 <= D(1) < D(2). * * Z (input) DOUBLE PRECISION array, dimension ( 2 ) * The components of the updating vector. * * DELTA (output) DOUBLE PRECISION array, dimension ( 2 ) * Contains (D(j) - lambda_I) in its j-th component. * The vector DELTA contains the information necessary * to construct the eigenvectors. * * RHO (input) DOUBLE PRECISION * The scalar in the symmetric updating formula. * * DSIGMA (output) DOUBLE PRECISION * The computed lambda_I, the I-th updated eigenvalue. * * WORK (workspace) DOUBLE PRECISION array, dimension ( 2 ) * WORK contains (D(j) + sigma_I) in its j-th component. * * Further Details * =============== * * Based on contributions by * Ren-Cang Li, Computer Science Division, University of California * at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, THREE, FOUR PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TWO = 2.0D+0, $ THREE = 3.0D+0, FOUR = 4.0D+0 ) * .. * .. Local Scalars .. DOUBLE PRECISION B, C, DEL, DELSQ, TAU, W * .. * .. Intrinsic Functions .. INTRINSIC ABS, SQRT * .. * .. Executable Statements .. * DEL = D( 2 ) - D( 1 ) DELSQ = DEL*( D( 2 )+D( 1 ) ) IF( I.EQ.1 ) THEN W = ONE + FOUR*RHO*( Z( 2 )*Z( 2 ) / ( D( 1 )+THREE*D( 2 ) )- $ Z( 1 )*Z( 1 ) / ( THREE*D( 1 )+D( 2 ) ) ) / DEL IF( W.GT.ZERO ) THEN B = DELSQ + RHO*( Z( 1 )*Z( 1 )+Z( 2 )*Z( 2 ) ) C = RHO*Z( 1 )*Z( 1 )*DELSQ * * B > ZERO, always * * The following TAU is DSIGMA * DSIGMA - D( 1 ) * D( 1 ) * TAU = TWO*C / ( B+SQRT( ABS( B*B-FOUR*C ) ) ) * * The following TAU is DSIGMA - D( 1 ) * TAU = TAU / ( D( 1 )+SQRT( D( 1 )*D( 1 )+TAU ) ) DSIGMA = D( 1 ) + TAU DELTA( 1 ) = -TAU DELTA( 2 ) = DEL - TAU WORK( 1 ) = TWO*D( 1 ) + TAU WORK( 2 ) = ( D( 1 )+TAU ) + D( 2 ) * DELTA( 1 ) = -Z( 1 ) / TAU * DELTA( 2 ) = Z( 2 ) / ( DEL-TAU ) ELSE B = -DELSQ + RHO*( Z( 1 )*Z( 1 )+Z( 2 )*Z( 2 ) ) C = RHO*Z( 2 )*Z( 2 )*DELSQ * * The following TAU is DSIGMA * DSIGMA - D( 2 ) * D( 2 ) * IF( B.GT.ZERO ) THEN TAU = -TWO*C / ( B+SQRT( B*B+FOUR*C ) ) ELSE TAU = ( B-SQRT( B*B+FOUR*C ) ) / TWO END IF * * The following TAU is DSIGMA - D( 2 ) * TAU = TAU / ( D( 2 )+SQRT( ABS( D( 2 )*D( 2 )+TAU ) ) ) DSIGMA = D( 2 ) + TAU DELTA( 1 ) = -( DEL+TAU ) DELTA( 2 ) = -TAU WORK( 1 ) = D( 1 ) + TAU + D( 2 ) WORK( 2 ) = TWO*D( 2 ) + TAU * DELTA( 1 ) = -Z( 1 ) / ( DEL+TAU ) * DELTA( 2 ) = -Z( 2 ) / TAU END IF * TEMP = SQRT( DELTA( 1 )*DELTA( 1 )+DELTA( 2 )*DELTA( 2 ) ) * DELTA( 1 ) = DELTA( 1 ) / TEMP * DELTA( 2 ) = DELTA( 2 ) / TEMP ELSE * * Now I=2 * B = -DELSQ + RHO*( Z( 1 )*Z( 1 )+Z( 2 )*Z( 2 ) ) C = RHO*Z( 2 )*Z( 2 )*DELSQ * * The following TAU is DSIGMA * DSIGMA - D( 2 ) * D( 2 ) * IF( B.GT.ZERO ) THEN TAU = ( B+SQRT( B*B+FOUR*C ) ) / TWO ELSE TAU = TWO*C / ( -B+SQRT( B*B+FOUR*C ) ) END IF * * The following TAU is DSIGMA - D( 2 ) * TAU = TAU / ( D( 2 )+SQRT( D( 2 )*D( 2 )+TAU ) ) DSIGMA = D( 2 ) + TAU DELTA( 1 ) = -( DEL+TAU ) DELTA( 2 ) = -TAU WORK( 1 ) = D( 1 ) + TAU + D( 2 ) WORK( 2 ) = TWO*D( 2 ) + TAU * DELTA( 1 ) = -Z( 1 ) / ( DEL+TAU ) * DELTA( 2 ) = -Z( 2 ) / TAU * TEMP = SQRT( DELTA( 1 )*DELTA( 1 )+DELTA( 2 )*DELTA( 2 ) ) * DELTA( 1 ) = DELTA( 1 ) / TEMP * DELTA( 2 ) = DELTA( 2 ) / TEMP END IF RETURN * * End of DLASD5 * END SUBROUTINE DLAED6( KNITER, ORGATI, RHO, D, Z, FINIT, TAU, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Oak Ridge National Lab, Argonne National Lab, * Courant Institute, NAG Ltd., and Rice University * June 30, 1999 * * .. Scalar Arguments .. LOGICAL ORGATI INTEGER INFO, KNITER DOUBLE PRECISION FINIT, RHO, TAU * .. * .. Array Arguments .. DOUBLE PRECISION D( 3 ), Z( 3 ) * .. * * Purpose * ======= * * DLAED6 computes the positive or negative root (closest to the origin) * of * z(1) z(2) z(3) * f(x) = rho + --------- + ---------- + --------- * d(1)-x d(2)-x d(3)-x * * It is assumed that * * if ORGATI = .true. the root is between d(2) and d(3); * otherwise it is between d(1) and d(2) * * This routine will be called by DLAED4 when necessary. In most cases, * the root sought is the smallest in magnitude, though it might not be * in some extremely rare situations. * * Arguments * ========= * * KNITER (input) INTEGER * Refer to DLAED4 for its significance. * * ORGATI (input) LOGICAL * If ORGATI is true, the needed root is between d(2) and * d(3); otherwise it is between d(1) and d(2). See * DLAED4 for further details. * * RHO (input) DOUBLE PRECISION * Refer to the equation f(x) above. * * D (input) DOUBLE PRECISION array, dimension (3) * D satisfies d(1) < d(2) < d(3). * * Z (input) DOUBLE PRECISION array, dimension (3) * Each of the elements in z must be positive. * * FINIT (input) DOUBLE PRECISION * The value of f at 0. It is more accurate than the one * evaluated inside this routine (if someone wants to do * so). * * TAU (output) DOUBLE PRECISION * The root of the equation f(x). * * INFO (output) INTEGER * = 0: successful exit * > 0: if INFO = 1, failure to converge * * Further Details * =============== * * Based on contributions by * Ren-Cang Li, Computer Science Division, University of California * at Berkeley, USA * * ===================================================================== * * .. Parameters .. INTEGER MAXIT PARAMETER ( MAXIT = 20 ) DOUBLE PRECISION ZERO, ONE, TWO, THREE, FOUR, EIGHT PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ THREE = 3.0D0, FOUR = 4.0D0, EIGHT = 8.0D0 ) * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Local Arrays .. DOUBLE PRECISION DSCALE( 3 ), ZSCALE( 3 ) * .. * .. Local Scalars .. LOGICAL FIRST, SCALE INTEGER I, ITER, NITER DOUBLE PRECISION A, B, BASE, C, DDF, DF, EPS, ERRETM, ETA, F, $ FC, SCLFAC, SCLINV, SMALL1, SMALL2, SMINV1, $ SMINV2, TEMP, TEMP1, TEMP2, TEMP3, TEMP4 * .. * .. Save statement .. SAVE FIRST, SMALL1, SMINV1, SMALL2, SMINV2, EPS * .. * .. Intrinsic Functions .. INTRINSIC ABS, INT, LOG, MAX, MIN, SQRT * .. * .. Data statements .. DATA FIRST / .TRUE. / * .. * .. Executable Statements .. * INFO = 0 * NITER = 1 TAU = ZERO IF( KNITER.EQ.2 ) THEN IF( ORGATI ) THEN TEMP = ( D( 3 )-D( 2 ) ) / TWO C = RHO + Z( 1 ) / ( ( D( 1 )-D( 2 ) )-TEMP ) A = C*( D( 2 )+D( 3 ) ) + Z( 2 ) + Z( 3 ) B = C*D( 2 )*D( 3 ) + Z( 2 )*D( 3 ) + Z( 3 )*D( 2 ) ELSE TEMP = ( D( 1 )-D( 2 ) ) / TWO C = RHO + Z( 3 ) / ( ( D( 3 )-D( 2 ) )-TEMP ) A = C*( D( 1 )+D( 2 ) ) + Z( 1 ) + Z( 2 ) B = C*D( 1 )*D( 2 ) + Z( 1 )*D( 2 ) + Z( 2 )*D( 1 ) END IF TEMP = MAX( ABS( A ), ABS( B ), ABS( C ) ) A = A / TEMP B = B / TEMP C = C / TEMP IF( C.EQ.ZERO ) THEN TAU = B / A ELSE IF( A.LE.ZERO ) THEN TAU = ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE TAU = TWO*B / ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF TEMP = RHO + Z( 1 ) / ( D( 1 )-TAU ) + $ Z( 2 ) / ( D( 2 )-TAU ) + Z( 3 ) / ( D( 3 )-TAU ) IF( ABS( FINIT ).LE.ABS( TEMP ) ) $ TAU = ZERO END IF * * On first call to routine, get machine parameters for * possible scaling to avoid overflow * IF( FIRST ) THEN EPS = DLAMCH( 'Epsilon' ) BASE = DLAMCH( 'Base' ) SMALL1 = BASE**( INT( LOG( DLAMCH( 'SafMin' ) ) / LOG( BASE ) / $ THREE ) ) SMINV1 = ONE / SMALL1 SMALL2 = SMALL1*SMALL1 SMINV2 = SMINV1*SMINV1 FIRST = .FALSE. END IF * * Determine if scaling of inputs necessary to avoid overflow * when computing 1/TEMP**3 * IF( ORGATI ) THEN TEMP = MIN( ABS( D( 2 )-TAU ), ABS( D( 3 )-TAU ) ) ELSE TEMP = MIN( ABS( D( 1 )-TAU ), ABS( D( 2 )-TAU ) ) END IF SCALE = .FALSE. IF( TEMP.LE.SMALL1 ) THEN SCALE = .TRUE. IF( TEMP.LE.SMALL2 ) THEN * * Scale up by power of radix nearest 1/SAFMIN**(2/3) * SCLFAC = SMINV2 SCLINV = SMALL2 ELSE * * Scale up by power of radix nearest 1/SAFMIN**(1/3) * SCLFAC = SMINV1 SCLINV = SMALL1 END IF * * Scaling up safe because D, Z, TAU scaled elsewhere to be O(1) * DO 10 I = 1, 3 DSCALE( I ) = D( I )*SCLFAC ZSCALE( I ) = Z( I )*SCLFAC 10 CONTINUE TAU = TAU*SCLFAC ELSE * * Copy D and Z to DSCALE and ZSCALE * DO 20 I = 1, 3 DSCALE( I ) = D( I ) ZSCALE( I ) = Z( I ) 20 CONTINUE END IF * FC = ZERO DF = ZERO DDF = ZERO DO 30 I = 1, 3 TEMP = ONE / ( DSCALE( I )-TAU ) TEMP1 = ZSCALE( I )*TEMP TEMP2 = TEMP1*TEMP TEMP3 = TEMP2*TEMP FC = FC + TEMP1 / DSCALE( I ) DF = DF + TEMP2 DDF = DDF + TEMP3 30 CONTINUE F = FINIT + TAU*FC * IF( ABS( F ).LE.ZERO ) $ GO TO 60 * * Iteration begins * * It is not hard to see that * * 1) Iterations will go up monotonically * if FINIT < 0; * * 2) Iterations will go down monotonically * if FINIT > 0. * ITER = NITER + 1 * DO 50 NITER = ITER, MAXIT * IF( ORGATI ) THEN TEMP1 = DSCALE( 2 ) - TAU TEMP2 = DSCALE( 3 ) - TAU ELSE TEMP1 = DSCALE( 1 ) - TAU TEMP2 = DSCALE( 2 ) - TAU END IF A = ( TEMP1+TEMP2 )*F - TEMP1*TEMP2*DF B = TEMP1*TEMP2*F C = F - ( TEMP1+TEMP2 )*DF + TEMP1*TEMP2*DDF TEMP = MAX( ABS( A ), ABS( B ), ABS( C ) ) A = A / TEMP B = B / TEMP C = C / TEMP IF( C.EQ.ZERO ) THEN ETA = B / A ELSE IF( A.LE.ZERO ) THEN ETA = ( A-SQRT( ABS( A*A-FOUR*B*C ) ) ) / ( TWO*C ) ELSE ETA = TWO*B / ( A+SQRT( ABS( A*A-FOUR*B*C ) ) ) END IF IF( F*ETA.GE.ZERO ) THEN ETA = -F / DF END IF * TEMP = ETA + TAU IF( ORGATI ) THEN IF( ETA.GT.ZERO .AND. TEMP.GE.DSCALE( 3 ) ) $ ETA = ( DSCALE( 3 )-TAU ) / TWO IF( ETA.LT.ZERO .AND. TEMP.LE.DSCALE( 2 ) ) $ ETA = ( DSCALE( 2 )-TAU ) / TWO ELSE IF( ETA.GT.ZERO .AND. TEMP.GE.DSCALE( 2 ) ) $ ETA = ( DSCALE( 2 )-TAU ) / TWO IF( ETA.LT.ZERO .AND. TEMP.LE.DSCALE( 1 ) ) $ ETA = ( DSCALE( 1 )-TAU ) / TWO END IF TAU = TAU + ETA * FC = ZERO ERRETM = ZERO DF = ZERO DDF = ZERO DO 40 I = 1, 3 TEMP = ONE / ( DSCALE( I )-TAU ) TEMP1 = ZSCALE( I )*TEMP TEMP2 = TEMP1*TEMP TEMP3 = TEMP2*TEMP TEMP4 = TEMP1 / DSCALE( I ) FC = FC + TEMP4 ERRETM = ERRETM + ABS( TEMP4 ) DF = DF + TEMP2 DDF = DDF + TEMP3 40 CONTINUE F = FINIT + TAU*FC ERRETM = EIGHT*( ABS( FINIT )+ABS( TAU )*ERRETM ) + $ ABS( TAU )*DF IF( ABS( F ).LE.EPS*ERRETM ) $ GO TO 60 50 CONTINUE INFO = 1 60 CONTINUE * * Undo scaling * IF( SCALE ) $ TAU = TAU*SCLINV RETURN * * End of DLAED6 * END SUBROUTINE RSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, $ ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, $ IWORK, LIWORK, INFO ) * * -- LAPACK driver routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * March 20, 2000 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE, UPLO INTEGER IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSYEVR computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric matrix T. Eigenvalues and eigenvectors can be * selected by specifying either a range of values or a range of * indices for the desired eigenvalues. * * Whenever possible, DSYEVR calls DSTEGR to compute the * eigenspectrum using Relatively Robust Representations. DSTEGR * computes eigenvalues by the dqds algorithm, while orthogonal * eigenvectors are computed from various "good" L D L^T representations * (also known as Relatively Robust Representations). Gram-Schmidt * orthogonalization is avoided as far as possible. More specifically, * the various steps of the algorithm are as follows. For the i-th * unreduced block of T, * (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T * is a relatively robust representation, * (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high * relative accuracy by the dqds algorithm, * (c) If there is a cluster of close eigenvalues, "choose" sigma_i * close to the cluster, and go to step (a), * (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, * compute the corresponding eigenvector by forming a * rank-revealing twisted factorization. * The desired accuracy of the output can be specified by the input * parameter ABSTOL. * * For more details, see "A new O(n^2) algorithm for the symmetric * tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, * Computer Science Division Technical Report No. UCB//CSD-97-971, * UC Berkeley, May 1997. * * * Note 1 : DSYEVR calls DSTEGR when the full spectrum is requested * on machines which conform to the ieee-754 floating point standard. * DSYEVR calls DSTEBZ and SSTEIN on non-ieee machines and * when partial spectrum requests are made. * * Normal execution of DSTEGR may create NaNs and infinities and * hence may abort due to a floating point exception in environments * which do not handle NaNs and infinities in the ieee standard default * manner. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. ********** For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and ********** DSTEIN are called * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A is stored; * = 'L': Lower triangle of A is stored. * * N (input) INTEGER * The order of the matrix A. N >= 0. * * A (input/output) DOUBLE PRECISION array, dimension (LDA, N) * On entry, the symmetric matrix A. If UPLO = 'U', the * leading N-by-N upper triangular part of A contains the * upper triangular part of the matrix A. If UPLO = 'L', * the leading N-by-N lower triangular part of A contains * the lower triangular part of the matrix A. * On exit, the lower triangle (if UPLO='L') or the upper * triangle (if UPLO='U') of A, including the diagonal, is * destroyed. * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,N). * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the eigenvalues. * An approximate eigenvalue is accepted as converged * when it is determined to lie in an interval [a,b] * of width less than or equal to * * ABSTOL + EPS * max( |a|,|b| ) , * * where EPS is the machine precision. If ABSTOL is less than * or equal to zero, then EPS*|T| will be used in its place, * where |T| is the 1-norm of the tridiagonal matrix obtained * by reducing A to tridiagonal form. * * See "Computing Small Singular Values of Bidiagonal Matrices * with Guaranteed High Relative Accuracy," by Demmel and * Kahan, LAPACK Working Note #3. * * If high relative accuracy is important, set ABSTOL to * DLAMCH( 'Safe minimum' ). Doing so will guarantee that * eigenvalues are computed to high relative accuracy when * possible in future releases. The current code does not * make any guarantees about high relative accuracy, but * furutre releases will. See J. Barlow and J. Demmel, * "Computing Accurate Eigensystems of Scaled Diagonally * Dominant Matrices", LAPACK Working Note #7, for a discussion * of which matrices define their eigenvalues to high relative * accuracy. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M)) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix A * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * ISUPPZ (output) INTEGER array, dimension ( 2*max(1,M) ) * The support of the eigenvectors in Z, i.e., the indices * indicating the nonzero elements in Z. The i-th eigenvector * is nonzero only in elements ISUPPZ( 2*i-1 ) through * ISUPPZ( 2*i ). ********** Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,26*N). * For optimal efficiency, LWORK >= (NB+6)*N, * where NB is the max of the blocksize for DSYTRD and DORMTR * returned by ILAENV. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. LIWORK >= max(1,10*N). * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: Internal error * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * Ken Stanley, Computer Science Division, University of * California at Berkeley, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LOWER, LQUERY, VALEIG, WANTZ CHARACTER ORDER INTEGER I, IEEEOK, IINFO, IMAX, INDD, INDDD, INDE, $ INDEE, INDIBL, INDIFL, INDISP, INDIWO, INDTAU, $ INDWK, INDWKN, ISCALE, ITMP1, J, JJ, LIWMIN, $ LLWORK, LLWRKN, LWKOPT, LWMIN, NB, NSPLIT DOUBLE PRECISION ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, $ SIGMA, SMLNUM, TMP1, VLL, VUU * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH, DLANSY EXTERNAL LSAME, ILAENV, DLAMCH, DLANSY * .. * .. External Subroutines .. EXTERNAL DCOPY, DORMTR, DSCAL, DSTEBZ, DSTEGR, DSTEIN, $ DSTERF, DSWAP, DSYTRD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * IEEEOK = ILAENV( 10, 'DSYEVR', 'N', 1, 2, 3, 4 ) * LOWER = LSAME( UPLO, 'L' ) WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * LQUERY = ( ( LWORK.EQ.-1 ) .OR. ( LIWORK.EQ.-1 ) ) * LWMIN = MAX( 1, 26*N ) LIWMIN = MAX( 1, 10*N ) * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 ELSE IF( .NOT.( LOWER .OR. LSAME( UPLO, 'U' ) ) ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( LDA.LT.MAX( 1, N ) ) THEN INFO = -6 ELSE IF( VALEIG ) THEN IF( N.GT.0 .AND. VU.LE.VL ) $ INFO = -8 ELSE IF( INDEIG ) THEN IF( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) THEN INFO = -9 ELSE IF( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) THEN INFO = -10 END IF END IF END IF IF( INFO.EQ.0 ) THEN IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -15 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -18 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -20 END IF END IF * IF( INFO.EQ.0 ) THEN NB = ILAENV( 1, 'ZHETRD', UPLO, N, -1, -1, -1 ) NB = MAX( NB, ILAENV( 1, 'ZUNMTR', UPLO, N, -1, -1, -1 ) ) LWKOPT = MAX( ( NB+1 )*N, LWMIN ) WORK( 1 ) = LWKOPT IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSYEVR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( N.EQ.1 ) THEN WORK( 1 ) = 7 IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = A( 1, 1 ) ELSE IF( VL.LT.A( 1, 1 ) .AND. VU.GE.A( 1, 1 ) ) THEN M = 1 W( 1 ) = A( 1, 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * ISCALE = 0 ABSTLL = ABSTOL VLL = VL VUU = VU ANRM = DLANSY( 'M', UPLO, N, A, LDA, WORK ) IF( ANRM.GT.ZERO .AND. ANRM.LT.RMIN ) THEN ISCALE = 1 SIGMA = RMIN / ANRM ELSE IF( ANRM.GT.RMAX ) THEN ISCALE = 1 SIGMA = RMAX / ANRM END IF IF( ISCALE.EQ.1 ) THEN IF( LOWER ) THEN DO 10 J = 1, N CALL DSCAL( N-J+1, SIGMA, A( J, J ), 1 ) 10 CONTINUE ELSE DO 20 J = 1, N CALL DSCAL( J, SIGMA, A( 1, J ), 1 ) 20 CONTINUE END IF IF( ABSTOL.GT.0 ) $ ABSTLL = ABSTOL*SIGMA IF( VALEIG ) THEN VLL = VL*SIGMA VUU = VU*SIGMA END IF END IF * * Call DSYTRD to reduce symmetric matrix to tridiagonal form. * INDTAU = 1 INDE = INDTAU + N INDD = INDE + N INDEE = INDD + N INDDD = INDEE + N INDIFL = INDDD + N INDWK = INDIFL + N LLWORK = LWORK - INDWK + 1 CALL DSYTRD( UPLO, N, A, LDA, WORK( INDD ), WORK( INDE ), $ WORK( INDTAU ), WORK( INDWK ), LLWORK, IINFO ) * * If all eigenvalues are desired * then call DSTERF or SSTEGR and DORMTR. * IF( ( ALLEIG .OR. ( INDEIG .AND. IL.EQ.1 .AND. IU.EQ.N ) ) .AND. $ IEEEOK.EQ.1 ) THEN IF( .NOT.WANTZ ) THEN CALL DCOPY( N, WORK( INDD ), 1, W, 1 ) CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DSTERF( N, W, WORK( INDEE ), INFO ) ELSE CALL DCOPY( N-1, WORK( INDE ), 1, WORK( INDEE ), 1 ) CALL DCOPY( N, WORK( INDD ), 1, WORK( INDDD ), 1 ) * CALL DSTEGR( JOBZ, 'A', N, WORK( INDDD ), WORK( INDEE ), $ VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, $ WORK( INDWK ), LWORK, IWORK, LIWORK, INFO ) * * * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * IF( WANTZ .AND. INFO.EQ.0 ) THEN INDWKN = INDE LLWRKN = LWORK - INDWKN + 1 CALL DORMTR( 'L', UPLO, 'N', N, M, A, LDA, $ WORK( INDTAU ), Z, LDZ, WORK( INDWKN ), $ LLWRKN, IINFO ) END IF END IF * * IF( INFO.EQ.0 ) THEN M = N GO TO 30 END IF INFO = 0 END IF * * Otherwise, call DSTEBZ and, if eigenvectors are desired, SSTEIN. * Also call DSTEBZ and SSTEIN if SSTEGR fails. * IF( WANTZ ) THEN ORDER = 'B' ELSE ORDER = 'E' END IF INDIFL = 1 INDIBL = INDIFL + N INDISP = INDIBL + N INDIWO = INDISP + N CALL DSTEBZ( RANGE, ORDER, N, VLL, VUU, IL, IU, ABSTLL, $ WORK( INDD ), WORK( INDE ), M, NSPLIT, W, $ IWORK( INDIBL ), IWORK( INDISP ), WORK( INDWK ), $ IWORK( INDIWO ), INFO ) * IF( WANTZ ) THEN CALL DSTEIN( N, WORK( INDD ), WORK( INDE ), M, W, $ IWORK( INDIBL ), IWORK( INDISP ), Z, LDZ, $ WORK( INDWK ), IWORK( INDIWO ), IWORK( INDIFL ), $ INFO ) * * Apply orthogonal matrix used in reduction to tridiagonal * form to eigenvectors returned by DSTEIN. * INDWKN = INDE LLWRKN = LWORK - INDWKN + 1 CALL DORMTR( 'L', UPLO, 'N', N, M, A, LDA, WORK( INDTAU ), Z, $ LDZ, WORK( INDWKN ), LLWRKN, IINFO ) END IF * * If matrix was scaled, then rescale eigenvalues appropriately. * 30 CONTINUE IF( ISCALE.EQ.1 ) THEN IF( INFO.EQ.0 ) THEN IMAX = M ELSE IMAX = INFO - 1 END IF CALL DSCAL( IMAX, ONE / SIGMA, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( WANTZ ) THEN DO 50 J = 1, M - 1 I = 0 TMP1 = W( J ) DO 40 JJ = J + 1, M IF( W( JJ ).LT.TMP1 ) THEN I = JJ TMP1 = W( JJ ) END IF 40 CONTINUE * IF( I.NE.0 ) THEN ITMP1 = IWORK( INDIBL+I-1 ) W( I ) = W( J ) IWORK( INDIBL+I-1 ) = IWORK( INDIBL+J-1 ) W( J ) = TMP1 IWORK( INDIBL+J-1 ) = ITMP1 CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) END IF 50 CONTINUE END IF * * Set WORK(1) to optimal workspace size. * WORK( 1 ) = LWKOPT IWORK( 1 ) = LIWMIN * RETURN * * End of DSYEVR * END SUBROUTINE DSTEGR( JOBZ, RANGE, N, D, E, VL, VU, IL, IU, ABSTOL, $ M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, $ LIWORK, INFO ) * * -- LAPACK computational routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER JOBZ, RANGE INTEGER IL, INFO, IU, LDZ, LIWORK, LWORK, M, N DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER ISUPPZ( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEGR computes selected eigenvalues and, optionally, eigenvectors * of a real symmetric tridiagonal matrix T. Eigenvalues and * eigenvectors can be selected by specifying either a range of values * or a range of indices for the desired eigenvalues. The eigenvalues * are computed by the dqds algorithm, while orthogonal eigenvectors are * computed from various ``good'' L D L^T representations (also known as * Relatively Robust Representations). Gram-Schmidt orthogonalization is * avoided as far as possible. More specifically, the various steps of * the algorithm are as follows. For the i-th unreduced block of T, * (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T * is a relatively robust representation, * (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high * relative accuracy by the dqds algorithm, * (c) If there is a cluster of close eigenvalues, "choose" sigma_i * close to the cluster, and go to step (a), * (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, * compute the corresponding eigenvector by forming a * rank-revealing twisted factorization. * The desired accuracy of the output can be specified by the input * parameter ABSTOL. * * For more details, see "A new O(n^2) algorithm for the symmetric * tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, * Computer Science Division Technical Report No. UCB/CSD-97-971, * UC Berkeley, May 1997. * * Note 1 : Currently DSTEGR is only set up to find ALL the n * eigenvalues and eigenvectors of T in O(n^2) time * Note 2 : Currently the routine DSTEIN is called when an appropriate * sigma_i cannot be chosen in step (c) above. DSTEIN invokes modified * Gram-Schmidt when eigenvalues are close. * Note 3 : DSTEGR works only on machines which follow ieee-754 * floating-point standard in their handling of infinities and NaNs. * Normal execution of DSTEGR may create NaNs and infinities and hence * may abort due to a floating point exception in environments which * do not conform to the ieee standard. * * Arguments * ========= * * JOBZ (input) CHARACTER*1 * = 'N': Compute eigenvalues only; * = 'V': Compute eigenvalues and eigenvectors. * * RANGE (input) CHARACTER*1 * = 'A': all eigenvalues will be found. * = 'V': all eigenvalues in the half-open interval (VL,VU] * will be found. * = 'I': the IL-th through IU-th eigenvalues will be found. ********** Only RANGE = 'A' is currently supported ********************* * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal matrix * T. On exit, D is overwritten. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix T in elements 1 to N-1 of E; E(N) need not be set. * On exit, E is overwritten. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute error tolerance for the * eigenvalues/eigenvectors. IF JOBZ = 'V', the eigenvalues and * eigenvectors output have residual norms bounded by ABSTOL, * and the dot products between different eigenvectors are * bounded by ABSTOL. If ABSTOL is less than N*EPS*|T|, then * N*EPS*|T| will be used in its place, where EPS is the * machine precision and |T| is the 1-norm of the tridiagonal * matrix. The eigenvalues are computed to an accuracy of * EPS*|T| irrespective of ABSTOL. If high relative accuracy * is important, set ABSTOL to DLAMCH( 'Safe minimum' ). * See Barlow and Demmel "Computing Accurate Eigensystems of * Scaled Diagonally Dominant Matrices", LAPACK Working Note #7 * for a discussion of which matrices define their eigenvalues * to high relative accuracy. * * M (output) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the selected eigenvalues in * ascending order. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix T * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * ISUPPZ (output) INTEGER ARRAY, dimension ( 2*max(1,M) ) * The support of the eigenvectors in Z, i.e., the indices * indicating the nonzero elements in Z. The i-th eigenvector * is nonzero only in elements ISUPPZ( 2*i-1 ) through * ISUPPZ( 2*i ). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal * (and minimal) LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. LWORK >= max(1,18*N) * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * IWORK (workspace/output) INTEGER array, dimension (LIWORK) * On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. * * LIWORK (input) INTEGER * The dimension of the array IWORK. LIWORK >= max(1,10*N) * * If LIWORK = -1, then a workspace query is assumed; the * routine only calculates the optimal size of the IWORK array, * returns this value as the first entry of the IWORK array, and * no error message related to LIWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = 1, internal error in DLARRE, * if INFO = 2, internal error in DLARRV. * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL ALLEIG, INDEIG, LQUERY, VALEIG, WANTZ INTEGER I, IBEGIN, IEND, IINDBL, IINDWK, IINFO, IINSPL, $ INDGRS, INDWOF, INDWRK, ITMP, J, JJ, LIWMIN, $ LWMIN, NSPLIT DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SCALE, SMLNUM, $ THRESH, TMP, TNRM, TOL * .. * .. External Functions .. LOGICAL LSAME DOUBLE PRECISION DLAMCH, DLANST EXTERNAL LSAME, DLAMCH, DLANST * .. * .. External Subroutines .. EXTERNAL DLARRE, DLARRV, DLASET, DSCAL, DSWAP, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC DBLE, MAX, MIN, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * WANTZ = LSAME( JOBZ, 'V' ) ALLEIG = LSAME( RANGE, 'A' ) VALEIG = LSAME( RANGE, 'V' ) INDEIG = LSAME( RANGE, 'I' ) * LQUERY = ( ( LWORK.EQ.-1 ) .OR. ( LIWORK.EQ.-1 ) ) LWMIN = 18*N LIWMIN = 10*N * INFO = 0 IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN INFO = -1 ELSE IF( .NOT.( ALLEIG .OR. VALEIG .OR. INDEIG ) ) THEN INFO = -2 * * The following two lines need to be removed once the * RANGE = 'V' and RANGE = 'I' options are provided. * ELSE IF( VALEIG .OR. INDEIG ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( VALEIG .AND. N.GT.0 .AND. VU.LE.VL ) THEN INFO = -7 ELSE IF( INDEIG .AND. IL.LT.1 ) THEN INFO = -8 * The following change should be made in DSTEVX also, otherwise * IL can be specified as N+1 and IU as N. * ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) THEN ELSE IF( INDEIG .AND. ( IU.LT.IL .OR. IU.GT.N ) ) THEN INFO = -9 ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN INFO = -14 ELSE IF( LWORK.LT.LWMIN .AND. .NOT.LQUERY ) THEN INFO = -17 ELSE IF( LIWORK.LT.LIWMIN .AND. .NOT.LQUERY ) THEN INFO = -19 END IF IF( INFO.EQ.0 ) THEN WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEGR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * IF( N.EQ.1 ) THEN IF( ALLEIG .OR. INDEIG ) THEN M = 1 W( 1 ) = D( 1 ) ELSE IF( VL.LT.D( 1 ) .AND. VU.GE.D( 1 ) ) THEN M = 1 W( 1 ) = D( 1 ) END IF END IF IF( WANTZ ) $ Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * SAFMIN = DLAMCH( 'Safe minimum' ) EPS = DLAMCH( 'Precision' ) SMLNUM = SAFMIN / EPS BIGNUM = ONE / SMLNUM RMIN = SQRT( SMLNUM ) RMAX = MIN( SQRT( BIGNUM ), ONE / SQRT( SQRT( SAFMIN ) ) ) * * Scale matrix to allowable range, if necessary. * SCALE = ONE TNRM = DLANST( 'M', N, D, E ) IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN SCALE = RMIN / TNRM ELSE IF( TNRM.GT.RMAX ) THEN SCALE = RMAX / TNRM END IF IF( SCALE.NE.ONE ) THEN CALL DSCAL( N, SCALE, D, 1 ) CALL DSCAL( N-1, SCALE, E, 1 ) TNRM = TNRM*SCALE END IF INDGRS = 1 INDWOF = 2*N + 1 INDWRK = 3*N + 1 * IINSPL = 1 IINDBL = N + 1 IINDWK = 2*N + 1 * CALL DLASET( 'Full', N, N, ZERO, ZERO, Z, LDZ ) * * Compute the desired eigenvalues of the tridiagonal after splitting * into smaller subblocks if the corresponding of-diagonal elements * are small * THRESH = EPS*TNRM CALL DLARRE( N, D, E, THRESH, NSPLIT, IWORK( IINSPL ), M, W, $ WORK( INDWOF ), WORK( INDGRS ), WORK( INDWRK ), $ IINFO ) IF( IINFO.NE.0 ) THEN INFO = 1 RETURN END IF * IF( WANTZ ) THEN * * Compute the desired eigenvectors corresponding to the computed * eigenvalues * TOL = MAX( ABSTOL, DBLE( N )*THRESH ) IBEGIN = 1 DO 20 I = 1, NSPLIT IEND = IWORK( IINSPL+I-1 ) DO 10 J = IBEGIN, IEND IWORK( IINDBL+J-1 ) = I 10 CONTINUE IBEGIN = IEND + 1 20 CONTINUE * CALL DLARRV( N, D, E, IWORK( IINSPL ), M, W, IWORK( IINDBL ), $ WORK( INDGRS ), TOL, Z, LDZ, ISUPPZ, $ WORK( INDWRK ), IWORK( IINDWK ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = 2 RETURN END IF * END IF * IBEGIN = 1 DO 40 I = 1, NSPLIT IEND = IWORK( IINSPL+I-1 ) DO 30 J = IBEGIN, IEND W( J ) = W( J ) + WORK( INDWOF+I-1 ) 30 CONTINUE IBEGIN = IEND + 1 40 CONTINUE * * If matrix was scaled, then rescale eigenvalues appropriately. * IF( SCALE.NE.ONE ) THEN CALL DSCAL( M, ONE / SCALE, W, 1 ) END IF * * If eigenvalues are not in order, then sort them, along with * eigenvectors. * IF( NSPLIT.GT.1 ) THEN DO 60 J = 1, M - 1 I = 0 TMP = W( J ) DO 50 JJ = J + 1, M IF( W( JJ ).LT.TMP ) THEN I = JJ TMP = W( JJ ) END IF 50 CONTINUE IF( I.NE.0 ) THEN W( I ) = W( J ) W( J ) = TMP IF( WANTZ ) THEN CALL DSWAP( N, Z( 1, I ), 1, Z( 1, J ), 1 ) ITMP = ISUPPZ( 2*I-1 ) ISUPPZ( 2*I-1 ) = ISUPPZ( 2*J-1 ) ISUPPZ( 2*J-1 ) = ITMP ITMP = ISUPPZ( 2*I ) ISUPPZ( 2*I ) = ISUPPZ( 2*J ) ISUPPZ( 2*J ) = ITMP END IF END IF 60 CONTINUE END IF * WORK( 1 ) = LWMIN IWORK( 1 ) = LIWMIN RETURN * * End of DSTEGR * END SUBROUTINE DORMTR( SIDE, UPLO, TRANS, M, N, A, LDA, TAU, C, LDC, $ WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS, UPLO INTEGER INFO, LDA, LDC, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORMTR overwrites the general real M-by-N matrix C with * * SIDE = 'L' SIDE = 'R' * TRANS = 'N': Q * C C * Q * TRANS = 'T': Q**T * C C * Q**T * * where Q is a real orthogonal matrix of order nq, with nq = m if * SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of * nq-1 elementary reflectors, as returned by DSYTRD: * * if UPLO = 'U', Q = H(nq-1) . . . H(2) H(1); * * if UPLO = 'L', Q = H(1) H(2) . . . H(nq-1). * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q**T from the Left; * = 'R': apply Q or Q**T from the Right. * * UPLO (input) CHARACTER*1 * = 'U': Upper triangle of A contains elementary reflectors * from DSYTRD; * = 'L': Lower triangle of A contains elementary reflectors * from DSYTRD. * * TRANS (input) CHARACTER*1 * = 'N': No transpose, apply Q; * = 'T': Transpose, apply Q**T. * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * A (input) DOUBLE PRECISION array, dimension * (LDA,M) if SIDE = 'L' * (LDA,N) if SIDE = 'R' * The vectors which define the elementary reflectors, as * returned by DSYTRD. * * LDA (input) INTEGER * The leading dimension of the array A. * LDA >= max(1,M) if SIDE = 'L'; LDA >= max(1,N) if SIDE = 'R'. * * TAU (input) DOUBLE PRECISION array, dimension * (M-1) if SIDE = 'L' * (N-1) if SIDE = 'R' * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DSYTRD. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N matrix C. * On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If SIDE = 'L', LWORK >= max(1,N); * if SIDE = 'R', LWORK >= max(1,M). * For optimum performance LWORK >= N*NB if SIDE = 'L', and * LWORK >= M*NB if SIDE = 'R', where NB is the optimal * blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Local Scalars .. LOGICAL LEFT, LQUERY, UPPER INTEGER I1, I2, IINFO, LWKOPT, MI, NB, NI, NQ, NW * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DORMQL, DORMQR, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) UPPER = LSAME( UPLO, 'U' ) LQUERY = ( LWORK.EQ.-1 ) * * NQ is the order of Q and NW is the minimum dimension of WORK * IF( LEFT ) THEN NQ = M NW = N ELSE NQ = N NW = M END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.UPPER .AND. .NOT.LSAME( UPLO, 'L' ) ) THEN INFO = -2 ELSE IF( .NOT.LSAME( TRANS, 'N' ) .AND. .NOT.LSAME( TRANS, 'T' ) ) $ THEN INFO = -3 ELSE IF( M.LT.0 ) THEN INFO = -4 ELSE IF( N.LT.0 ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, NQ ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 ELSE IF( LWORK.LT.MAX( 1, NW ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF * IF( INFO.EQ.0 ) THEN IF( UPPER ) THEN IF( LEFT ) THEN NB = ILAENV( 1, 'DORMQL', SIDE // TRANS, M-1, N, M-1, $ -1 ) ELSE NB = ILAENV( 1, 'DORMQL', SIDE // TRANS, M, N-1, N-1, $ -1 ) END IF ELSE IF( LEFT ) THEN NB = ILAENV( 1, 'DORMQR', SIDE // TRANS, M-1, N, M-1, $ -1 ) ELSE NB = ILAENV( 1, 'DORMQR', SIDE // TRANS, M, N-1, N-1, $ -1 ) END IF END IF LWKOPT = MAX( 1, NW )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORMTR', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. NQ.EQ.1 ) THEN WORK( 1 ) = 1 RETURN END IF * IF( LEFT ) THEN MI = M - 1 NI = N ELSE MI = M NI = N - 1 END IF * IF( UPPER ) THEN * * Q was determined by a call to DSYTRD with UPLO = 'U' * CALL DORMQL( SIDE, TRANS, MI, NI, NQ-1, A( 1, 2 ), LDA, TAU, C, $ LDC, WORK, LWORK, IINFO ) ELSE * * Q was determined by a call to DSYTRD with UPLO = 'L' * IF( LEFT ) THEN I1 = 2 I2 = 1 ELSE I1 = 1 I2 = 2 END IF CALL DORMQR( SIDE, TRANS, MI, NI, NQ-1, A( 2, 1 ), LDA, TAU, $ C( I1, I2 ), LDC, WORK, LWORK, IINFO ) END IF WORK( 1 ) = LWKOPT RETURN * * End of DORMTR * END SUBROUTINE DSTEBZ( RANGE, ORDER, N, VL, VU, IL, IU, ABSTOL, D, E, $ M, NSPLIT, W, IBLOCK, ISPLIT, WORK, IWORK, $ INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER ORDER, RANGE INTEGER IL, INFO, IU, M, N, NSPLIT DOUBLE PRECISION ABSTOL, VL, VU * .. * .. Array Arguments .. INTEGER IBLOCK( * ), ISPLIT( * ), IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * DSTEBZ computes the eigenvalues of a symmetric tridiagonal * matrix T. The user may ask for all eigenvalues, all eigenvalues * in the half-open interval (VL, VU], or the IL-th through IU-th * eigenvalues. * * To avoid overflow, the matrix must be scaled so that its * largest element is no greater than overflow**(1/2) * * underflow**(1/4) in absolute value, and for greatest * accuracy, it should not be much smaller than that. * * See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal * Matrix", Report CS41, Computer Science Dept., Stanford * University, July 21, 1966. * * Arguments * ========= * * RANGE (input) CHARACTER * = 'A': ("All") all eigenvalues will be found. * = 'V': ("Value") all eigenvalues in the half-open interval * (VL, VU] will be found. * = 'I': ("Index") the IL-th through IU-th eigenvalues (of the * entire matrix) will be found. * * ORDER (input) CHARACTER * = 'B': ("By Block") the eigenvalues will be grouped by * split-off block (see IBLOCK, ISPLIT) and * ordered from smallest to largest within * the block. * = 'E': ("Entire matrix") * the eigenvalues for the entire matrix * will be ordered from smallest to * largest. * * N (input) INTEGER * The order of the tridiagonal matrix T. N >= 0. * * VL (input) DOUBLE PRECISION * VU (input) DOUBLE PRECISION * If RANGE='V', the lower and upper bounds of the interval to * be searched for eigenvalues. Eigenvalues less than or equal * to VL, or greater than VU, will not be returned. VL < VU. * Not referenced if RANGE = 'A' or 'I'. * * IL (input) INTEGER * IU (input) INTEGER * If RANGE='I', the indices (in ascending order) of the * smallest and largest eigenvalues to be returned. * 1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0. * Not referenced if RANGE = 'A' or 'V'. * * ABSTOL (input) DOUBLE PRECISION * The absolute tolerance for the eigenvalues. An eigenvalue * (or cluster) is considered to be located if it has been * determined to lie in an interval whose width is ABSTOL or * less. If ABSTOL is less than or equal to zero, then ULP*|T| * will be used, where |T| means the 1-norm of T. * * Eigenvalues will be computed most accurately when ABSTOL is * set to twice the underflow threshold 2*DLAMCH('S'), not zero. * * D (input) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the tridiagonal matrix T. * * E (input) DOUBLE PRECISION array, dimension (N-1) * The (n-1) off-diagonal elements of the tridiagonal matrix T. * * M (output) INTEGER * The actual number of eigenvalues found. 0 <= M <= N. * (See also the description of INFO=2,3.) * * NSPLIT (output) INTEGER * The number of diagonal blocks in the matrix T. * 1 <= NSPLIT <= N. * * W (output) DOUBLE PRECISION array, dimension (N) * On exit, the first M elements of W will contain the * eigenvalues. (DSTEBZ may use the remaining N-M elements as * workspace.) * * IBLOCK (output) INTEGER array, dimension (N) * At each row/column j where E(j) is zero or small, the * matrix T is considered to split into a block diagonal * matrix. On exit, if INFO = 0, IBLOCK(i) specifies to which * block (from 1 to the number of blocks) the eigenvalue W(i) * belongs. (DSTEBZ may use the remaining N-M elements as * workspace.) * * ISPLIT (output) INTEGER array, dimension (N) * The splitting points, at which T breaks up into submatrices. * The first submatrix consists of rows/columns 1 to ISPLIT(1), * the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), * etc., and the NSPLIT-th consists of rows/columns * ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. * (Only the first NSPLIT elements will actually be used, but * since the user cannot know a priori what value NSPLIT will * have, N words must be reserved for ISPLIT.) * * WORK (workspace) DOUBLE PRECISION array, dimension (4*N) * * IWORK (workspace) INTEGER array, dimension (3*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: some or all of the eigenvalues failed to converge or * were not computed: * =1 or 3: Bisection failed to converge for some * eigenvalues; these eigenvalues are flagged by a * negative block number. The effect is that the * eigenvalues may not be as accurate as the * absolute and relative tolerances. This is * generally caused by unexpectedly inaccurate * arithmetic. * =2 or 3: RANGE='I' only: Not all of the eigenvalues * IL:IU were found. * Effect: M < IU+1-IL * Cause: non-monotonic arithmetic, causing the * Sturm sequence to be non-monotonic. * Cure: recalculate, using RANGE='A', and pick * out eigenvalues IL:IU. In some cases, * increasing the PARAMETER "FUDGE" may * make things work. * = 4: RANGE='I', and the Gershgorin interval * initially used was too small. No eigenvalues * were computed. * Probable cause: your machine has sloppy * floating-point arithmetic. * Cure: Increase the PARAMETER "FUDGE", * recompile, and try again. * * Internal Parameters * =================== * * RELFAC DOUBLE PRECISION, default = 2.0e0 * The relative tolerance. An interval (a,b] lies within * "relative tolerance" if b-a < RELFAC*ulp*max(|a|,|b|), * where "ulp" is the machine precision (distance from 1 to * the next larger floating point number.) * * FUDGE DOUBLE PRECISION, default = 2 * A "fudge factor" to widen the Gershgorin intervals. Ideally, * a value of 1 should work, but on machines with sloppy * arithmetic, this needs to be larger. The default for * publicly released versions should be large enough to handle * the worst machine around. Note that this has no effect * on accuracy of the solution. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, HALF PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ HALF = 1.0D0 / TWO ) DOUBLE PRECISION FUDGE, RELFAC PARAMETER ( FUDGE = 2.0D0, RELFAC = 2.0D0 ) * .. * .. Local Scalars .. LOGICAL NCNVRG, TOOFEW INTEGER IB, IBEGIN, IDISCL, IDISCU, IE, IEND, IINFO, $ IM, IN, IOFF, IORDER, IOUT, IRANGE, ITMAX, $ ITMP1, IW, IWOFF, J, JB, JDISC, JE, NB, NWL, $ NWU DOUBLE PRECISION ATOLI, BNORM, GL, GU, PIVMIN, RTOLI, SAFEMN, $ TMP1, TMP2, TNORM, ULP, WKILL, WL, WLU, WU, WUL * .. * .. Local Arrays .. INTEGER IDUMMA( 1 ) * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV DOUBLE PRECISION DLAMCH EXTERNAL LSAME, ILAENV, DLAMCH * .. * .. External Subroutines .. EXTERNAL DLAEBZ, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, INT, LOG, MAX, MIN, SQRT * .. * .. Executable Statements .. * INFO = 0 * * Decode RANGE * IF( LSAME( RANGE, 'A' ) ) THEN IRANGE = 1 ELSE IF( LSAME( RANGE, 'V' ) ) THEN IRANGE = 2 ELSE IF( LSAME( RANGE, 'I' ) ) THEN IRANGE = 3 ELSE IRANGE = 0 END IF * * Decode ORDER * IF( LSAME( ORDER, 'B' ) ) THEN IORDER = 2 ELSE IF( LSAME( ORDER, 'E' ) ) THEN IORDER = 1 ELSE IORDER = 0 END IF * * Check for Errors * IF( IRANGE.LE.0 ) THEN INFO = -1 ELSE IF( IORDER.LE.0 ) THEN INFO = -2 ELSE IF( N.LT.0 ) THEN INFO = -3 ELSE IF( IRANGE.EQ.2 ) THEN IF( VL.GE.VU ) $ INFO = -5 ELSE IF( IRANGE.EQ.3 .AND. ( IL.LT.1 .OR. IL.GT.MAX( 1, N ) ) ) $ THEN INFO = -6 ELSE IF( IRANGE.EQ.3 .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) $ THEN INFO = -7 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEBZ', -INFO ) RETURN END IF * * Initialize error flags * INFO = 0 NCNVRG = .FALSE. TOOFEW = .FALSE. * * Quick return if possible * M = 0 IF( N.EQ.0 ) $ RETURN * * Simplifications: * IF( IRANGE.EQ.3 .AND. IL.EQ.1 .AND. IU.EQ.N ) $ IRANGE = 1 * * Get machine constants * NB is the minimum vector length for vector bisection, or 0 * if only scalar is to be done. * SAFEMN = DLAMCH( 'S' ) ULP = DLAMCH( 'P' ) RTOLI = ULP*RELFAC NB = ILAENV( 1, 'DSTEBZ', ' ', N, -1, -1, -1 ) IF( NB.LE.1 ) $ NB = 0 * * Special Case when N=1 * IF( N.EQ.1 ) THEN NSPLIT = 1 ISPLIT( 1 ) = 1 IF( IRANGE.EQ.2 .AND. ( VL.GE.D( 1 ) .OR. VU.LT.D( 1 ) ) ) THEN M = 0 ELSE W( 1 ) = D( 1 ) IBLOCK( 1 ) = 1 M = 1 END IF RETURN END IF * * Compute Splitting Points * NSPLIT = 1 WORK( N ) = ZERO PIVMIN = ONE * *DIR$ NOVECTOR DO 10 J = 2, N TMP1 = E( J-1 )**2 IF( ABS( D( J )*D( J-1 ) )*ULP**2+SAFEMN.GT.TMP1 ) THEN ISPLIT( NSPLIT ) = J - 1 NSPLIT = NSPLIT + 1 WORK( J-1 ) = ZERO ELSE WORK( J-1 ) = TMP1 PIVMIN = MAX( PIVMIN, TMP1 ) END IF 10 CONTINUE ISPLIT( NSPLIT ) = N PIVMIN = PIVMIN*SAFEMN * * Compute Interval and ATOLI * IF( IRANGE.EQ.3 ) THEN * * RANGE='I': Compute the interval containing eigenvalues * IL through IU. * * Compute Gershgorin interval for entire (split) matrix * and use it as the initial interval * GU = D( 1 ) GL = D( 1 ) TMP1 = ZERO * DO 20 J = 1, N - 1 TMP2 = SQRT( WORK( J ) ) GU = MAX( GU, D( J )+TMP1+TMP2 ) GL = MIN( GL, D( J )-TMP1-TMP2 ) TMP1 = TMP2 20 CONTINUE * GU = MAX( GU, D( N )+TMP1 ) GL = MIN( GL, D( N )-TMP1 ) TNORM = MAX( ABS( GL ), ABS( GU ) ) GL = GL - FUDGE*TNORM*ULP*N - FUDGE*TWO*PIVMIN GU = GU + FUDGE*TNORM*ULP*N + FUDGE*PIVMIN * * Compute Iteration parameters * ITMAX = INT( ( LOG( TNORM+PIVMIN )-LOG( PIVMIN ) ) / $ LOG( TWO ) ) + 2 IF( ABSTOL.LE.ZERO ) THEN ATOLI = ULP*TNORM ELSE ATOLI = ABSTOL END IF * WORK( N+1 ) = GL WORK( N+2 ) = GL WORK( N+3 ) = GU WORK( N+4 ) = GU WORK( N+5 ) = GL WORK( N+6 ) = GU IWORK( 1 ) = -1 IWORK( 2 ) = -1 IWORK( 3 ) = N + 1 IWORK( 4 ) = N + 1 IWORK( 5 ) = IL - 1 IWORK( 6 ) = IU * CALL DLAEBZ( 3, ITMAX, N, 2, 2, NB, ATOLI, RTOLI, PIVMIN, D, E, $ WORK, IWORK( 5 ), WORK( N+1 ), WORK( N+5 ), IOUT, $ IWORK, W, IBLOCK, IINFO ) * IF( IWORK( 6 ).EQ.IU ) THEN WL = WORK( N+1 ) WLU = WORK( N+3 ) NWL = IWORK( 1 ) WU = WORK( N+4 ) WUL = WORK( N+2 ) NWU = IWORK( 4 ) ELSE WL = WORK( N+2 ) WLU = WORK( N+4 ) NWL = IWORK( 2 ) WU = WORK( N+3 ) WUL = WORK( N+1 ) NWU = IWORK( 3 ) END IF * IF( NWL.LT.0 .OR. NWL.GE.N .OR. NWU.LT.1 .OR. NWU.GT.N ) THEN INFO = 4 RETURN END IF ELSE * * RANGE='A' or 'V' -- Set ATOLI * TNORM = MAX( ABS( D( 1 ) )+ABS( E( 1 ) ), $ ABS( D( N ) )+ABS( E( N-1 ) ) ) * DO 30 J = 2, N - 1 TNORM = MAX( TNORM, ABS( D( J ) )+ABS( E( J-1 ) )+ $ ABS( E( J ) ) ) 30 CONTINUE * IF( ABSTOL.LE.ZERO ) THEN ATOLI = ULP*TNORM ELSE ATOLI = ABSTOL END IF * IF( IRANGE.EQ.2 ) THEN WL = VL WU = VU ELSE WL = ZERO WU = ZERO END IF END IF * * Find Eigenvalues -- Loop Over Blocks and recompute NWL and NWU. * NWL accumulates the number of eigenvalues .le. WL, * NWU accumulates the number of eigenvalues .le. WU * M = 0 IEND = 0 INFO = 0 NWL = 0 NWU = 0 * DO 70 JB = 1, NSPLIT IOFF = IEND IBEGIN = IOFF + 1 IEND = ISPLIT( JB ) IN = IEND - IOFF * IF( IN.EQ.1 ) THEN * * Special Case -- IN=1 * IF( IRANGE.EQ.1 .OR. WL.GE.D( IBEGIN )-PIVMIN ) $ NWL = NWL + 1 IF( IRANGE.EQ.1 .OR. WU.GE.D( IBEGIN )-PIVMIN ) $ NWU = NWU + 1 IF( IRANGE.EQ.1 .OR. ( WL.LT.D( IBEGIN )-PIVMIN .AND. WU.GE. $ D( IBEGIN )-PIVMIN ) ) THEN M = M + 1 W( M ) = D( IBEGIN ) IBLOCK( M ) = JB END IF ELSE * * General Case -- IN > 1 * * Compute Gershgorin Interval * and use it as the initial interval * GU = D( IBEGIN ) GL = D( IBEGIN ) TMP1 = ZERO * DO 40 J = IBEGIN, IEND - 1 TMP2 = ABS( E( J ) ) GU = MAX( GU, D( J )+TMP1+TMP2 ) GL = MIN( GL, D( J )-TMP1-TMP2 ) TMP1 = TMP2 40 CONTINUE * GU = MAX( GU, D( IEND )+TMP1 ) GL = MIN( GL, D( IEND )-TMP1 ) BNORM = MAX( ABS( GL ), ABS( GU ) ) GL = GL - FUDGE*BNORM*ULP*IN - FUDGE*PIVMIN GU = GU + FUDGE*BNORM*ULP*IN + FUDGE*PIVMIN * * Compute ATOLI for the current submatrix * IF( ABSTOL.LE.ZERO ) THEN ATOLI = ULP*MAX( ABS( GL ), ABS( GU ) ) ELSE ATOLI = ABSTOL END IF * IF( IRANGE.GT.1 ) THEN IF( GU.LT.WL ) THEN NWL = NWL + IN NWU = NWU + IN GO TO 70 END IF GL = MAX( GL, WL ) GU = MIN( GU, WU ) IF( GL.GE.GU ) $ GO TO 70 END IF * * Set Up Initial Interval * WORK( N+1 ) = GL WORK( N+IN+1 ) = GU CALL DLAEBZ( 1, 0, IN, IN, 1, NB, ATOLI, RTOLI, PIVMIN, $ D( IBEGIN ), E( IBEGIN ), WORK( IBEGIN ), $ IDUMMA, WORK( N+1 ), WORK( N+2*IN+1 ), IM, $ IWORK, W( M+1 ), IBLOCK( M+1 ), IINFO ) * NWL = NWL + IWORK( 1 ) NWU = NWU + IWORK( IN+1 ) IWOFF = M - IWORK( 1 ) * * Compute Eigenvalues * ITMAX = INT( ( LOG( GU-GL+PIVMIN )-LOG( PIVMIN ) ) / $ LOG( TWO ) ) + 2 CALL DLAEBZ( 2, ITMAX, IN, IN, 1, NB, ATOLI, RTOLI, PIVMIN, $ D( IBEGIN ), E( IBEGIN ), WORK( IBEGIN ), $ IDUMMA, WORK( N+1 ), WORK( N+2*IN+1 ), IOUT, $ IWORK, W( M+1 ), IBLOCK( M+1 ), IINFO ) * * Copy Eigenvalues Into W and IBLOCK * Use -JB for block number for unconverged eigenvalues. * DO 60 J = 1, IOUT TMP1 = HALF*( WORK( J+N )+WORK( J+IN+N ) ) * * Flag non-convergence. * IF( J.GT.IOUT-IINFO ) THEN NCNVRG = .TRUE. IB = -JB ELSE IB = JB END IF DO 50 JE = IWORK( J ) + 1 + IWOFF, $ IWORK( J+IN ) + IWOFF W( JE ) = TMP1 IBLOCK( JE ) = IB 50 CONTINUE 60 CONTINUE * M = M + IM END IF 70 CONTINUE * * If RANGE='I', then (WL,WU) contains eigenvalues NWL+1,...,NWU * If NWL+1 < IL or NWU > IU, discard extra eigenvalues. * IF( IRANGE.EQ.3 ) THEN IM = 0 IDISCL = IL - 1 - NWL IDISCU = NWU - IU * IF( IDISCL.GT.0 .OR. IDISCU.GT.0 ) THEN DO 80 JE = 1, M IF( W( JE ).LE.WLU .AND. IDISCL.GT.0 ) THEN IDISCL = IDISCL - 1 ELSE IF( W( JE ).GE.WUL .AND. IDISCU.GT.0 ) THEN IDISCU = IDISCU - 1 ELSE IM = IM + 1 W( IM ) = W( JE ) IBLOCK( IM ) = IBLOCK( JE ) END IF 80 CONTINUE M = IM END IF IF( IDISCL.GT.0 .OR. IDISCU.GT.0 ) THEN * * Code to deal with effects of bad arithmetic: * Some low eigenvalues to be discarded are not in (WL,WLU], * or high eigenvalues to be discarded are not in (WUL,WU] * so just kill off the smallest IDISCL/largest IDISCU * eigenvalues, by simply finding the smallest/largest * eigenvalue(s). * * (If N(w) is monotone non-decreasing, this should never * happen.) * IF( IDISCL.GT.0 ) THEN WKILL = WU DO 100 JDISC = 1, IDISCL IW = 0 DO 90 JE = 1, M IF( IBLOCK( JE ).NE.0 .AND. $ ( W( JE ).LT.WKILL .OR. IW.EQ.0 ) ) THEN IW = JE WKILL = W( JE ) END IF 90 CONTINUE IBLOCK( IW ) = 0 100 CONTINUE END IF IF( IDISCU.GT.0 ) THEN * WKILL = WL DO 120 JDISC = 1, IDISCU IW = 0 DO 110 JE = 1, M IF( IBLOCK( JE ).NE.0 .AND. $ ( W( JE ).GT.WKILL .OR. IW.EQ.0 ) ) THEN IW = JE WKILL = W( JE ) END IF 110 CONTINUE IBLOCK( IW ) = 0 120 CONTINUE END IF IM = 0 DO 130 JE = 1, M IF( IBLOCK( JE ).NE.0 ) THEN IM = IM + 1 W( IM ) = W( JE ) IBLOCK( IM ) = IBLOCK( JE ) END IF 130 CONTINUE M = IM END IF IF( IDISCL.LT.0 .OR. IDISCU.LT.0 ) THEN TOOFEW = .TRUE. END IF END IF * * If ORDER='B', do nothing -- the eigenvalues are already sorted * by block. * If ORDER='E', sort the eigenvalues from smallest to largest * IF( IORDER.EQ.1 .AND. NSPLIT.GT.1 ) THEN DO 150 JE = 1, M - 1 IE = 0 TMP1 = W( JE ) DO 140 J = JE + 1, M IF( W( J ).LT.TMP1 ) THEN IE = J TMP1 = W( J ) END IF 140 CONTINUE * IF( IE.NE.0 ) THEN ITMP1 = IBLOCK( IE ) W( IE ) = W( JE ) IBLOCK( IE ) = IBLOCK( JE ) W( JE ) = TMP1 IBLOCK( JE ) = ITMP1 END IF 150 CONTINUE END IF * INFO = 0 IF( NCNVRG ) $ INFO = INFO + 1 IF( TOOFEW ) $ INFO = INFO + 2 RETURN * * End of DSTEBZ * END SUBROUTINE DSTEIN( N, D, E, M, W, IBLOCK, ISPLIT, Z, LDZ, WORK, $ IWORK, IFAIL, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER INFO, LDZ, M, N * .. * .. Array Arguments .. INTEGER IBLOCK( * ), IFAIL( * ), ISPLIT( * ), $ IWORK( * ) DOUBLE PRECISION D( * ), E( * ), W( * ), WORK( * ), Z( LDZ, * ) * .. * * Purpose * ======= * * DSTEIN computes the eigenvectors of a real symmetric tridiagonal * matrix T corresponding to specified eigenvalues, using inverse * iteration. * * The maximum number of iterations allowed for each eigenvector is * specified by an internal parameter MAXITS (currently set to 5). * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the tridiagonal matrix T. * * E (input) DOUBLE PRECISION array, dimension (N) * The (n-1) subdiagonal elements of the tridiagonal matrix * T, in elements 1 to N-1. E(N) need not be set. * * M (input) INTEGER * The number of eigenvectors to be found. 0 <= M <= N. * * W (input) DOUBLE PRECISION array, dimension (N) * The first M elements of W contain the eigenvalues for * which eigenvectors are to be computed. The eigenvalues * should be grouped by split-off block and ordered from * smallest to largest within the block. ( The output array * W from DSTEBZ with ORDER = 'B' is expected here. ) * * IBLOCK (input) INTEGER array, dimension (N) * The submatrix indices associated with the corresponding * eigenvalues in W; IBLOCK(i)=1 if eigenvalue W(i) belongs to * the first submatrix from the top, =2 if W(i) belongs to * the second submatrix, etc. ( The output array IBLOCK * from DSTEBZ is expected here. ) * * ISPLIT (input) INTEGER array, dimension (N) * The splitting points, at which T breaks up into submatrices. * The first submatrix consists of rows/columns 1 to * ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1 * through ISPLIT( 2 ), etc. * ( The output array ISPLIT from DSTEBZ is expected here. ) * * Z (output) DOUBLE PRECISION array, dimension (LDZ, M) * The computed eigenvectors. The eigenvector associated * with the eigenvalue W(i) is stored in the i-th column of * Z. Any vector which fails to converge is set to its current * iterate after MAXITS iterations. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= max(1,N). * * WORK (workspace) DOUBLE PRECISION array, dimension (5*N) * * IWORK (workspace) INTEGER array, dimension (N) * * IFAIL (output) INTEGER array, dimension (M) * On normal exit, all elements of IFAIL are zero. * If one or more eigenvectors fail to converge after * MAXITS iterations, then their indices are stored in * array IFAIL. * * INFO (output) INTEGER * = 0: successful exit. * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = i, then i eigenvectors failed to converge * in MAXITS iterations. Their indices are stored in * array IFAIL. * * Internal Parameters * =================== * * MAXITS INTEGER, default = 5 * The maximum number of iterations performed. * * EXTRA INTEGER, default = 2 * The number of iterations performed after norm growth * criterion is satisfied, should be at least 1. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TEN, ODM3, ODM1 PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0, TEN = 1.0D+1, $ ODM3 = 1.0D-3, ODM1 = 1.0D-1 ) INTEGER MAXITS, EXTRA PARAMETER ( MAXITS = 5, EXTRA = 2 ) * .. * .. Local Scalars .. INTEGER B1, BLKSIZ, BN, GPIND, I, IINFO, INDRV1, $ INDRV2, INDRV3, INDRV4, INDRV5, ITS, J, J1, $ JBLK, JMAX, NBLK, NRMCHK DOUBLE PRECISION DTPCRT, EPS, EPS1, NRM, ONENRM, ORTOL, PERTOL, $ SCL, SEP, TOL, XJ, XJM, ZTR * .. * .. Local Arrays .. INTEGER ISEED( 4 ) * .. * .. External Functions .. INTEGER IDAMAX DOUBLE PRECISION DASUM, DDOT, DLAMCH, DNRM2 EXTERNAL IDAMAX, DASUM, DDOT, DLAMCH, DNRM2 * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DLAGTF, DLAGTS, DLARNV, DSCAL, $ XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SQRT * .. * .. Executable Statements .. * * Test the input parameters. * INFO = 0 DO 10 I = 1, M IFAIL( I ) = 0 10 CONTINUE * IF( N.LT.0 ) THEN INFO = -1 ELSE IF( M.LT.0 .OR. M.GT.N ) THEN INFO = -4 ELSE IF( LDZ.LT.MAX( 1, N ) ) THEN INFO = -9 ELSE DO 20 J = 2, M IF( IBLOCK( J ).LT.IBLOCK( J-1 ) ) THEN INFO = -6 GO TO 30 END IF IF( IBLOCK( J ).EQ.IBLOCK( J-1 ) .AND. W( J ).LT.W( J-1 ) ) $ THEN INFO = -5 GO TO 30 END IF 20 CONTINUE 30 CONTINUE END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DSTEIN', -INFO ) RETURN END IF * * Quick return if possible * IF( N.EQ.0 .OR. M.EQ.0 ) THEN RETURN ELSE IF( N.EQ.1 ) THEN Z( 1, 1 ) = ONE RETURN END IF * * Get machine constants. * EPS = DLAMCH( 'Precision' ) * * Initialize seed for random number generator DLARNV. * DO 40 I = 1, 4 ISEED( I ) = 1 40 CONTINUE * * Initialize pointers. * INDRV1 = 0 INDRV2 = INDRV1 + N INDRV3 = INDRV2 + N INDRV4 = INDRV3 + N INDRV5 = INDRV4 + N * * Compute eigenvectors of matrix blocks. * J1 = 1 DO 160 NBLK = 1, IBLOCK( M ) * * Find starting and ending indices of block nblk. * IF( NBLK.EQ.1 ) THEN B1 = 1 ELSE B1 = ISPLIT( NBLK-1 ) + 1 END IF BN = ISPLIT( NBLK ) BLKSIZ = BN - B1 + 1 IF( BLKSIZ.EQ.1 ) $ GO TO 60 GPIND = B1 * * Compute reorthogonalization criterion and stopping criterion. * ONENRM = ABS( D( B1 ) ) + ABS( E( B1 ) ) ONENRM = MAX( ONENRM, ABS( D( BN ) )+ABS( E( BN-1 ) ) ) DO 50 I = B1 + 1, BN - 1 ONENRM = MAX( ONENRM, ABS( D( I ) )+ABS( E( I-1 ) )+ $ ABS( E( I ) ) ) 50 CONTINUE ORTOL = ODM3*ONENRM * DTPCRT = SQRT( ODM1 / BLKSIZ ) * * Loop through eigenvalues of block nblk. * 60 CONTINUE JBLK = 0 DO 150 J = J1, M IF( IBLOCK( J ).NE.NBLK ) THEN J1 = J GO TO 160 END IF JBLK = JBLK + 1 XJ = W( J ) * * Skip all the work if the block size is one. * IF( BLKSIZ.EQ.1 ) THEN WORK( INDRV1+1 ) = ONE GO TO 120 END IF * * If eigenvalues j and j-1 are too close, add a relatively * small perturbation. * IF( JBLK.GT.1 ) THEN EPS1 = ABS( EPS*XJ ) PERTOL = TEN*EPS1 SEP = XJ - XJM IF( SEP.LT.PERTOL ) $ XJ = XJM + PERTOL END IF * ITS = 0 NRMCHK = 0 * * Get random starting vector. * CALL DLARNV( 2, ISEED, BLKSIZ, WORK( INDRV1+1 ) ) * * Copy the matrix T so it won't be destroyed in factorization. * CALL DCOPY( BLKSIZ, D( B1 ), 1, WORK( INDRV4+1 ), 1 ) CALL DCOPY( BLKSIZ-1, E( B1 ), 1, WORK( INDRV2+2 ), 1 ) CALL DCOPY( BLKSIZ-1, E( B1 ), 1, WORK( INDRV3+1 ), 1 ) * * Compute LU factors with partial pivoting ( PT = LU ) * TOL = ZERO CALL DLAGTF( BLKSIZ, WORK( INDRV4+1 ), XJ, WORK( INDRV2+2 ), $ WORK( INDRV3+1 ), TOL, WORK( INDRV5+1 ), IWORK, $ IINFO ) * * Update iteration count. * 70 CONTINUE ITS = ITS + 1 IF( ITS.GT.MAXITS ) $ GO TO 100 * * Normalize and scale the righthand side vector Pb. * SCL = BLKSIZ*ONENRM*MAX( EPS, $ ABS( WORK( INDRV4+BLKSIZ ) ) ) / $ DASUM( BLKSIZ, WORK( INDRV1+1 ), 1 ) CALL DSCAL( BLKSIZ, SCL, WORK( INDRV1+1 ), 1 ) * * Solve the system LU = Pb. * CALL DLAGTS( -1, BLKSIZ, WORK( INDRV4+1 ), WORK( INDRV2+2 ), $ WORK( INDRV3+1 ), WORK( INDRV5+1 ), IWORK, $ WORK( INDRV1+1 ), TOL, IINFO ) * * Reorthogonalize by modified Gram-Schmidt if eigenvalues are * close enough. * IF( JBLK.EQ.1 ) $ GO TO 90 IF( ABS( XJ-XJM ).GT.ORTOL ) $ GPIND = J IF( GPIND.NE.J ) THEN DO 80 I = GPIND, J - 1 ZTR = -DDOT( BLKSIZ, WORK( INDRV1+1 ), 1, Z( B1, I ), $ 1 ) CALL DAXPY( BLKSIZ, ZTR, Z( B1, I ), 1, $ WORK( INDRV1+1 ), 1 ) 80 CONTINUE END IF * * Check the infinity norm of the iterate. * 90 CONTINUE JMAX = IDAMAX( BLKSIZ, WORK( INDRV1+1 ), 1 ) NRM = ABS( WORK( INDRV1+JMAX ) ) * * Continue for additional iterations after norm reaches * stopping criterion. * IF( NRM.LT.DTPCRT ) $ GO TO 70 NRMCHK = NRMCHK + 1 IF( NRMCHK.LT.EXTRA+1 ) $ GO TO 70 * GO TO 110 * * If stopping criterion was not satisfied, update info and * store eigenvector number in array ifail. * 100 CONTINUE INFO = INFO + 1 IFAIL( INFO ) = J * * Accept iterate as jth eigenvector. * 110 CONTINUE SCL = ONE / DNRM2( BLKSIZ, WORK( INDRV1+1 ), 1 ) JMAX = IDAMAX( BLKSIZ, WORK( INDRV1+1 ), 1 ) IF( WORK( INDRV1+JMAX ).LT.ZERO ) $ SCL = -SCL CALL DSCAL( BLKSIZ, SCL, WORK( INDRV1+1 ), 1 ) 120 CONTINUE DO 130 I = 1, N Z( I, J ) = ZERO 130 CONTINUE DO 140 I = 1, BLKSIZ Z( B1+I-1, J ) = WORK( INDRV1+I ) 140 CONTINUE * * Save the shift to check eigenvalue spacing at next * iteration. * XJM = XJ * 150 CONTINUE 160 CONTINUE * RETURN * * End of DSTEIN * END SUBROUTINE DORMQL( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, LWORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, LWORK, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORMQL overwrites the general real M-by-N matrix C with * * SIDE = 'L' SIDE = 'R' * TRANS = 'N': Q * C C * Q * TRANS = 'T': Q**T * C C * Q**T * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(k) . . . H(2) H(1) * * as returned by DGEQLF. Q is of order M if SIDE = 'L' and of order N * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q**T from the Left; * = 'R': apply Q or Q**T from the Right. * * TRANS (input) CHARACTER*1 * = 'N': No transpose, apply Q; * = 'T': Transpose, apply Q**T. * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,K) * The i-th column must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGEQLF in the last k columns of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. * If SIDE = 'L', LDA >= max(1,M); * if SIDE = 'R', LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQLF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the M-by-N matrix C. * On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) * On exit, if INFO = 0, WORK(1) returns the optimal LWORK. * * LWORK (input) INTEGER * The dimension of the array WORK. * If SIDE = 'L', LWORK >= max(1,N); * if SIDE = 'R', LWORK >= max(1,M). * For optimum performance LWORK >= N*NB if SIDE = 'L', and * LWORK >= M*NB if SIDE = 'R', where NB is the optimal * blocksize. * * If LWORK = -1, then a workspace query is assumed; the routine * only calculates the optimal size of the WORK array, returns * this value as the first entry of the WORK array, and no error * message related to LWORK is issued by XERBLA. * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. INTEGER NBMAX, LDT PARAMETER ( NBMAX = 64, LDT = NBMAX+1 ) * .. * .. Local Scalars .. LOGICAL LEFT, LQUERY, NOTRAN INTEGER I, I1, I2, I3, IB, IINFO, IWS, LDWORK, LWKOPT, $ MI, NB, NBMIN, NI, NQ, NW * .. * .. Local Arrays .. DOUBLE PRECISION T( LDT, NBMAX ) * .. * .. External Functions .. LOGICAL LSAME INTEGER ILAENV EXTERNAL LSAME, ILAENV * .. * .. External Subroutines .. EXTERNAL DLARFB, DLARFT, DORM2L, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX, MIN * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) LQUERY = ( LWORK.EQ.-1 ) * * NQ is the order of Q and NW is the minimum dimension of WORK * IF( LEFT ) THEN NQ = M NW = N ELSE NQ = N NW = M END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, NQ ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 ELSE IF( LWORK.LT.MAX( 1, NW ) .AND. .NOT.LQUERY ) THEN INFO = -12 END IF * IF( INFO.EQ.0 ) THEN * * Determine the block size. NB may be at most NBMAX, where NBMAX * is used to define the local array T. * NB = MIN( NBMAX, ILAENV( 1, 'DORMQL', SIDE // TRANS, M, N, K, $ -1 ) ) LWKOPT = MAX( 1, NW )*NB WORK( 1 ) = LWKOPT END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORMQL', -INFO ) RETURN ELSE IF( LQUERY ) THEN RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) THEN WORK( 1 ) = 1 RETURN END IF * NBMIN = 2 LDWORK = NW IF( NB.GT.1 .AND. NB.LT.K ) THEN IWS = NW*NB IF( LWORK.LT.IWS ) THEN NB = LWORK / LDWORK NBMIN = MAX( 2, ILAENV( 2, 'DORMQL', SIDE // TRANS, M, N, K, $ -1 ) ) END IF ELSE IWS = NW END IF * IF( NB.LT.NBMIN .OR. NB.GE.K ) THEN * * Use unblocked code * CALL DORM2L( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, WORK, $ IINFO ) ELSE * * Use blocked code * IF( ( LEFT .AND. NOTRAN ) .OR. $ ( .NOT.LEFT .AND. .NOT.NOTRAN ) ) THEN I1 = 1 I2 = K I3 = NB ELSE I1 = ( ( K-1 ) / NB )*NB + 1 I2 = 1 I3 = -NB END IF * IF( LEFT ) THEN NI = N ELSE MI = M END IF * DO 10 I = I1, I2, I3 IB = MIN( NB, K-I+1 ) * * Form the triangular factor of the block reflector * H = H(i+ib-1) . . . H(i+1) H(i) * CALL DLARFT( 'Backward', 'Columnwise', NQ-K+I+IB-1, IB, $ A( 1, I ), LDA, TAU( I ), T, LDT ) IF( LEFT ) THEN * * H or H' is applied to C(1:m-k+i+ib-1,1:n) * MI = M - K + I + IB - 1 ELSE * * H or H' is applied to C(1:m,1:n-k+i+ib-1) * NI = N - K + I + IB - 1 END IF * * Apply H or H' * CALL DLARFB( SIDE, TRANS, 'Backward', 'Columnwise', MI, NI, $ IB, A( 1, I ), LDA, T, LDT, C, LDC, WORK, $ LDWORK ) 10 CONTINUE END IF WORK( 1 ) = LWKOPT RETURN * * End of DORMQL * END SUBROUTINE DLARRE( N, D, E, TOL, NSPLIT, ISPLIT, M, W, WOFF, $ GERSCH, WORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, M, N, NSPLIT DOUBLE PRECISION TOL * .. * .. Array Arguments .. INTEGER ISPLIT( * ) DOUBLE PRECISION D( * ), E( * ), GERSCH( * ), W( * ), WOFF( * ), $ WORK( * ) * .. * * Purpose * ======= * * Given the tridiagonal matrix T, DLARRE sets "small" off-diagonal * elements to zero, and for each unreduced block T_i, it finds * (i) the numbers sigma_i * (ii) the base T_i - sigma_i I = L_i D_i L_i^T representations and * (iii) eigenvalues of each L_i D_i L_i^T. * The representations and eigenvalues found are then used by * DSTEGR to compute the eigenvectors of a symmetric tridiagonal * matrix. Currently, the base representations are limited to being * positive or negative definite, and the eigenvalues of the definite * matrices are found by the dqds algorithm (subroutine DLASQ2). As * an added benefit, DLARRE also outputs the n Gerschgorin * intervals for each L_i D_i L_i^T. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the tridiagonal * matrix T. * On exit, the n diagonal elements of the diagonal * matrices D_i. * * E (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the (n-1) subdiagonal elements of the tridiagonal * matrix T; E(N) need not be set. * On exit, the subdiagonal elements of the unit bidiagonal * matrices L_i. * * TOL (input) DOUBLE PRECISION * The threshold for splitting. If on input |E(i)| < TOL, then * the matrix T is split into smaller blocks. * * NSPLIT (input) INTEGER * The number of blocks T splits into. 1 <= NSPLIT <= N. * * ISPLIT (output) INTEGER array, dimension (2*N) * The splitting points, at which T breaks up into submatrices. * The first submatrix consists of rows/columns 1 to ISPLIT(1), * the second of rows/columns ISPLIT(1)+1 through ISPLIT(2), * etc., and the NSPLIT-th consists of rows/columns * ISPLIT(NSPLIT-1)+1 through ISPLIT(NSPLIT)=N. * * M (output) INTEGER * The total number of eigenvalues (of all the L_i D_i L_i^T) * found. * * W (output) DOUBLE PRECISION array, dimension (N) * The first M elements contain the eigenvalues. The * eigenvalues of each of the blocks, L_i D_i L_i^T, are * sorted in ascending order. * * WOFF (output) DOUBLE PRECISION array, dimension (N) * The NSPLIT base points sigma_i. * * GERSCH (output) DOUBLE PRECISION array, dimension (2*N) * The n Gerschgorin intervals. * * WORK (input) DOUBLE PRECISION array, dimension (4*N???) * Workspace. * * INFO (output) INTEGER * Output error code from DLASQ2 * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE, TWO, FOUR, FOURTH PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0, $ FOUR = 4.0D0, FOURTH = ONE / FOUR ) * .. * .. Local Scalars .. INTEGER CNT, I, IBEGIN, IEND, IN, J, JBLK, MAXCNT DOUBLE PRECISION DELTA, EPS, GL, GU, NRM, OFFD, S, SGNDEF, $ SIGMA, TAU, TMP1, WIDTH * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. External Subroutines .. EXTERNAL DCOPY, DLASQ2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * INFO = 0 EPS = DLAMCH( 'Precision' ) * * Compute Splitting Points * NSPLIT = 1 DO 10 I = 1, N - 1 IF( ABS( E( I ) ).LE.TOL ) THEN ISPLIT( NSPLIT ) = I NSPLIT = NSPLIT + 1 END IF 10 CONTINUE ISPLIT( NSPLIT ) = N * IBEGIN = 1 DO 170 JBLK = 1, NSPLIT IEND = ISPLIT( JBLK ) IF( IBEGIN.EQ.IEND ) THEN W( IBEGIN ) = D( IBEGIN ) WOFF( JBLK ) = ZERO IBEGIN = IEND + 1 GO TO 170 END IF IN = IEND - IBEGIN + 1 * * Form the n Gerschgorin intervals * GL = D( IBEGIN ) - ABS( E( IBEGIN ) ) GU = D( IBEGIN ) + ABS( E( IBEGIN ) ) GERSCH( 2*IBEGIN-1 ) = GL GERSCH( 2*IBEGIN ) = GU GERSCH( 2*IEND-1 ) = D( IEND ) - ABS( E( IEND-1 ) ) GERSCH( 2*IEND ) = D( IEND ) + ABS( E( IEND-1 ) ) GL = MIN( GERSCH( 2*IEND-1 ), GL ) GU = MAX( GERSCH( 2*IEND ), GU ) DO 20 I = IBEGIN + 1, IEND - 1 OFFD = ABS( E( I-1 ) ) + ABS( E( I ) ) GERSCH( 2*I-1 ) = D( I ) - OFFD GL = MIN( GERSCH( 2*I-1 ), GL ) GERSCH( 2*I ) = D( I ) + OFFD GU = MAX( GERSCH( 2*I ), GU ) 20 CONTINUE NRM = MAX( ABS( GL ), ABS( GU ) ) * * Find the number SIGMA where the base representation * T - sigma I = L D L^T is to be formed. * WIDTH = GU - GL DO 30 I = IBEGIN, IEND - 1 WORK( I ) = E( I )*E( I ) 30 CONTINUE DO 50 J = 1, 2 IF( J.EQ.1 ) THEN TAU = GL + FOURTH*WIDTH ELSE TAU = GU - FOURTH*WIDTH END IF TMP1 = D( IBEGIN ) - TAU IF( TMP1.LT.ZERO ) THEN CNT = 1 ELSE CNT = 0 END IF DO 40 I = IBEGIN + 1, IEND TMP1 = D( I ) - TAU - WORK( I-1 ) / TMP1 IF( TMP1.LT.ZERO ) $ CNT = CNT + 1 40 CONTINUE IF( CNT.EQ.0 ) THEN GL = TAU ELSE IF( CNT.EQ.IN ) THEN GU = TAU END IF IF( J.EQ.1 ) THEN MAXCNT = CNT SIGMA = GL SGNDEF = ONE ELSE IF( IN-CNT.GT.MAXCNT ) THEN SIGMA = GU SGNDEF = -ONE END IF END IF 50 CONTINUE * * Find the base L D L^T representation * WORK( 3*IN ) = ONE DELTA = EPS TAU = SGNDEF*NRM 60 CONTINUE SIGMA = SIGMA - DELTA*TAU WORK( 1 ) = D( IBEGIN ) - SIGMA J = IBEGIN DO 70 I = 1, IN - 1 WORK( 2*IN+I ) = ONE / WORK( 2*I-1 ) TMP1 = E( J )*WORK( 2*IN+I ) WORK( 2*I+1 ) = ( D( J+1 )-SIGMA ) - TMP1*E( J ) WORK( 2*I ) = TMP1 J = J + 1 70 CONTINUE DO 80 I = IN, 1, -1 TMP1 = SGNDEF*WORK( 2*I-1 ) IF( TMP1.LT.ZERO .OR. WORK( 2*IN+I ).EQ.ZERO .OR. .NOT. $ ( TMP1.GT.ZERO .OR. TMP1.LT.ONE ) ) THEN DELTA = TWO*DELTA GO TO 60 END IF J = J - 1 80 CONTINUE * J = IBEGIN D( IBEGIN ) = WORK( 1 ) WORK( 1 ) = ABS( WORK( 1 ) ) DO 90 I = 1, IN - 1 TMP1 = E( J ) E( J ) = WORK( 2*I ) WORK( 2*I ) = ABS( TMP1*WORK( 2*I ) ) J = J + 1 D( J ) = WORK( 2*I+1 ) WORK( 2*I+1 ) = ABS( WORK( 2*I+1 ) ) 90 CONTINUE * CALL DLASQ2( IN, WORK, INFO ) * TAU = SGNDEF*WORK( IN ) WORK( 3*IN ) = ONE DELTA = TWO*EPS 100 CONTINUE TAU = TAU*( ONE-DELTA ) * S = -TAU J = IBEGIN DO 110 I = 1, IN - 1 WORK( I ) = D( J ) + S WORK( 2*IN+I ) = ONE / WORK( I ) * WORK( N+I ) = ( E( I ) * D( I ) ) / WORK( I ) WORK( IN+I ) = ( E( J )*D( J ) )*WORK( 2*IN+I ) S = S*WORK( IN+I )*E( J ) - TAU J = J + 1 110 CONTINUE WORK( IN ) = D( IEND ) + S * * Checking to see if all the diagonal elements of the new * L D L^T representation have the same sign * DO 120 I = IN, 1, -1 TMP1 = SGNDEF*WORK( I ) IF( TMP1.LT.ZERO .OR. WORK( 2*IN+I ).EQ.ZERO .OR. .NOT. $ ( TMP1.GT.ZERO .OR. TMP1.LT.ONE ) ) THEN DELTA = TWO*DELTA GO TO 100 END IF 120 CONTINUE * SIGMA = SIGMA + TAU CALL DCOPY( IN, WORK, 1, D( IBEGIN ), 1 ) CALL DCOPY( IN-1, WORK( IN+1 ), 1, E( IBEGIN ), 1 ) WOFF( JBLK ) = SIGMA * * Update the n Gerschgorin intervals * DO 130 I = IBEGIN, IEND GERSCH( 2*I-1 ) = GERSCH( 2*I-1 ) - SIGMA GERSCH( 2*I ) = GERSCH( 2*I ) - SIGMA 130 CONTINUE * * Compute the eigenvalues of L D L^T. * J = IBEGIN DO 140 I = 1, IN - 1 WORK( 2*I-1 ) = ABS( D( J ) ) WORK( 2*I ) = E( J )*E( J )*WORK( 2*I-1 ) J = J + 1 140 CONTINUE WORK( 2*IN-1 ) = ABS( D( IEND ) ) * CALL DLASQ2( IN, WORK, INFO ) * J = IBEGIN IF( SGNDEF.GT.ZERO ) THEN DO 150 I = 1, IN W( J ) = WORK( IN-I+1 ) J = J + 1 150 CONTINUE ELSE DO 160 I = 1, IN W( J ) = -WORK( I ) J = J + 1 160 CONTINUE END IF IBEGIN = IEND + 1 170 CONTINUE M = N * RETURN * * End of DLARRE * END SUBROUTINE DLARRV( N, D, L, ISPLIT, M, W, IBLOCK, GERSCH, TOL, Z, $ LDZ, ISUPPZ, WORK, IWORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, LDZ, M, N DOUBLE PRECISION TOL * .. * .. Array Arguments .. INTEGER IBLOCK( * ), ISPLIT( * ), ISUPPZ( * ), $ IWORK( * ) DOUBLE PRECISION D( * ), GERSCH( * ), L( * ), W( * ), WORK( * ), $ Z( LDZ, * ) * .. * * Purpose * ======= * * DLARRV computes the eigenvectors of the tridiagonal matrix * T = L D L^T given L, D and the eigenvalues of L D L^T. * The input eigenvalues should have high relative accuracy with * respect to the entries of L and D. The desired accuracy of the * output can be specified by the input parameter TOL. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. N >= 0. * * D (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the n diagonal elements of the diagonal matrix D. * On exit, D may be overwritten. * * L (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, the (n-1) subdiagonal elements of the unit * bidiagonal matrix L in elements 1 to N-1 of L. L(N) need * not be set. On exit, L is overwritten. * * ISPLIT (input) INTEGER array, dimension (N) * The splitting points, at which T breaks up into submatrices. * The first submatrix consists of rows/columns 1 to * ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1 * through ISPLIT( 2 ), etc. * * TOL (input) DOUBLE PRECISION * The absolute error tolerance for the * eigenvalues/eigenvectors. * Errors in the input eigenvalues must be bounded by TOL. * The eigenvectors output have residual norms * bounded by TOL, and the dot products between different * eigenvectors are bounded by TOL. TOL must be at least * N*EPS*|T|, where EPS is the machine precision and |T| is * the 1-norm of the tridiagonal matrix. * * M (input) INTEGER * The total number of eigenvalues found. 0 <= M <= N. * If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. * * W (input) DOUBLE PRECISION array, dimension (N) * The first M elements of W contain the eigenvalues for * which eigenvectors are to be computed. The eigenvalues * should be grouped by split-off block and ordered from * smallest to largest within the block ( The output array * W from DLARRE is expected here ). * Errors in W must be bounded by TOL (see above). * * IBLOCK (input) INTEGER array, dimension (N) * The submatrix indices associated with the corresponding * eigenvalues in W; IBLOCK(i)=1 if eigenvalue W(i) belongs to * the first submatrix from the top, =2 if W(i) belongs to * the second submatrix, etc. * * Z (output) DOUBLE PRECISION array, dimension (LDZ, max(1,M) ) * If JOBZ = 'V', then if INFO = 0, the first M columns of Z * contain the orthonormal eigenvectors of the matrix T * corresponding to the selected eigenvalues, with the i-th * column of Z holding the eigenvector associated with W(i). * If JOBZ = 'N', then Z is not referenced. * Note: the user must ensure that at least max(1,M) columns are * supplied in the array Z; if RANGE = 'V', the exact value of M * is not known in advance and an upper bound must be used. * * LDZ (input) INTEGER * The leading dimension of the array Z. LDZ >= 1, and if * JOBZ = 'V', LDZ >= max(1,N). * * ISUPPZ (output) INTEGER ARRAY, dimension ( 2*max(1,M) ) * The support of the eigenvectors in Z, i.e., the indices * indicating the nonzero elements in Z. The i-th eigenvector * is nonzero only in elements ISUPPZ( 2*i-1 ) through * ISUPPZ( 2*i ). * * WORK (workspace) DOUBLE PRECISION array, dimension (13*N) * * IWORK (workspace) INTEGER array, dimension (6*N) * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * > 0: if INFO = 1, internal error in DLARRB * if INFO = 2, internal error in DSTEIN * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. INTEGER MGSSIZ PARAMETER ( MGSSIZ = 20 ) DOUBLE PRECISION ZERO, ONE, FOUR PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, FOUR = 4.0D0 ) * .. * .. Local Scalars .. LOGICAL MGSCLS INTEGER I, IBEGIN, IEND, IINDC1, IINDC2, IINDR, IINDWK, $ IINFO, IM, IN, INDERR, INDGAP, INDLD, INDLLD, $ INDWRK, ITER, ITMP1, ITMP2, J, JBLK, K, KTOT, $ LSBDPT, MAXITR, NCLUS, NDEPTH, NDONE, NEWCLS, $ NEWFRS, NEWFTT, NEWLST, NEWSIZ, NSPLIT, OLDCLS, $ OLDFST, OLDIEN, OLDLST, OLDNCL, P, Q DOUBLE PRECISION EPS, GAP, LAMBDA, MGSTOL, MINGMA, MINRGP, $ NRMINV, RELGAP, RELTOL, RESID, RQCORR, SIGMA, $ TMP1, ZTZ * .. * .. External Functions .. DOUBLE PRECISION DDOT, DLAMCH, DNRM2 EXTERNAL DDOT, DLAMCH, DNRM2 * .. * .. External Subroutines .. EXTERNAL DAXPY, DCOPY, DLAR1V, DLARRB, DLARRF, DLASET, $ DSCAL, DSTEIN * .. * .. Intrinsic Functions .. INTRINSIC ABS, DBLE, MAX, MIN, SQRT * .. * .. Local Arrays .. INTEGER TEMP( 1 ) * .. * .. Executable Statements .. * * Test the input parameters. * INDERR = N + 1 INDLD = 2*N INDLLD = 3*N INDGAP = 4*N INDWRK = 5*N + 1 * IINDR = N IINDC1 = 2*N IINDC2 = 3*N IINDWK = 4*N + 1 * EPS = DLAMCH( 'Precision' ) * DO 10 I = 1, 2*N IWORK( I ) = 0 10 CONTINUE DO 20 I = 1, M WORK( INDERR+I-1 ) = EPS*ABS( W( I ) ) 20 CONTINUE CALL DLASET( 'Full', N, N, ZERO, ZERO, Z, LDZ ) MGSTOL = 5.0D0*EPS * NSPLIT = IBLOCK( M ) IBEGIN = 1 DO 170 JBLK = 1, NSPLIT IEND = ISPLIT( JBLK ) * * Find the eigenvectors of the submatrix indexed IBEGIN * through IEND. * IF( IBEGIN.EQ.IEND ) THEN Z( IBEGIN, IBEGIN ) = ONE ISUPPZ( 2*IBEGIN-1 ) = IBEGIN ISUPPZ( 2*IBEGIN ) = IBEGIN IBEGIN = IEND + 1 GO TO 170 END IF OLDIEN = IBEGIN - 1 IN = IEND - OLDIEN RELTOL = MIN( 1.0D-2, ONE / DBLE( IN ) ) IM = IN CALL DCOPY( IM, W( IBEGIN ), 1, WORK, 1 ) DO 30 I = 1, IN - 1 WORK( INDGAP+I ) = WORK( I+1 ) - WORK( I ) 30 CONTINUE WORK( INDGAP+IN ) = MAX( ABS( WORK( IN ) ), EPS ) NDONE = 0 * NDEPTH = 0 LSBDPT = 1 NCLUS = 1 IWORK( IINDC1+1 ) = 1 IWORK( IINDC1+2 ) = IN * * While( NDONE.LT.IM ) do * 40 CONTINUE IF( NDONE.LT.IM ) THEN OLDNCL = NCLUS NCLUS = 0 LSBDPT = 1 - LSBDPT DO 150 I = 1, OLDNCL IF( LSBDPT.EQ.0 ) THEN OLDCLS = IINDC1 NEWCLS = IINDC2 ELSE OLDCLS = IINDC2 NEWCLS = IINDC1 END IF * * If NDEPTH > 1, retrieve the relatively robust * representation (RRR) and perform limited bisection * (if necessary) to get approximate eigenvalues. * J = OLDCLS + 2*I OLDFST = IWORK( J-1 ) OLDLST = IWORK( J ) IF( NDEPTH.GT.0 ) THEN J = OLDIEN + OLDFST CALL DCOPY( IN, Z( IBEGIN, J ), 1, D( IBEGIN ), 1 ) CALL DCOPY( IN, Z( IBEGIN, J+1 ), 1, L( IBEGIN ), 1 ) SIGMA = L( IEND ) END IF K = IBEGIN DO 50 J = 1, IN - 1 WORK( INDLD+J ) = D( K )*L( K ) WORK( INDLLD+J ) = WORK( INDLD+J )*L( K ) K = K + 1 50 CONTINUE IF( NDEPTH.GT.0 ) THEN CALL DLARRB( IN, D( IBEGIN ), L( IBEGIN ), $ WORK( INDLD+1 ), WORK( INDLLD+1 ), $ OLDFST, OLDLST, SIGMA, RELTOL, WORK, $ WORK( INDGAP+1 ), WORK( INDERR ), $ WORK( INDWRK ), IWORK( IINDWK ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = 1 RETURN END IF END IF * * Classify eigenvalues of the current representation (RRR) * as (i) isolated, (ii) loosely clustered or (iii) tightly * clustered * NEWFRS = OLDFST DO 140 J = OLDFST, OLDLST IF( J.EQ.OLDLST .OR. WORK( INDGAP+J ).GE.RELTOL* $ ABS( WORK( J ) ) ) THEN NEWLST = J ELSE * * continue (to the next loop) * RELGAP = WORK( INDGAP+J ) / ABS( WORK( J ) ) IF( J.EQ.NEWFRS ) THEN MINRGP = RELGAP ELSE MINRGP = MIN( MINRGP, RELGAP ) END IF GO TO 140 END IF NEWSIZ = NEWLST - NEWFRS + 1 MAXITR = 10 NEWFTT = OLDIEN + NEWFRS IF( NEWSIZ.GT.1 ) THEN MGSCLS = NEWSIZ.LE.MGSSIZ .AND. MINRGP.GE.MGSTOL IF( .NOT.MGSCLS ) THEN CALL DLARRF( IN, D( IBEGIN ), L( IBEGIN ), $ WORK( INDLD+1 ), WORK( INDLLD+1 ), $ NEWFRS, NEWLST, WORK, $ Z( IBEGIN, NEWFTT ), $ Z( IBEGIN, NEWFTT+1 ), $ WORK( INDWRK ), IWORK( IINDWK ), $ INFO ) IF( INFO.EQ.0 ) THEN NCLUS = NCLUS + 1 K = NEWCLS + 2*NCLUS IWORK( K-1 ) = NEWFRS IWORK( K ) = NEWLST ELSE INFO = 0 IF( MINRGP.GE.MGSTOL ) THEN MGSCLS = .TRUE. ELSE * * Call DSTEIN to process this tight cluster. * This happens only if MINRGP <= MGSTOL * and DLARRF returns INFO = 1. The latter * means that a new RRR to "break" the * cluster could not be found. * WORK( INDWRK ) = D( IBEGIN ) DO 60 K = 1, IN - 1 WORK( INDWRK+K ) = D( IBEGIN+K ) + $ WORK( INDLLD+K ) 60 CONTINUE DO 70 K = 1, NEWSIZ IWORK( IINDWK+K-1 ) = 1 70 CONTINUE DO 80 K = NEWFRS, NEWLST ISUPPZ( 2*( IBEGIN+K )-3 ) = 1 ISUPPZ( 2*( IBEGIN+K )-2 ) = IN 80 CONTINUE TEMP( 1 ) = IN CALL DSTEIN( IN, WORK( INDWRK ), $ WORK( INDLD+1 ), NEWSIZ, $ WORK( NEWFRS ), $ IWORK( IINDWK ), TEMP( 1 ), $ Z( IBEGIN, NEWFTT ), LDZ, $ WORK( INDWRK+IN ), $ IWORK( IINDWK+IN ), $ IWORK( IINDWK+2*IN ), IINFO ) IF( IINFO.NE.0 ) THEN INFO = 2 RETURN END IF NDONE = NDONE + NEWSIZ END IF END IF END IF ELSE MGSCLS = .FALSE. END IF IF( NEWSIZ.EQ.1 .OR. MGSCLS ) THEN KTOT = NEWFTT DO 100 K = NEWFRS, NEWLST ITER = 0 90 CONTINUE LAMBDA = WORK( K ) CALL DLAR1V( IN, 1, IN, LAMBDA, D( IBEGIN ), $ L( IBEGIN ), WORK( INDLD+1 ), $ WORK( INDLLD+1 ), $ GERSCH( 2*OLDIEN+1 ), $ Z( IBEGIN, KTOT ), ZTZ, MINGMA, $ IWORK( IINDR+KTOT ), $ ISUPPZ( 2*KTOT-1 ), $ WORK( INDWRK ) ) TMP1 = ONE / ZTZ NRMINV = SQRT( TMP1 ) RESID = ABS( MINGMA )*NRMINV RQCORR = MINGMA*TMP1 IF( K.EQ.IN ) THEN GAP = WORK( INDGAP+K-1 ) ELSE IF( K.EQ.1 ) THEN GAP = WORK( INDGAP+K ) ELSE GAP = MIN( WORK( INDGAP+K-1 ), $ WORK( INDGAP+K ) ) END IF ITER = ITER + 1 IF( RESID.GT.TOL*GAP .AND. ABS( RQCORR ).GT. $ FOUR*EPS*ABS( LAMBDA ) ) THEN WORK( K ) = LAMBDA + RQCORR IF( ITER.LT.MAXITR ) THEN GO TO 90 END IF END IF IWORK( KTOT ) = 1 IF( NEWSIZ.EQ.1 ) $ NDONE = NDONE + 1 CALL DSCAL( IN, NRMINV, Z( IBEGIN, KTOT ), 1 ) KTOT = KTOT + 1 100 CONTINUE IF( NEWSIZ.GT.1 ) THEN ITMP1 = ISUPPZ( 2*NEWFTT-1 ) ITMP2 = ISUPPZ( 2*NEWFTT ) KTOT = OLDIEN + NEWLST DO 120 P = NEWFTT + 1, KTOT DO 110 Q = NEWFTT, P - 1 TMP1 = -DDOT( IN, Z( IBEGIN, P ), 1, $ Z( IBEGIN, Q ), 1 ) CALL DAXPY( IN, TMP1, Z( IBEGIN, Q ), 1, $ Z( IBEGIN, P ), 1 ) 110 CONTINUE TMP1 = ONE / DNRM2( IN, Z( IBEGIN, P ), 1 ) CALL DSCAL( IN, TMP1, Z( IBEGIN, P ), 1 ) ITMP1 = MIN( ITMP1, ISUPPZ( 2*P-1 ) ) ITMP2 = MAX( ITMP2, ISUPPZ( 2*P ) ) 120 CONTINUE DO 130 P = NEWFTT, KTOT ISUPPZ( 2*P-1 ) = ITMP1 ISUPPZ( 2*P ) = ITMP2 130 CONTINUE NDONE = NDONE + NEWSIZ END IF END IF NEWFRS = J + 1 140 CONTINUE 150 CONTINUE NDEPTH = NDEPTH + 1 GO TO 40 END IF J = 2*IBEGIN DO 160 I = IBEGIN, IEND ISUPPZ( J-1 ) = ISUPPZ( J-1 ) + OLDIEN ISUPPZ( J ) = ISUPPZ( J ) + OLDIEN J = J + 2 160 CONTINUE IBEGIN = IEND + 1 170 CONTINUE * RETURN * * End of DLARRV * END SUBROUTINE DLAEBZ( IJOB, NITMAX, N, MMAX, MINP, NBMIN, ABSTOL, $ RELTOL, PIVMIN, D, E, E2, NVAL, AB, C, MOUT, $ NAB, WORK, IWORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IJOB, INFO, MINP, MMAX, MOUT, N, NBMIN, NITMAX DOUBLE PRECISION ABSTOL, PIVMIN, RELTOL * .. * .. Array Arguments .. INTEGER IWORK( * ), NAB( MMAX, * ), NVAL( * ) DOUBLE PRECISION AB( MMAX, * ), C( * ), D( * ), E( * ), E2( * ), $ WORK( * ) * .. * * Purpose * ======= * * DLAEBZ contains the iteration loops which compute and use the * function N(w), which is the count of eigenvalues of a symmetric * tridiagonal matrix T less than or equal to its argument w. It * performs a choice of two types of loops: * * IJOB=1, followed by * IJOB=2: It takes as input a list of intervals and returns a list of * sufficiently small intervals whose union contains the same * eigenvalues as the union of the original intervals. * The input intervals are (AB(j,1),AB(j,2)], j=1,...,MINP. * The output interval (AB(j,1),AB(j,2)] will contain * eigenvalues NAB(j,1)+1,...,NAB(j,2), where 1 <= j <= MOUT. * * IJOB=3: It performs a binary search in each input interval * (AB(j,1),AB(j,2)] for a point w(j) such that * N(w(j))=NVAL(j), and uses C(j) as the starting point of * the search. If such a w(j) is found, then on output * AB(j,1)=AB(j,2)=w. If no such w(j) is found, then on output * (AB(j,1),AB(j,2)] will be a small interval containing the * point where N(w) jumps through NVAL(j), unless that point * lies outside the initial interval. * * Note that the intervals are in all cases half-open intervals, * i.e., of the form (a,b] , which includes b but not a . * * To avoid underflow, the matrix should be scaled so that its largest * element is no greater than overflow**(1/2) * underflow**(1/4) * in absolute value. To assure the most accurate computation * of small eigenvalues, the matrix should be scaled to be * not much smaller than that, either. * * See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal * Matrix", Report CS41, Computer Science Dept., Stanford * University, July 21, 1966 * * Note: the arguments are, in general, *not* checked for unreasonable * values. * * Arguments * ========= * * IJOB (input) INTEGER * Specifies what is to be done: * = 1: Compute NAB for the initial intervals. * = 2: Perform bisection iteration to find eigenvalues of T. * = 3: Perform bisection iteration to invert N(w), i.e., * to find a point which has a specified number of * eigenvalues of T to its left. * Other values will cause DLAEBZ to return with INFO=-1. * * NITMAX (input) INTEGER * The maximum number of "levels" of bisection to be * performed, i.e., an interval of width W will not be made * smaller than 2^(-NITMAX) * W. If not all intervals * have converged after NITMAX iterations, then INFO is set * to the number of non-converged intervals. * * N (input) INTEGER * The dimension n of the tridiagonal matrix T. It must be at * least 1. * * MMAX (input) INTEGER * The maximum number of intervals. If more than MMAX intervals * are generated, then DLAEBZ will quit with INFO=MMAX+1. * * MINP (input) INTEGER * The initial number of intervals. It may not be greater than * MMAX. * * NBMIN (input) INTEGER * The smallest number of intervals that should be processed * using a vector loop. If zero, then only the scalar loop * will be used. * * ABSTOL (input) DOUBLE PRECISION * The minimum (absolute) width of an interval. When an * interval is narrower than ABSTOL, or than RELTOL times the * larger (in magnitude) endpoint, then it is considered to be * sufficiently small, i.e., converged. This must be at least * zero. * * RELTOL (input) DOUBLE PRECISION * The minimum relative width of an interval. When an interval * is narrower than ABSTOL, or than RELTOL times the larger (in * magnitude) endpoint, then it is considered to be * sufficiently small, i.e., converged. Note: this should * always be at least radix*machine epsilon. * * PIVMIN (input) DOUBLE PRECISION * The minimum absolute value of a "pivot" in the Sturm * sequence loop. This *must* be at least max |e(j)**2| * * safe_min and at least safe_min, where safe_min is at least * the smallest number that can divide one without overflow. * * D (input) DOUBLE PRECISION array, dimension (N) * The diagonal elements of the tridiagonal matrix T. * * E (input) DOUBLE PRECISION array, dimension (N) * The offdiagonal elements of the tridiagonal matrix T in * positions 1 through N-1. E(N) is arbitrary. * * E2 (input) DOUBLE PRECISION array, dimension (N) * The squares of the offdiagonal elements of the tridiagonal * matrix T. E2(N) is ignored. * * NVAL (input/output) INTEGER array, dimension (MINP) * If IJOB=1 or 2, not referenced. * If IJOB=3, the desired values of N(w). The elements of NVAL * will be reordered to correspond with the intervals in AB. * Thus, NVAL(j) on output will not, in general be the same as * NVAL(j) on input, but it will correspond with the interval * (AB(j,1),AB(j,2)] on output. * * AB (input/output) DOUBLE PRECISION array, dimension (MMAX,2) * The endpoints of the intervals. AB(j,1) is a(j), the left * endpoint of the j-th interval, and AB(j,2) is b(j), the * right endpoint of the j-th interval. The input intervals * will, in general, be modified, split, and reordered by the * calculation. * * C (input/output) DOUBLE PRECISION array, dimension (MMAX) * If IJOB=1, ignored. * If IJOB=2, workspace. * If IJOB=3, then on input C(j) should be initialized to the * first search point in the binary search. * * MOUT (output) INTEGER * If IJOB=1, the number of eigenvalues in the intervals. * If IJOB=2 or 3, the number of intervals output. * If IJOB=3, MOUT will equal MINP. * * NAB (input/output) INTEGER array, dimension (MMAX,2) * If IJOB=1, then on output NAB(i,j) will be set to N(AB(i,j)). * If IJOB=2, then on input, NAB(i,j) should be set. It must * satisfy the condition: * N(AB(i,1)) <= NAB(i,1) <= NAB(i,2) <= N(AB(i,2)), * which means that in interval i only eigenvalues * NAB(i,1)+1,...,NAB(i,2) will be considered. Usually, * NAB(i,j)=N(AB(i,j)), from a previous call to DLAEBZ with * IJOB=1. * On output, NAB(i,j) will contain * max(na(k),min(nb(k),N(AB(i,j)))), where k is the index of * the input interval that the output interval * (AB(j,1),AB(j,2)] came from, and na(k) and nb(k) are the * the input values of NAB(k,1) and NAB(k,2). * If IJOB=3, then on output, NAB(i,j) contains N(AB(i,j)), * unless N(w) > NVAL(i) for all search points w , in which * case NAB(i,1) will not be modified, i.e., the output * value will be the same as the input value (modulo * reorderings -- see NVAL and AB), or unless N(w) < NVAL(i) * for all search points w , in which case NAB(i,2) will * not be modified. Normally, NAB should be set to some * distinctive value(s) before DLAEBZ is called. * * WORK (workspace) DOUBLE PRECISION array, dimension (MMAX) * Workspace. * * IWORK (workspace) INTEGER array, dimension (MMAX) * Workspace. * * INFO (output) INTEGER * = 0: All intervals converged. * = 1--MMAX: The last INFO intervals did not converge. * = MMAX+1: More than MMAX intervals were generated. * * Further Details * =============== * * This routine is intended to be called only by other LAPACK * routines, thus the interface is less user-friendly. It is intended * for two purposes: * * (a) finding eigenvalues. In this case, DLAEBZ should have one or * more initial intervals set up in AB, and DLAEBZ should be called * with IJOB=1. This sets up NAB, and also counts the eigenvalues. * Intervals with no eigenvalues would usually be thrown out at * this point. Also, if not all the eigenvalues in an interval i * are desired, NAB(i,1) can be increased or NAB(i,2) decreased. * For example, set NAB(i,1)=NAB(i,2)-1 to get the largest * eigenvalue. DLAEBZ is then called with IJOB=2 and MMAX * no smaller than the value of MOUT returned by the call with * IJOB=1. After this (IJOB=2) call, eigenvalues NAB(i,1)+1 * through NAB(i,2) are approximately AB(i,1) (or AB(i,2)) to the * tolerance specified by ABSTOL and RELTOL. * * (b) finding an interval (a',b'] containing eigenvalues w(f),...,w(l). * In this case, start with a Gershgorin interval (a,b). Set up * AB to contain 2 search intervals, both initially (a,b). One * NVAL element should contain f-1 and the other should contain l * , while C should contain a and b, resp. NAB(i,1) should be -1 * and NAB(i,2) should be N+1, to flag an error if the desired * interval does not lie in (a,b). DLAEBZ is then called with * IJOB=3. On exit, if w(f-1) < w(f), then one of the intervals -- * j -- will have AB(j,1)=AB(j,2) and NAB(j,1)=NAB(j,2)=f-1, while * if, to the specified tolerance, w(f-k)=...=w(f+r), k > 0 and r * >= 0, then the interval will have N(AB(j,1))=NAB(j,1)=f-k and * N(AB(j,2))=NAB(j,2)=f+r. The cases w(l) < w(l+1) and * w(l-r)=...=w(l+k) are handled similarly. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, TWO, HALF PARAMETER ( ZERO = 0.0D0, TWO = 2.0D0, $ HALF = 1.0D0 / TWO ) * .. * .. Local Scalars .. INTEGER ITMP1, ITMP2, J, JI, JIT, JP, KF, KFNEW, KL, $ KLNEW DOUBLE PRECISION TMP1, TMP2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * * Check for Errors * INFO = 0 IF( IJOB.LT.1 .OR. IJOB.GT.3 ) THEN INFO = -1 RETURN END IF * * Initialize NAB * IF( IJOB.EQ.1 ) THEN * * Compute the number of eigenvalues in the initial intervals. * MOUT = 0 *DIR$ NOVECTOR DO 30 JI = 1, MINP DO 20 JP = 1, 2 TMP1 = D( 1 ) - AB( JI, JP ) IF( ABS( TMP1 ).LT.PIVMIN ) $ TMP1 = -PIVMIN NAB( JI, JP ) = 0 IF( TMP1.LE.ZERO ) $ NAB( JI, JP ) = 1 * DO 10 J = 2, N TMP1 = D( J ) - E2( J-1 ) / TMP1 - AB( JI, JP ) IF( ABS( TMP1 ).LT.PIVMIN ) $ TMP1 = -PIVMIN IF( TMP1.LE.ZERO ) $ NAB( JI, JP ) = NAB( JI, JP ) + 1 10 CONTINUE 20 CONTINUE MOUT = MOUT + NAB( JI, 2 ) - NAB( JI, 1 ) 30 CONTINUE RETURN END IF * * Initialize for loop * * KF and KL have the following meaning: * Intervals 1,...,KF-1 have converged. * Intervals KF,...,KL still need to be refined. * KF = 1 KL = MINP * * If IJOB=2, initialize C. * If IJOB=3, use the user-supplied starting point. * IF( IJOB.EQ.2 ) THEN DO 40 JI = 1, MINP C( JI ) = HALF*( AB( JI, 1 )+AB( JI, 2 ) ) 40 CONTINUE END IF * * Iteration loop * DO 130 JIT = 1, NITMAX * * Loop over intervals * IF( KL-KF+1.GE.NBMIN .AND. NBMIN.GT.0 ) THEN * * Begin of Parallel Version of the loop * DO 60 JI = KF, KL * * Compute N(c), the number of eigenvalues less than c * WORK( JI ) = D( 1 ) - C( JI ) IWORK( JI ) = 0 IF( WORK( JI ).LE.PIVMIN ) THEN IWORK( JI ) = 1 WORK( JI ) = MIN( WORK( JI ), -PIVMIN ) END IF * DO 50 J = 2, N WORK( JI ) = D( J ) - E2( J-1 ) / WORK( JI ) - C( JI ) IF( WORK( JI ).LE.PIVMIN ) THEN IWORK( JI ) = IWORK( JI ) + 1 WORK( JI ) = MIN( WORK( JI ), -PIVMIN ) END IF 50 CONTINUE 60 CONTINUE * IF( IJOB.LE.2 ) THEN * * IJOB=2: Choose all intervals containing eigenvalues. * KLNEW = KL DO 70 JI = KF, KL * * Insure that N(w) is monotone * IWORK( JI ) = MIN( NAB( JI, 2 ), $ MAX( NAB( JI, 1 ), IWORK( JI ) ) ) * * Update the Queue -- add intervals if both halves * contain eigenvalues. * IF( IWORK( JI ).EQ.NAB( JI, 2 ) ) THEN * * No eigenvalue in the upper interval: * just use the lower interval. * AB( JI, 2 ) = C( JI ) * ELSE IF( IWORK( JI ).EQ.NAB( JI, 1 ) ) THEN * * No eigenvalue in the lower interval: * just use the upper interval. * AB( JI, 1 ) = C( JI ) ELSE KLNEW = KLNEW + 1 IF( KLNEW.LE.MMAX ) THEN * * Eigenvalue in both intervals -- add upper to * queue. * AB( KLNEW, 2 ) = AB( JI, 2 ) NAB( KLNEW, 2 ) = NAB( JI, 2 ) AB( KLNEW, 1 ) = C( JI ) NAB( KLNEW, 1 ) = IWORK( JI ) AB( JI, 2 ) = C( JI ) NAB( JI, 2 ) = IWORK( JI ) ELSE INFO = MMAX + 1 END IF END IF 70 CONTINUE IF( INFO.NE.0 ) $ RETURN KL = KLNEW ELSE * * IJOB=3: Binary search. Keep only the interval containing * w s.t. N(w) = NVAL * DO 80 JI = KF, KL IF( IWORK( JI ).LE.NVAL( JI ) ) THEN AB( JI, 1 ) = C( JI ) NAB( JI, 1 ) = IWORK( JI ) END IF IF( IWORK( JI ).GE.NVAL( JI ) ) THEN AB( JI, 2 ) = C( JI ) NAB( JI, 2 ) = IWORK( JI ) END IF 80 CONTINUE END IF * ELSE * * End of Parallel Version of the loop * * Begin of Serial Version of the loop * KLNEW = KL DO 100 JI = KF, KL * * Compute N(w), the number of eigenvalues less than w * TMP1 = C( JI ) TMP2 = D( 1 ) - TMP1 ITMP1 = 0 IF( TMP2.LE.PIVMIN ) THEN ITMP1 = 1 TMP2 = MIN( TMP2, -PIVMIN ) END IF * * A series of compiler directives to defeat vectorization * for the next loop * *$PL$ CMCHAR=' ' CDIR$ NEXTSCALAR C$DIR SCALAR CDIR$ NEXT SCALAR CVD$L NOVECTOR CDEC$ NOVECTOR CVD$ NOVECTOR *VDIR NOVECTOR *VOCL LOOP,SCALAR CIBM PREFER SCALAR *$PL$ CMCHAR='*' * DO 90 J = 2, N TMP2 = D( J ) - E2( J-1 ) / TMP2 - TMP1 IF( TMP2.LE.PIVMIN ) THEN ITMP1 = ITMP1 + 1 TMP2 = MIN( TMP2, -PIVMIN ) END IF 90 CONTINUE * IF( IJOB.LE.2 ) THEN * * IJOB=2: Choose all intervals containing eigenvalues. * * Insure that N(w) is monotone * ITMP1 = MIN( NAB( JI, 2 ), $ MAX( NAB( JI, 1 ), ITMP1 ) ) * * Update the Queue -- add intervals if both halves * contain eigenvalues. * IF( ITMP1.EQ.NAB( JI, 2 ) ) THEN * * No eigenvalue in the upper interval: * just use the lower interval. * AB( JI, 2 ) = TMP1 * ELSE IF( ITMP1.EQ.NAB( JI, 1 ) ) THEN * * No eigenvalue in the lower interval: * just use the upper interval. * AB( JI, 1 ) = TMP1 ELSE IF( KLNEW.LT.MMAX ) THEN * * Eigenvalue in both intervals -- add upper to queue. * KLNEW = KLNEW + 1 AB( KLNEW, 2 ) = AB( JI, 2 ) NAB( KLNEW, 2 ) = NAB( JI, 2 ) AB( KLNEW, 1 ) = TMP1 NAB( KLNEW, 1 ) = ITMP1 AB( JI, 2 ) = TMP1 NAB( JI, 2 ) = ITMP1 ELSE INFO = MMAX + 1 RETURN END IF ELSE * * IJOB=3: Binary search. Keep only the interval * containing w s.t. N(w) = NVAL * IF( ITMP1.LE.NVAL( JI ) ) THEN AB( JI, 1 ) = TMP1 NAB( JI, 1 ) = ITMP1 END IF IF( ITMP1.GE.NVAL( JI ) ) THEN AB( JI, 2 ) = TMP1 NAB( JI, 2 ) = ITMP1 END IF END IF 100 CONTINUE KL = KLNEW * * End of Serial Version of the loop * END IF * * Check for convergence * KFNEW = KF DO 110 JI = KF, KL TMP1 = ABS( AB( JI, 2 )-AB( JI, 1 ) ) TMP2 = MAX( ABS( AB( JI, 2 ) ), ABS( AB( JI, 1 ) ) ) IF( TMP1.LT.MAX( ABSTOL, PIVMIN, RELTOL*TMP2 ) .OR. $ NAB( JI, 1 ).GE.NAB( JI, 2 ) ) THEN * * Converged -- Swap with position KFNEW, * then increment KFNEW * IF( JI.GT.KFNEW ) THEN TMP1 = AB( JI, 1 ) TMP2 = AB( JI, 2 ) ITMP1 = NAB( JI, 1 ) ITMP2 = NAB( JI, 2 ) AB( JI, 1 ) = AB( KFNEW, 1 ) AB( JI, 2 ) = AB( KFNEW, 2 ) NAB( JI, 1 ) = NAB( KFNEW, 1 ) NAB( JI, 2 ) = NAB( KFNEW, 2 ) AB( KFNEW, 1 ) = TMP1 AB( KFNEW, 2 ) = TMP2 NAB( KFNEW, 1 ) = ITMP1 NAB( KFNEW, 2 ) = ITMP2 IF( IJOB.EQ.3 ) THEN ITMP1 = NVAL( JI ) NVAL( JI ) = NVAL( KFNEW ) NVAL( KFNEW ) = ITMP1 END IF END IF KFNEW = KFNEW + 1 END IF 110 CONTINUE KF = KFNEW * * Choose Midpoints * DO 120 JI = KF, KL C( JI ) = HALF*( AB( JI, 1 )+AB( JI, 2 ) ) 120 CONTINUE * * If no more intervals to refine, quit. * IF( KF.GT.KL ) $ GO TO 140 130 CONTINUE * * Converged * 140 CONTINUE INFO = MAX( KL+1-KF, 0 ) MOUT = KL * RETURN * * End of DLAEBZ * END SUBROUTINE DLARNV( IDIST, ISEED, N, X ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER IDIST, N * .. * .. Array Arguments .. INTEGER ISEED( 4 ) DOUBLE PRECISION X( * ) * .. * * Purpose * ======= * * DLARNV returns a vector of n random real numbers from a uniform or * normal distribution. * * Arguments * ========= * * IDIST (input) INTEGER * Specifies the distribution of the random numbers: * = 1: uniform (0,1) * = 2: uniform (-1,1) * = 3: normal (0,1) * * ISEED (input/output) INTEGER array, dimension (4) * On entry, the seed of the random number generator; the array * elements must be between 0 and 4095, and ISEED(4) must be * odd. * On exit, the seed is updated. * * N (input) INTEGER * The number of random numbers to be generated. * * X (output) DOUBLE PRECISION array, dimension (N) * The generated random numbers. * * Further Details * =============== * * This routine calls the auxiliary routine DLARUV to generate random * real numbers from a uniform (0,1) distribution, in batches of up to * 128 using vectorisable code. The Box-Muller method is used to * transform numbers from a uniform to a normal distribution. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, TWO PARAMETER ( ONE = 1.0D+0, TWO = 2.0D+0 ) INTEGER LV PARAMETER ( LV = 128 ) DOUBLE PRECISION TWOPI PARAMETER ( TWOPI = 6.2831853071795864769252867663D+0 ) * .. * .. Local Scalars .. INTEGER I, IL, IL2, IV * .. * .. Local Arrays .. DOUBLE PRECISION U( LV ) * .. * .. Intrinsic Functions .. INTRINSIC COS, LOG, MIN, SQRT * .. * .. External Subroutines .. EXTERNAL DLARUV * .. * .. Executable Statements .. * DO 40 IV = 1, N, LV / 2 IL = MIN( LV / 2, N-IV+1 ) IF( IDIST.EQ.3 ) THEN IL2 = 2*IL ELSE IL2 = IL END IF * * Call DLARUV to generate IL2 numbers from a uniform (0,1) * distribution (IL2 <= LV) * CALL DLARUV( ISEED, IL2, U ) * IF( IDIST.EQ.1 ) THEN * * Copy generated numbers * DO 10 I = 1, IL X( IV+I-1 ) = U( I ) 10 CONTINUE ELSE IF( IDIST.EQ.2 ) THEN * * Convert generated numbers to uniform (-1,1) distribution * DO 20 I = 1, IL X( IV+I-1 ) = TWO*U( I ) - ONE 20 CONTINUE ELSE IF( IDIST.EQ.3 ) THEN * * Convert generated numbers to normal (0,1) distribution * DO 30 I = 1, IL X( IV+I-1 ) = SQRT( -TWO*LOG( U( 2*I-1 ) ) )* $ COS( TWOPI*U( 2*I ) ) 30 CONTINUE END IF 40 CONTINUE RETURN * * End of DLARNV * END SUBROUTINE DLAGTF( N, A, LAMBDA, B, C, TOL, D, IN, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER INFO, N DOUBLE PRECISION LAMBDA, TOL * .. * .. Array Arguments .. INTEGER IN( * ) DOUBLE PRECISION A( * ), B( * ), C( * ), D( * ) * .. * * Purpose * ======= * * DLAGTF factorizes the matrix (T - lambda*I), where T is an n by n * tridiagonal matrix and lambda is a scalar, as * * T - lambda*I = PLU, * * where P is a permutation matrix, L is a unit lower tridiagonal matrix * with at most one non-zero sub-diagonal elements per column and U is * an upper triangular matrix with at most two non-zero super-diagonal * elements per column. * * The factorization is obtained by Gaussian elimination with partial * pivoting and implicit row scaling. * * The parameter LAMBDA is included in the routine so that DLAGTF may * be used, in conjunction with DLAGTS, to obtain eigenvectors of T by * inverse iteration. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix T. * * A (input/output) DOUBLE PRECISION array, dimension (N) * On entry, A must contain the diagonal elements of T. * * On exit, A is overwritten by the n diagonal elements of the * upper triangular matrix U of the factorization of T. * * LAMBDA (input) DOUBLE PRECISION * On entry, the scalar lambda. * * B (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, B must contain the (n-1) super-diagonal elements of * T. * * On exit, B is overwritten by the (n-1) super-diagonal * elements of the matrix U of the factorization of T. * * C (input/output) DOUBLE PRECISION array, dimension (N-1) * On entry, C must contain the (n-1) sub-diagonal elements of * T. * * On exit, C is overwritten by the (n-1) sub-diagonal elements * of the matrix L of the factorization of T. * * TOL (input) DOUBLE PRECISION * On entry, a relative tolerance used to indicate whether or * not the matrix (T - lambda*I) is nearly singular. TOL should * normally be chose as approximately the largest relative error * in the elements of T. For example, if the elements of T are * correct to about 4 significant figures, then TOL should be * set to about 5*10**(-4). If TOL is supplied as less than eps, * where eps is the relative machine precision, then the value * eps is used in place of TOL. * * D (output) DOUBLE PRECISION array, dimension (N-2) * On exit, D is overwritten by the (n-2) second super-diagonal * elements of the matrix U of the factorization of T. * * IN (output) INTEGER array, dimension (N) * On exit, IN contains details of the permutation matrix P. If * an interchange occurred at the kth step of the elimination, * then IN(k) = 1, otherwise IN(k) = 0. The element IN(n) * returns the smallest positive integer j such that * * abs( u(j,j) ).le. norm( (T - lambda*I)(j) )*TOL, * * where norm( A(j) ) denotes the sum of the absolute values of * the jth row of the matrix A. If no such j exists then IN(n) * is returned as zero. If IN(n) is returned as positive, then a * diagonal element of U is small, indicating that * (T - lambda*I) is singular or nearly singular, * * INFO (output) INTEGER * = 0 : successful exit * .lt. 0: if INFO = -k, the kth argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO PARAMETER ( ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER K DOUBLE PRECISION EPS, MULT, PIV1, PIV2, SCALE1, SCALE2, TEMP, TL * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. Executable Statements .. * INFO = 0 IF( N.LT.0 ) THEN INFO = -1 CALL XERBLA( 'DLAGTF', -INFO ) RETURN END IF * IF( N.EQ.0 ) $ RETURN * A( 1 ) = A( 1 ) - LAMBDA IN( N ) = 0 IF( N.EQ.1 ) THEN IF( A( 1 ).EQ.ZERO ) $ IN( 1 ) = 1 RETURN END IF * EPS = DLAMCH( 'Epsilon' ) * TL = MAX( TOL, EPS ) SCALE1 = ABS( A( 1 ) ) + ABS( B( 1 ) ) DO 10 K = 1, N - 1 A( K+1 ) = A( K+1 ) - LAMBDA SCALE2 = ABS( C( K ) ) + ABS( A( K+1 ) ) IF( K.LT.( N-1 ) ) $ SCALE2 = SCALE2 + ABS( B( K+1 ) ) IF( A( K ).EQ.ZERO ) THEN PIV1 = ZERO ELSE PIV1 = ABS( A( K ) ) / SCALE1 END IF IF( C( K ).EQ.ZERO ) THEN IN( K ) = 0 PIV2 = ZERO SCALE1 = SCALE2 IF( K.LT.( N-1 ) ) $ D( K ) = ZERO ELSE PIV2 = ABS( C( K ) ) / SCALE2 IF( PIV2.LE.PIV1 ) THEN IN( K ) = 0 SCALE1 = SCALE2 C( K ) = C( K ) / A( K ) A( K+1 ) = A( K+1 ) - C( K )*B( K ) IF( K.LT.( N-1 ) ) $ D( K ) = ZERO ELSE IN( K ) = 1 MULT = A( K ) / C( K ) A( K ) = C( K ) TEMP = A( K+1 ) A( K+1 ) = B( K ) - MULT*TEMP IF( K.LT.( N-1 ) ) THEN D( K ) = B( K+1 ) B( K+1 ) = -MULT*D( K ) END IF B( K ) = TEMP C( K ) = MULT END IF END IF IF( ( MAX( PIV1, PIV2 ).LE.TL ) .AND. ( IN( N ).EQ.0 ) ) $ IN( N ) = K 10 CONTINUE IF( ( ABS( A( N ) ).LE.SCALE1*TL ) .AND. ( IN( N ).EQ.0 ) ) $ IN( N ) = N * RETURN * * End of DLAGTF * END SUBROUTINE DLAGTS( JOB, N, A, B, C, D, IN, Y, TOL, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. INTEGER INFO, JOB, N DOUBLE PRECISION TOL * .. * .. Array Arguments .. INTEGER IN( * ) DOUBLE PRECISION A( * ), B( * ), C( * ), D( * ), Y( * ) * .. * * Purpose * ======= * * DLAGTS may be used to solve one of the systems of equations * * (T - lambda*I)*x = y or (T - lambda*I)'*x = y, * * where T is an n by n tridiagonal matrix, for x, following the * factorization of (T - lambda*I) as * * (T - lambda*I) = P*L*U , * * by routine DLAGTF. The choice of equation to be solved is * controlled by the argument JOB, and in each case there is an option * to perturb zero or very small diagonal elements of U, this option * being intended for use in applications such as inverse iteration. * * Arguments * ========= * * JOB (input) INTEGER * Specifies the job to be performed by DLAGTS as follows: * = 1: The equations (T - lambda*I)x = y are to be solved, * but diagonal elements of U are not to be perturbed. * = -1: The equations (T - lambda*I)x = y are to be solved * and, if overflow would otherwise occur, the diagonal * elements of U are to be perturbed. See argument TOL * below. * = 2: The equations (T - lambda*I)'x = y are to be solved, * but diagonal elements of U are not to be perturbed. * = -2: The equations (T - lambda*I)'x = y are to be solved * and, if overflow would otherwise occur, the diagonal * elements of U are to be perturbed. See argument TOL * below. * * N (input) INTEGER * The order of the matrix T. * * A (input) DOUBLE PRECISION array, dimension (N) * On entry, A must contain the diagonal elements of U as * returned from DLAGTF. * * B (input) DOUBLE PRECISION array, dimension (N-1) * On entry, B must contain the first super-diagonal elements of * U as returned from DLAGTF. * * C (input) DOUBLE PRECISION array, dimension (N-1) * On entry, C must contain the sub-diagonal elements of L as * returned from DLAGTF. * * D (input) DOUBLE PRECISION array, dimension (N-2) * On entry, D must contain the second super-diagonal elements * of U as returned from DLAGTF. * * IN (input) INTEGER array, dimension (N) * On entry, IN must contain details of the matrix P as returned * from DLAGTF. * * Y (input/output) DOUBLE PRECISION array, dimension (N) * On entry, the right hand side vector y. * On exit, Y is overwritten by the solution vector x. * * TOL (input/output) DOUBLE PRECISION * On entry, with JOB .lt. 0, TOL should be the minimum * perturbation to be made to very small diagonal elements of U. * TOL should normally be chosen as about eps*norm(U), where eps * is the relative machine precision, but if TOL is supplied as * non-positive, then it is reset to eps*max( abs( u(i,j) ) ). * If JOB .gt. 0 then TOL is not referenced. * * On exit, TOL is changed as described above, only if TOL is * non-positive on entry. Otherwise TOL is unchanged. * * INFO (output) INTEGER * = 0 : successful exit * .lt. 0: if INFO = -i, the i-th argument had an illegal value * .gt. 0: overflow would occur when computing the INFO(th) * element of the solution vector x. This can only occur * when JOB is supplied as positive and either means * that a diagonal element of U is very small, or that * the elements of the right-hand side vector y are very * large. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE, ZERO PARAMETER ( ONE = 1.0D+0, ZERO = 0.0D+0 ) * .. * .. Local Scalars .. INTEGER K DOUBLE PRECISION ABSAK, AK, BIGNUM, EPS, PERT, SFMIN, TEMP * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, SIGN * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. Executable Statements .. * INFO = 0 IF( ( ABS( JOB ).GT.2 ) .OR. ( JOB.EQ.0 ) ) THEN INFO = -1 ELSE IF( N.LT.0 ) THEN INFO = -2 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DLAGTS', -INFO ) RETURN END IF * IF( N.EQ.0 ) $ RETURN * EPS = DLAMCH( 'Epsilon' ) SFMIN = DLAMCH( 'Safe minimum' ) BIGNUM = ONE / SFMIN * IF( JOB.LT.0 ) THEN IF( TOL.LE.ZERO ) THEN TOL = ABS( A( 1 ) ) IF( N.GT.1 ) $ TOL = MAX( TOL, ABS( A( 2 ) ), ABS( B( 1 ) ) ) DO 10 K = 3, N TOL = MAX( TOL, ABS( A( K ) ), ABS( B( K-1 ) ), $ ABS( D( K-2 ) ) ) 10 CONTINUE TOL = TOL*EPS IF( TOL.EQ.ZERO ) $ TOL = EPS END IF END IF * IF( ABS( JOB ).EQ.1 ) THEN DO 20 K = 2, N IF( IN( K-1 ).EQ.0 ) THEN Y( K ) = Y( K ) - C( K-1 )*Y( K-1 ) ELSE TEMP = Y( K-1 ) Y( K-1 ) = Y( K ) Y( K ) = TEMP - C( K-1 )*Y( K ) END IF 20 CONTINUE IF( JOB.EQ.1 ) THEN DO 30 K = N, 1, -1 IF( K.LE.N-2 ) THEN TEMP = Y( K ) - B( K )*Y( K+1 ) - D( K )*Y( K+2 ) ELSE IF( K.EQ.N-1 ) THEN TEMP = Y( K ) - B( K )*Y( K+1 ) ELSE TEMP = Y( K ) END IF AK = A( K ) ABSAK = ABS( AK ) IF( ABSAK.LT.ONE ) THEN IF( ABSAK.LT.SFMIN ) THEN IF( ABSAK.EQ.ZERO .OR. ABS( TEMP )*SFMIN.GT.ABSAK ) $ THEN INFO = K RETURN ELSE TEMP = TEMP*BIGNUM AK = AK*BIGNUM END IF ELSE IF( ABS( TEMP ).GT.ABSAK*BIGNUM ) THEN INFO = K RETURN END IF END IF Y( K ) = TEMP / AK 30 CONTINUE ELSE DO 50 K = N, 1, -1 IF( K.LE.N-2 ) THEN TEMP = Y( K ) - B( K )*Y( K+1 ) - D( K )*Y( K+2 ) ELSE IF( K.EQ.N-1 ) THEN TEMP = Y( K ) - B( K )*Y( K+1 ) ELSE TEMP = Y( K ) END IF AK = A( K ) PERT = SIGN( TOL, AK ) 40 CONTINUE ABSAK = ABS( AK ) IF( ABSAK.LT.ONE ) THEN IF( ABSAK.LT.SFMIN ) THEN IF( ABSAK.EQ.ZERO .OR. ABS( TEMP )*SFMIN.GT.ABSAK ) $ THEN AK = AK + PERT PERT = 2*PERT GO TO 40 ELSE TEMP = TEMP*BIGNUM AK = AK*BIGNUM END IF ELSE IF( ABS( TEMP ).GT.ABSAK*BIGNUM ) THEN AK = AK + PERT PERT = 2*PERT GO TO 40 END IF END IF Y( K ) = TEMP / AK 50 CONTINUE END IF ELSE * * Come to here if JOB = 2 or -2 * IF( JOB.EQ.2 ) THEN DO 60 K = 1, N IF( K.GE.3 ) THEN TEMP = Y( K ) - B( K-1 )*Y( K-1 ) - D( K-2 )*Y( K-2 ) ELSE IF( K.EQ.2 ) THEN TEMP = Y( K ) - B( K-1 )*Y( K-1 ) ELSE TEMP = Y( K ) END IF AK = A( K ) ABSAK = ABS( AK ) IF( ABSAK.LT.ONE ) THEN IF( ABSAK.LT.SFMIN ) THEN IF( ABSAK.EQ.ZERO .OR. ABS( TEMP )*SFMIN.GT.ABSAK ) $ THEN INFO = K RETURN ELSE TEMP = TEMP*BIGNUM AK = AK*BIGNUM END IF ELSE IF( ABS( TEMP ).GT.ABSAK*BIGNUM ) THEN INFO = K RETURN END IF END IF Y( K ) = TEMP / AK 60 CONTINUE ELSE DO 80 K = 1, N IF( K.GE.3 ) THEN TEMP = Y( K ) - B( K-1 )*Y( K-1 ) - D( K-2 )*Y( K-2 ) ELSE IF( K.EQ.2 ) THEN TEMP = Y( K ) - B( K-1 )*Y( K-1 ) ELSE TEMP = Y( K ) END IF AK = A( K ) PERT = SIGN( TOL, AK ) 70 CONTINUE ABSAK = ABS( AK ) IF( ABSAK.LT.ONE ) THEN IF( ABSAK.LT.SFMIN ) THEN IF( ABSAK.EQ.ZERO .OR. ABS( TEMP )*SFMIN.GT.ABSAK ) $ THEN AK = AK + PERT PERT = 2*PERT GO TO 70 ELSE TEMP = TEMP*BIGNUM AK = AK*BIGNUM END IF ELSE IF( ABS( TEMP ).GT.ABSAK*BIGNUM ) THEN AK = AK + PERT PERT = 2*PERT GO TO 70 END IF END IF Y( K ) = TEMP / AK 80 CONTINUE END IF * DO 90 K = N, 2, -1 IF( IN( K-1 ).EQ.0 ) THEN Y( K-1 ) = Y( K-1 ) - C( K-1 )*Y( K ) ELSE TEMP = Y( K-1 ) Y( K-1 ) = Y( K ) Y( K ) = TEMP - C( K-1 )*Y( K ) END IF 90 CONTINUE END IF * * End of DLAGTS * END SUBROUTINE DORM2L( SIDE, TRANS, M, N, K, A, LDA, TAU, C, LDC, $ WORK, INFO ) * * -- LAPACK routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. Scalar Arguments .. CHARACTER SIDE, TRANS INTEGER INFO, K, LDA, LDC, M, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), C( LDC, * ), TAU( * ), WORK( * ) * .. * * Purpose * ======= * * DORM2L overwrites the general real m by n matrix C with * * Q * C if SIDE = 'L' and TRANS = 'N', or * * Q'* C if SIDE = 'L' and TRANS = 'T', or * * C * Q if SIDE = 'R' and TRANS = 'N', or * * C * Q' if SIDE = 'R' and TRANS = 'T', * * where Q is a real orthogonal matrix defined as the product of k * elementary reflectors * * Q = H(k) . . . H(2) H(1) * * as returned by DGEQLF. Q is of order m if SIDE = 'L' and of order n * if SIDE = 'R'. * * Arguments * ========= * * SIDE (input) CHARACTER*1 * = 'L': apply Q or Q' from the Left * = 'R': apply Q or Q' from the Right * * TRANS (input) CHARACTER*1 * = 'N': apply Q (No transpose) * = 'T': apply Q' (Transpose) * * M (input) INTEGER * The number of rows of the matrix C. M >= 0. * * N (input) INTEGER * The number of columns of the matrix C. N >= 0. * * K (input) INTEGER * The number of elementary reflectors whose product defines * the matrix Q. * If SIDE = 'L', M >= K >= 0; * if SIDE = 'R', N >= K >= 0. * * A (input) DOUBLE PRECISION array, dimension (LDA,K) * The i-th column must contain the vector which defines the * elementary reflector H(i), for i = 1,2,...,k, as returned by * DGEQLF in the last k columns of its array argument A. * A is modified by the routine but restored on exit. * * LDA (input) INTEGER * The leading dimension of the array A. * If SIDE = 'L', LDA >= max(1,M); * if SIDE = 'R', LDA >= max(1,N). * * TAU (input) DOUBLE PRECISION array, dimension (K) * TAU(i) must contain the scalar factor of the elementary * reflector H(i), as returned by DGEQLF. * * C (input/output) DOUBLE PRECISION array, dimension (LDC,N) * On entry, the m by n matrix C. * On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q. * * LDC (input) INTEGER * The leading dimension of the array C. LDC >= max(1,M). * * WORK (workspace) DOUBLE PRECISION array, dimension * (N) if SIDE = 'L', * (M) if SIDE = 'R' * * INFO (output) INTEGER * = 0: successful exit * < 0: if INFO = -i, the i-th argument had an illegal value * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D+0 ) * .. * .. Local Scalars .. LOGICAL LEFT, NOTRAN INTEGER I, I1, I2, I3, MI, NI, NQ DOUBLE PRECISION AII * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. External Subroutines .. EXTERNAL DLARF, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC MAX * .. * .. Executable Statements .. * * Test the input arguments * INFO = 0 LEFT = LSAME( SIDE, 'L' ) NOTRAN = LSAME( TRANS, 'N' ) * * NQ is the order of Q * IF( LEFT ) THEN NQ = M ELSE NQ = N END IF IF( .NOT.LEFT .AND. .NOT.LSAME( SIDE, 'R' ) ) THEN INFO = -1 ELSE IF( .NOT.NOTRAN .AND. .NOT.LSAME( TRANS, 'T' ) ) THEN INFO = -2 ELSE IF( M.LT.0 ) THEN INFO = -3 ELSE IF( N.LT.0 ) THEN INFO = -4 ELSE IF( K.LT.0 .OR. K.GT.NQ ) THEN INFO = -5 ELSE IF( LDA.LT.MAX( 1, NQ ) ) THEN INFO = -7 ELSE IF( LDC.LT.MAX( 1, M ) ) THEN INFO = -10 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DORM2L', -INFO ) RETURN END IF * * Quick return if possible * IF( M.EQ.0 .OR. N.EQ.0 .OR. K.EQ.0 ) $ RETURN * IF( ( LEFT .AND. NOTRAN ) .OR. ( .NOT.LEFT .AND. .NOT.NOTRAN ) ) $ THEN I1 = 1 I2 = K I3 = 1 ELSE I1 = K I2 = 1 I3 = -1 END IF * IF( LEFT ) THEN NI = N ELSE MI = M END IF * DO 10 I = I1, I2, I3 IF( LEFT ) THEN * * H(i) is applied to C(1:m-k+i,1:n) * MI = M - K + I ELSE * * H(i) is applied to C(1:m,1:n-k+i) * NI = N - K + I END IF * * Apply H(i) * AII = A( NQ-K+I, I ) A( NQ-K+I, I ) = ONE CALL DLARF( SIDE, MI, NI, A( 1, I ), 1, TAU( I ), C, LDC, $ WORK ) A( NQ-K+I, I ) = AII 10 CONTINUE RETURN * * End of DORM2L * END SUBROUTINE DLARRB( N, D, L, LD, LLD, IFIRST, ILAST, SIGMA, RELTOL, $ W, WGAP, WERR, WORK, IWORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IFIRST, ILAST, INFO, N DOUBLE PRECISION RELTOL, SIGMA * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION D( * ), L( * ), LD( * ), LLD( * ), W( * ), $ WERR( * ), WGAP( * ), WORK( * ) * .. * * Purpose * ======= * * Given the relatively robust representation(RRR) L D L^T, DLARRB * does ``limited'' bisection to locate the eigenvalues of L D L^T, * W( IFIRST ) thru' W( ILAST ), to more accuracy. Intervals * [left, right] are maintained by storing their mid-points and * semi-widths in the arrays W and WERR respectively. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. * * D (input) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the diagonal matrix D. * * L (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 subdiagonal elements of the unit bidiagonal matrix L. * * LD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*D(i). * * LLD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*L(i)*D(i). * * IFIRST (input) INTEGER * The index of the first eigenvalue in the cluster. * * ILAST (input) INTEGER * The index of the last eigenvalue in the cluster. * * SIGMA (input) DOUBLE PRECISION * The shift used to form L D L^T (see DLARRF). * * RELTOL (input) DOUBLE PRECISION * The relative tolerance. * * W (input/output) DOUBLE PRECISION array, dimension (N) * On input, W( IFIRST ) thru' W( ILAST ) are estimates of the * corresponding eigenvalues of L D L^T. * On output, these estimates are ``refined''. * * WGAP (input/output) DOUBLE PRECISION array, dimension (N) * The gaps between the eigenvalues of L D L^T. Very small * gaps are changed on output. * * WERR (input/output) DOUBLE PRECISION array, dimension (N) * On input, WERR( IFIRST ) thru' WERR( ILAST ) are the errors * in the estimates W( IFIRST ) thru' W( ILAST ). * On output, these are the ``refined'' errors. * *****Reminder to Inder --- WORK is never used in this subroutine ***** * WORK (input) DOUBLE PRECISION array, dimension (???) * Workspace. * * IWORK (input) INTEGER array, dimension (2*N) * Workspace. * *****Reminder to Inder --- INFO is never set in this subroutine ****** * INFO (output) INTEGER * Error flag. * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, TWO, HALF PARAMETER ( ZERO = 0.0D0, TWO = 2.0D0, HALF = 0.5D0 ) * .. * .. Local Scalars .. INTEGER CNT, I, I1, I2, INITI1, INITI2, J, K, NCNVRG, $ NEIG, NINT, NRIGHT, OLNINT DOUBLE PRECISION DELTA, EPS, GAP, LEFT, MID, PERT, RIGHT, S, $ THRESH, TMP, WIDTH * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * EPS = DLAMCH( 'Precision' ) I1 = IFIRST I2 = IFIRST NEIG = ILAST - IFIRST + 1 NCNVRG = 0 THRESH = RELTOL DO 10 I = IFIRST, ILAST IWORK( I ) = 0 PERT = EPS*( ABS( SIGMA )+ABS( W( I ) ) ) WERR( I ) = WERR( I ) + PERT IF( WGAP( I ).LT.PERT ) $ WGAP( I ) = PERT 10 CONTINUE DO 20 I = I1, ILAST IF( I.EQ.1 ) THEN GAP = WGAP( I ) ELSE IF( I.EQ.N ) THEN GAP = WGAP( I-1 ) ELSE GAP = MIN( WGAP( I-1 ), WGAP( I ) ) END IF IF( WERR( I ).LT.THRESH*GAP ) THEN NCNVRG = NCNVRG + 1 IWORK( I ) = 1 IF( I1.EQ.I ) $ I1 = I1 + 1 ELSE I2 = I END IF 20 CONTINUE * * Initialize the unconverged intervals. * I = I1 NINT = 0 RIGHT = ZERO 30 CONTINUE IF( I.LE.I2 ) THEN IF( IWORK( I ).EQ.0 ) THEN DELTA = EPS LEFT = W( I ) - WERR( I ) * * Do while( CNT(LEFT).GT.I-1 ) * 40 CONTINUE IF( I.GT.I1 .AND. LEFT.LE.RIGHT ) THEN LEFT = RIGHT CNT = I - 1 ELSE S = -LEFT CNT = 0 DO 50 J = 1, N - 1 TMP = D( J ) + S S = S*( LD( J ) / TMP )*L( J ) - LEFT IF( TMP.LT.ZERO ) $ CNT = CNT + 1 50 CONTINUE TMP = D( N ) + S IF( TMP.LT.ZERO ) $ CNT = CNT + 1 IF( CNT.GT.I-1 ) THEN DELTA = TWO*DELTA LEFT = LEFT - ( ABS( SIGMA )+ABS( LEFT ) )*DELTA GO TO 40 END IF END IF DELTA = EPS RIGHT = W( I ) + WERR( I ) * * Do while( CNT(RIGHT).LT.I ) * 60 CONTINUE S = -RIGHT CNT = 0 DO 70 J = 1, N - 1 TMP = D( J ) + S S = S*( LD( J ) / TMP )*L( J ) - RIGHT IF( TMP.LT.ZERO ) $ CNT = CNT + 1 70 CONTINUE TMP = D( N ) + S IF( TMP.LT.ZERO ) $ CNT = CNT + 1 IF( CNT.LT.I ) THEN DELTA = TWO*DELTA RIGHT = RIGHT + ( ABS( SIGMA )+ABS( RIGHT ) )*DELTA GO TO 60 END IF WERR( I ) = LEFT W( I ) = RIGHT IWORK( N+I ) = CNT NINT = NINT + 1 I = CNT + 1 ELSE I = I + 1 END IF GO TO 30 END IF * * While( NCNVRG.LT.NEIG ) * INITI1 = I1 INITI2 = I2 80 CONTINUE IF( NCNVRG.LT.NEIG ) THEN OLNINT = NINT I = I1 DO 100 K = 1, OLNINT NRIGHT = IWORK( N+I ) IF( IWORK( I ).EQ.0 ) THEN MID = HALF*( WERR( I )+W( I ) ) S = -MID CNT = 0 DO 90 J = 1, N - 1 TMP = D( J ) + S S = S*( LD( J ) / TMP )*L( J ) - MID IF( TMP.LT.ZERO ) $ CNT = CNT + 1 90 CONTINUE TMP = D( N ) + S IF( TMP.LT.ZERO ) $ CNT = CNT + 1 CNT = MAX( I-1, MIN( NRIGHT, CNT ) ) IF( I.EQ.NRIGHT ) THEN IF( I.EQ.IFIRST ) THEN GAP = WERR( I+1 ) - W( I ) ELSE IF( I.EQ.ILAST ) THEN GAP = WERR( I ) - W( I-1 ) ELSE GAP = MIN( WERR( I+1 )-W( I ), WERR( I )-W( I-1 ) ) END IF WIDTH = W( I ) - MID IF( WIDTH.LT.THRESH*GAP ) THEN NCNVRG = NCNVRG + 1 IWORK( I ) = 1 IF( I1.EQ.I ) THEN I1 = I1 + 1 NINT = NINT - 1 END IF END IF END IF IF( IWORK( I ).EQ.0 ) $ I2 = K IF( CNT.EQ.I-1 ) THEN WERR( I ) = MID ELSE IF( CNT.EQ.NRIGHT ) THEN W( I ) = MID ELSE IWORK( N+I ) = CNT NINT = NINT + 1 WERR( CNT+1 ) = MID W( CNT+1 ) = W( I ) W( I ) = MID I = CNT + 1 IWORK( N+I ) = NRIGHT END IF END IF I = NRIGHT + 1 100 CONTINUE NINT = NINT - OLNINT + I2 GO TO 80 END IF DO 110 I = INITI1, INITI2 W( I ) = HALF*( WERR( I )+W( I ) ) WERR( I ) = W( I ) - WERR( I ) 110 CONTINUE * RETURN * * End of DLARRB * END SUBROUTINE DLARRF( N, D, L, LD, LLD, IFIRST, ILAST, W, DPLUS, $ LPLUS, WORK, IWORK, INFO ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER IFIRST, ILAST, INFO, N * .. * .. Array Arguments .. INTEGER IWORK( * ) DOUBLE PRECISION D( * ), DPLUS( * ), L( * ), LD( * ), LLD( * ), $ LPLUS( * ), W( * ), WORK( * ) * .. * * Purpose * ======= * * Given the initial representation L D L^T and its cluster of close * eigenvalues (in a relative measure), W( IFIRST ), W( IFIRST+1 ), ... * W( ILAST ), DLARRF finds a new relatively robust representation * L D L^T - SIGMA I = L(+) D(+) L(+)^T such that at least one of the * eigenvalues of L(+) D(+) L(+)^T is relatively isolated. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix. * * D (input) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the diagonal matrix D. * * L (input) DOUBLE PRECISION array, dimension (N-1) * The (n-1) subdiagonal elements of the unit bidiagonal * matrix L. * * LD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*D(i). * * LLD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*L(i)*D(i). * * IFIRST (input) INTEGER * The index of the first eigenvalue in the cluster. * * ILAST (input) INTEGER * The index of the last eigenvalue in the cluster. * * W (input/output) DOUBLE PRECISION array, dimension (N) * On input, the eigenvalues of L D L^T in ascending order. * W( IFIRST ) through W( ILAST ) form the cluster of relatively * close eigenalues. * On output, W( IFIRST ) thru' W( ILAST ) are estimates of the * corresponding eigenvalues of L(+) D(+) L(+)^T. * * SIGMA (input) DOUBLE PRECISION * The shift used to form L(+) D(+) L(+)^T. * * DPLUS (output) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the diagonal matrix D(+). * * LPLUS (output) DOUBLE PRECISION array, dimension (N) * The first (n-1) elements of LPLUS contain the subdiagonal * elements of the unit bidiagonal matrix L(+). LPLUS( N ) is * set to SIGMA. * * WORK (input) DOUBLE PRECISION array, dimension (???) * Workspace. * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, TWO PARAMETER ( ZERO = 0.0D0, TWO = 2.0D0 ) * .. * .. Local Scalars .. INTEGER I DOUBLE PRECISION DELTA, EPS, S, SIGMA * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS * .. * .. Executable Statements .. * INFO = 0 EPS = DLAMCH( 'Precision' ) IF( IFIRST.EQ.1 ) THEN SIGMA = W( IFIRST ) ELSE IF( ILAST.EQ.N ) THEN SIGMA = W( ILAST ) ELSE INFO = 1 RETURN END IF * * Compute the new relatively robust representation (RRR) * DELTA = TWO*EPS 10 CONTINUE IF( IFIRST.EQ.1 ) THEN SIGMA = SIGMA - ABS( SIGMA )*DELTA ELSE SIGMA = SIGMA + ABS( SIGMA )*DELTA END IF S = -SIGMA DO 20 I = 1, N - 1 DPLUS( I ) = D( I ) + S LPLUS( I ) = LD( I ) / DPLUS( I ) S = S*LPLUS( I )*L( I ) - SIGMA 20 CONTINUE DPLUS( N ) = D( N ) + S IF( IFIRST.EQ.1 ) THEN DO 30 I = 1, N IF( DPLUS( I ).LT.ZERO ) THEN DELTA = TWO*DELTA GO TO 10 END IF 30 CONTINUE ELSE DO 40 I = 1, N IF( DPLUS( I ).GT.ZERO ) THEN DELTA = TWO*DELTA GO TO 10 END IF 40 CONTINUE END IF DO 50 I = IFIRST, ILAST W( I ) = W( I ) - SIGMA 50 CONTINUE LPLUS( N ) = SIGMA * RETURN * * End of DLARRF * END SUBROUTINE DLAR1V( N, B1, BN, SIGMA, D, L, LD, LLD, GERSCH, Z, $ ZTZ, MINGMA, R, ISUPPZ, WORK ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * June 30, 1999 * * .. Scalar Arguments .. INTEGER B1, BN, N, R DOUBLE PRECISION MINGMA, SIGMA, ZTZ * .. * .. Array Arguments .. INTEGER ISUPPZ( * ) DOUBLE PRECISION D( * ), GERSCH( * ), L( * ), LD( * ), LLD( * ), $ WORK( * ), Z( * ) * .. * * Purpose * ======= * * DLAR1V computes the (scaled) r-th column of the inverse of * the sumbmatrix in rows B1 through BN of the tridiagonal matrix * L D L^T - sigma I. The following steps accomplish this computation : * (a) Stationary qd transform, L D L^T - sigma I = L(+) D(+) L(+)^T, * (b) Progressive qd transform, L D L^T - sigma I = U(-) D(-) U(-)^T, * (c) Computation of the diagonal elements of the inverse of * L D L^T - sigma I by combining the above transforms, and choosing * r as the index where the diagonal of the inverse is (one of the) * largest in magnitude. * (d) Computation of the (scaled) r-th column of the inverse using the * twisted factorization obtained by combining the top part of the * the stationary and the bottom part of the progressive transform. * * Arguments * ========= * * N (input) INTEGER * The order of the matrix L D L^T. * * B1 (input) INTEGER * First index of the submatrix of L D L^T. * * BN (input) INTEGER * Last index of the submatrix of L D L^T. * * SIGMA (input) DOUBLE PRECISION * The shift. Initially, when R = 0, SIGMA should be a good * approximation to an eigenvalue of L D L^T. * * L (input) DOUBLE PRECISION array, dimension (N-1) * The (n-1) subdiagonal elements of the unit bidiagonal matrix * L, in elements 1 to N-1. * * D (input) DOUBLE PRECISION array, dimension (N) * The n diagonal elements of the diagonal matrix D. * * LD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*D(i). * * LLD (input) DOUBLE PRECISION array, dimension (N-1) * The n-1 elements L(i)*L(i)*D(i). * * GERSCH (input) DOUBLE PRECISION array, dimension (2*N) * The n Gerschgorin intervals. These are used to restrict * the initial search for R, when R is input as 0. * * Z (output) DOUBLE PRECISION array, dimension (N) * The (scaled) r-th column of the inverse. Z(R) is returned * to be 1. * * ZTZ (output) DOUBLE PRECISION * The square of the norm of Z. * * MINGMA (output) DOUBLE PRECISION * The reciprocal of the largest (in magnitude) diagonal * element of the inverse of L D L^T - sigma I. * * R (input/output) INTEGER * Initially, R should be input to be 0 and is then output as * the index where the diagonal element of the inverse is * largest in magnitude. In later iterations, this same value * of R should be input. * * ISUPPZ (output) INTEGER array, dimension (2) * The support of the vector in Z, i.e., the vector Z is * nonzero only in elements ISUPPZ(1) through ISUPPZ( 2 ). * * WORK (workspace) DOUBLE PRECISION array, dimension (4*N) * * Further Details * =============== * * Based on contributions by * Inderjit Dhillon, IBM Almaden, USA * Osni Marques, LBNL/NERSC, USA * * ===================================================================== * * .. Parameters .. INTEGER BLKSIZ PARAMETER ( BLKSIZ = 32 ) DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 ) * .. * .. Local Scalars .. LOGICAL SAWNAN INTEGER FROM, I, INDP, INDS, INDUMN, J, R1, R2, TO DOUBLE PRECISION DMINUS, DPLUS, EPS, S, TMP * .. * .. External Functions .. DOUBLE PRECISION DLAMCH EXTERNAL DLAMCH * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. Executable Statements .. * EPS = DLAMCH( 'Precision' ) IF( R.EQ.0 ) THEN * * Eliminate the top and bottom indices from the possible values * of R where the desired eigenvector is largest in magnitude. * R1 = B1 DO 10 I = B1, BN IF( SIGMA.GE.GERSCH( 2*I-1 ) .OR. SIGMA.LE.GERSCH( 2*I ) ) $ THEN R1 = I GO TO 20 END IF 10 CONTINUE 20 CONTINUE R2 = BN DO 30 I = BN, B1, -1 IF( SIGMA.GE.GERSCH( 2*I-1 ) .OR. SIGMA.LE.GERSCH( 2*I ) ) $ THEN R2 = I GO TO 40 END IF 30 CONTINUE 40 CONTINUE ELSE R1 = R R2 = R END IF * INDUMN = N INDS = 2*N + 1 INDP = 3*N + 1 SAWNAN = .FALSE. * * Compute the stationary transform (using the differential form) * untill the index R2 * IF( B1.EQ.1 ) THEN WORK( INDS ) = ZERO ELSE WORK( INDS ) = LLD( B1-1 ) END IF S = WORK( INDS ) - SIGMA DO 50 I = B1, R2 - 1 DPLUS = D( I ) + S WORK( I ) = LD( I ) / DPLUS WORK( INDS+I ) = S*WORK( I )*L( I ) S = WORK( INDS+I ) - SIGMA 50 CONTINUE * IF( .NOT.( S.GT.ZERO .OR. S.LT.ONE ) ) THEN * * Run a slower version of the above loop if a NaN is detected * SAWNAN = .TRUE. J = B1 + 1 60 CONTINUE IF( WORK( INDS+J ).GT.ZERO .OR. WORK( INDS+J ).LT.ONE ) THEN J = J + 1 GO TO 60 END IF WORK( INDS+J ) = LLD( J ) S = WORK( INDS+J ) - SIGMA DO 70 I = J + 1, R2 - 1 DPLUS = D( I ) + S WORK( I ) = LD( I ) / DPLUS IF( WORK( I ).EQ.ZERO ) THEN WORK( INDS+I ) = LLD( I ) ELSE WORK( INDS+I ) = S*WORK( I )*L( I ) END IF S = WORK( INDS+I ) - SIGMA 70 CONTINUE END IF WORK( INDP+BN-1 ) = D( BN ) - SIGMA DO 80 I = BN - 1, R1, -1 DMINUS = LLD( I ) + WORK( INDP+I ) TMP = D( I ) / DMINUS WORK( INDUMN+I ) = L( I )*TMP WORK( INDP+I-1 ) = WORK( INDP+I )*TMP - SIGMA 80 CONTINUE TMP = WORK( INDP+R1-1 ) IF( .NOT.( TMP.GT.ZERO .OR. TMP.LT.ONE ) ) THEN * * Run a slower version of the above loop if a NaN is detected * SAWNAN = .TRUE. J = BN - 3 90 CONTINUE IF( WORK( INDP+J ).GT.ZERO .OR. WORK( INDP+J ).LT.ONE ) THEN J = J - 1 GO TO 90 END IF WORK( INDP+J ) = D( J+1 ) - SIGMA DO 100 I = J, R1, -1 DMINUS = LLD( I ) + WORK( INDP+I ) TMP = D( I ) / DMINUS WORK( INDUMN+I ) = L( I )*TMP IF( TMP.EQ.ZERO ) THEN WORK( INDP+I-1 ) = D( I ) - SIGMA ELSE WORK( INDP+I-1 ) = WORK( INDP+I )*TMP - SIGMA END IF 100 CONTINUE END IF * * Find the index (from R1 to R2) of the largest (in magnitude) * diagonal element of the inverse * MINGMA = WORK( INDS+R1-1 ) + WORK( INDP+R1-1 ) IF( MINGMA.EQ.ZERO ) $ MINGMA = EPS*WORK( INDS+R1-1 ) R = R1 DO 110 I = R1, R2 - 1 TMP = WORK( INDS+I ) + WORK( INDP+I ) IF( TMP.EQ.ZERO ) $ TMP = EPS*WORK( INDS+I ) IF( ABS( TMP ).LT.ABS( MINGMA ) ) THEN MINGMA = TMP R = I + 1 END IF 110 CONTINUE * * Compute the (scaled) r-th column of the inverse * ISUPPZ( 1 ) = B1 ISUPPZ( 2 ) = BN Z( R ) = ONE ZTZ = ONE IF( .NOT.SAWNAN ) THEN FROM = R - 1 TO = MAX( R-BLKSIZ, B1 ) 120 CONTINUE IF( FROM.GE.B1 ) THEN DO 130 I = FROM, TO, -1 Z( I ) = -( WORK( I )*Z( I+1 ) ) ZTZ = ZTZ + Z( I )*Z( I ) 130 CONTINUE IF( ABS( Z( TO ) ).LE.EPS .AND. ABS( Z( TO+1 ) ).LE.EPS ) $ THEN ISUPPZ( 1 ) = TO + 2 ELSE FROM = TO - 1 TO = MAX( TO-BLKSIZ, B1 ) GO TO 120 END IF END IF FROM = R + 1 TO = MIN( R+BLKSIZ, BN ) 140 CONTINUE IF( FROM.LE.BN ) THEN DO 150 I = FROM, TO Z( I ) = -( WORK( INDUMN+I-1 )*Z( I-1 ) ) ZTZ = ZTZ + Z( I )*Z( I ) 150 CONTINUE IF( ABS( Z( TO ) ).LE.EPS .AND. ABS( Z( TO-1 ) ).LE.EPS ) $ THEN ISUPPZ( 2 ) = TO - 2 ELSE FROM = TO + 1 TO = MIN( TO+BLKSIZ, BN ) GO TO 140 END IF END IF ELSE DO 160 I = R - 1, B1, -1 IF( Z( I+1 ).EQ.ZERO ) THEN Z( I ) = -( LD( I+1 ) / LD( I ) )*Z( I+2 ) ELSE IF( ABS( Z( I+1 ) ).LE.EPS .AND. ABS( Z( I+2 ) ).LE. $ EPS ) THEN ISUPPZ( 1 ) = I + 3 GO TO 170 ELSE Z( I ) = -( WORK( I )*Z( I+1 ) ) END IF ZTZ = ZTZ + Z( I )*Z( I ) 160 CONTINUE 170 CONTINUE DO 180 I = R, BN - 1 IF( Z( I ).EQ.ZERO ) THEN Z( I+1 ) = -( LD( I-1 ) / LD( I ) )*Z( I-1 ) ELSE IF( ABS( Z( I ) ).LE.EPS .AND. ABS( Z( I-1 ) ).LE.EPS ) $ THEN ISUPPZ( 2 ) = I - 2 GO TO 190 ELSE Z( I+1 ) = -( WORK( INDUMN+I )*Z( I ) ) END IF ZTZ = ZTZ + Z( I+1 )*Z( I+1 ) 180 CONTINUE 190 CONTINUE END IF DO 200 I = B1, ISUPPZ( 1 ) - 3 Z( I ) = ZERO 200 CONTINUE DO 210 I = ISUPPZ( 2 ) + 3, BN Z( I ) = ZERO 210 CONTINUE * RETURN * * End of DLAR1V * END SUBROUTINE DLARUV( ISEED, N, X ) * * -- LAPACK auxiliary routine (version 3.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. Scalar Arguments .. INTEGER N * .. * .. Array Arguments .. INTEGER ISEED( 4 ) DOUBLE PRECISION X( N ) * .. * * Purpose * ======= * * DLARUV returns a vector of n random real numbers from a uniform (0,1) * distribution (n <= 128). * * This is an auxiliary routine called by DLARNV and ZLARNV. * * Arguments * ========= * * ISEED (input/output) INTEGER array, dimension (4) * On entry, the seed of the random number generator; the array * elements must be between 0 and 4095, and ISEED(4) must be * odd. * On exit, the seed is updated. * * N (input) INTEGER * The number of random numbers to be generated. N <= 128. * * X (output) DOUBLE PRECISION array, dimension (N) * The generated random numbers. * * Further Details * =============== * * This routine uses a multiplicative congruential method with modulus * 2**48 and multiplier 33952834046453 (see G.S.Fishman, * 'Multiplicative congruential random number generators with modulus * 2**b: an exhaustive analysis for b = 32 and a partial analysis for * b = 48', Math. Comp. 189, pp 331-344, 1990). * * 48-bit integers are stored in 4 integer array elements with 12 bits * per element. Hence the routine is portable across machines with * integers of 32 bits or more. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ONE PARAMETER ( ONE = 1.0D0 ) INTEGER LV, IPW2 DOUBLE PRECISION R PARAMETER ( LV = 128, IPW2 = 4096, R = ONE / IPW2 ) * .. * .. Local Scalars .. INTEGER I, I1, I2, I3, I4, IT1, IT2, IT3, IT4, J * .. * .. Local Arrays .. INTEGER MM( LV, 4 ) * .. * .. Intrinsic Functions .. INTRINSIC DBLE, MIN, MOD * .. * .. Data statements .. DATA ( MM( 1, J ), J = 1, 4 ) / 494, 322, 2508, $ 2549 / DATA ( MM( 2, J ), J = 1, 4 ) / 2637, 789, 3754, $ 1145 / DATA ( MM( 3, J ), J = 1, 4 ) / 255, 1440, 1766, $ 2253 / DATA ( MM( 4, J ), J = 1, 4 ) / 2008, 752, 3572, $ 305 / DATA ( MM( 5, J ), J = 1, 4 ) / 1253, 2859, 2893, $ 3301 / DATA ( MM( 6, J ), J = 1, 4 ) / 3344, 123, 307, $ 1065 / DATA ( MM( 7, J ), J = 1, 4 ) / 4084, 1848, 1297, $ 3133 / DATA ( MM( 8, J ), J = 1, 4 ) / 1739, 643, 3966, $ 2913 / DATA ( MM( 9, J ), J = 1, 4 ) / 3143, 2405, 758, $ 3285 / DATA ( MM( 10, J ), J = 1, 4 ) / 3468, 2638, 2598, $ 1241 / DATA ( MM( 11, J ), J = 1, 4 ) / 688, 2344, 3406, $ 1197 / DATA ( MM( 12, J ), J = 1, 4 ) / 1657, 46, 2922, $ 3729 / DATA ( MM( 13, J ), J = 1, 4 ) / 1238, 3814, 1038, $ 2501 / DATA ( MM( 14, J ), J = 1, 4 ) / 3166, 913, 2934, $ 1673 / DATA ( MM( 15, J ), J = 1, 4 ) / 1292, 3649, 2091, $ 541 / DATA ( MM( 16, J ), J = 1, 4 ) / 3422, 339, 2451, $ 2753 / DATA ( MM( 17, J ), J = 1, 4 ) / 1270, 3808, 1580, $ 949 / DATA ( MM( 18, J ), J = 1, 4 ) / 2016, 822, 1958, $ 2361 / DATA ( MM( 19, J ), J = 1, 4 ) / 154, 2832, 2055, $ 1165 / DATA ( MM( 20, J ), J = 1, 4 ) / 2862, 3078, 1507, $ 4081 / DATA ( MM( 21, J ), J = 1, 4 ) / 697, 3633, 1078, $ 2725 / DATA ( MM( 22, J ), J = 1, 4 ) / 1706, 2970, 3273, $ 3305 / DATA ( MM( 23, J ), J = 1, 4 ) / 491, 637, 17, $ 3069 / DATA ( MM( 24, J ), J = 1, 4 ) / 931, 2249, 854, $ 3617 / DATA ( MM( 25, J ), J = 1, 4 ) / 1444, 2081, 2916, $ 3733 / DATA ( MM( 26, J ), J = 1, 4 ) / 444, 4019, 3971, $ 409 / DATA ( MM( 27, J ), J = 1, 4 ) / 3577, 1478, 2889, $ 2157 / DATA ( MM( 28, J ), J = 1, 4 ) / 3944, 242, 3831, $ 1361 / DATA ( MM( 29, J ), J = 1, 4 ) / 2184, 481, 2621, $ 3973 / DATA ( MM( 30, J ), J = 1, 4 ) / 1661, 2075, 1541, $ 1865 / DATA ( MM( 31, J ), J = 1, 4 ) / 3482, 4058, 893, $ 2525 / DATA ( MM( 32, J ), J = 1, 4 ) / 657, 622, 736, $ 1409 / DATA ( MM( 33, J ), J = 1, 4 ) / 3023, 3376, 3992, $ 3445 / DATA ( MM( 34, J ), J = 1, 4 ) / 3618, 812, 787, $ 3577 / DATA ( MM( 35, J ), J = 1, 4 ) / 1267, 234, 2125, $ 77 / DATA ( MM( 36, J ), J = 1, 4 ) / 1828, 641, 2364, $ 3761 / DATA ( MM( 37, J ), J = 1, 4 ) / 164, 4005, 2460, $ 2149 / DATA ( MM( 38, J ), J = 1, 4 ) / 3798, 1122, 257, $ 1449 / DATA ( MM( 39, J ), J = 1, 4 ) / 3087, 3135, 1574, $ 3005 / DATA ( MM( 40, J ), J = 1, 4 ) / 2400, 2640, 3912, $ 225 / DATA ( MM( 41, J ), J = 1, 4 ) / 2870, 2302, 1216, $ 85 / DATA ( MM( 42, J ), J = 1, 4 ) / 3876, 40, 3248, $ 3673 / DATA ( MM( 43, J ), J = 1, 4 ) / 1905, 1832, 3401, $ 3117 / DATA ( MM( 44, J ), J = 1, 4 ) / 1593, 2247, 2124, $ 3089 / DATA ( MM( 45, J ), J = 1, 4 ) / 1797, 2034, 2762, $ 1349 / DATA ( MM( 46, J ), J = 1, 4 ) / 1234, 2637, 149, $ 2057 / DATA ( MM( 47, J ), J = 1, 4 ) / 3460, 1287, 2245, $ 413 / DATA ( MM( 48, J ), J = 1, 4 ) / 328, 1691, 166, $ 65 / DATA ( MM( 49, J ), J = 1, 4 ) / 2861, 496, 466, $ 1845 / DATA ( MM( 50, J ), J = 1, 4 ) / 1950, 1597, 4018, $ 697 / DATA ( MM( 51, J ), J = 1, 4 ) / 617, 2394, 1399, $ 3085 / DATA ( MM( 52, J ), J = 1, 4 ) / 2070, 2584, 190, $ 3441 / DATA ( MM( 53, J ), J = 1, 4 ) / 3331, 1843, 2879, $ 1573 / DATA ( MM( 54, J ), J = 1, 4 ) / 769, 336, 153, $ 3689 / DATA ( MM( 55, J ), J = 1, 4 ) / 1558, 1472, 2320, $ 2941 / DATA ( MM( 56, J ), J = 1, 4 ) / 2412, 2407, 18, $ 929 / DATA ( MM( 57, J ), J = 1, 4 ) / 2800, 433, 712, $ 533 / DATA ( MM( 58, J ), J = 1, 4 ) / 189, 2096, 2159, $ 2841 / DATA ( MM( 59, J ), J = 1, 4 ) / 287, 1761, 2318, $ 4077 / DATA ( MM( 60, J ), J = 1, 4 ) / 2045, 2810, 2091, $ 721 / DATA ( MM( 61, J ), J = 1, 4 ) / 1227, 566, 3443, $ 2821 / DATA ( MM( 62, J ), J = 1, 4 ) / 2838, 442, 1510, $ 2249 / DATA ( MM( 63, J ), J = 1, 4 ) / 209, 41, 449, $ 2397 / DATA ( MM( 64, J ), J = 1, 4 ) / 2770, 1238, 1956, $ 2817 / DATA ( MM( 65, J ), J = 1, 4 ) / 3654, 1086, 2201, $ 245 / DATA ( MM( 66, J ), J = 1, 4 ) / 3993, 603, 3137, $ 1913 / DATA ( MM( 67, J ), J = 1, 4 ) / 192, 840, 3399, $ 1997 / DATA ( MM( 68, J ), J = 1, 4 ) / 2253, 3168, 1321, $ 3121 / DATA ( MM( 69, J ), J = 1, 4 ) / 3491, 1499, 2271, $ 997 / DATA ( MM( 70, J ), J = 1, 4 ) / 2889, 1084, 3667, $ 1833 / DATA ( MM( 71, J ), J = 1, 4 ) / 2857, 3438, 2703, $ 2877 / DATA ( MM( 72, J ), J = 1, 4 ) / 2094, 2408, 629, $ 1633 / DATA ( MM( 73, J ), J = 1, 4 ) / 1818, 1589, 2365, $ 981 / DATA ( MM( 74, J ), J = 1, 4 ) / 688, 2391, 2431, $ 2009 / DATA ( MM( 75, J ), J = 1, 4 ) / 1407, 288, 1113, $ 941 / DATA ( MM( 76, J ), J = 1, 4 ) / 634, 26, 3922, $ 2449 / DATA ( MM( 77, J ), J = 1, 4 ) / 3231, 512, 2554, $ 197 / DATA ( MM( 78, J ), J = 1, 4 ) / 815, 1456, 184, $ 2441 / DATA ( MM( 79, J ), J = 1, 4 ) / 3524, 171, 2099, $ 285 / DATA ( MM( 80, J ), J = 1, 4 ) / 1914, 1677, 3228, $ 1473 / DATA ( MM( 81, J ), J = 1, 4 ) / 516, 2657, 4012, $ 2741 / DATA ( MM( 82, J ), J = 1, 4 ) / 164, 2270, 1921, $ 3129 / DATA ( MM( 83, J ), J = 1, 4 ) / 303, 2587, 3452, $ 909 / DATA ( MM( 84, J ), J = 1, 4 ) / 2144, 2961, 3901, $ 2801 / DATA ( MM( 85, J ), J = 1, 4 ) / 3480, 1970, 572, $ 421 / DATA ( MM( 86, J ), J = 1, 4 ) / 119, 1817, 3309, $ 4073 / DATA ( MM( 87, J ), J = 1, 4 ) / 3357, 676, 3171, $ 2813 / DATA ( MM( 88, J ), J = 1, 4 ) / 837, 1410, 817, $ 2337 / DATA ( MM( 89, J ), J = 1, 4 ) / 2826, 3723, 3039, $ 1429 / DATA ( MM( 90, J ), J = 1, 4 ) / 2332, 2803, 1696, $ 1177 / DATA ( MM( 91, J ), J = 1, 4 ) / 2089, 3185, 1256, $ 1901 / DATA ( MM( 92, J ), J = 1, 4 ) / 3780, 184, 3715, $ 81 / DATA ( MM( 93, J ), J = 1, 4 ) / 1700, 663, 2077, $ 1669 / DATA ( MM( 94, J ), J = 1, 4 ) / 3712, 499, 3019, $ 2633 / DATA ( MM( 95, J ), J = 1, 4 ) / 150, 3784, 1497, $ 2269 / DATA ( MM( 96, J ), J = 1, 4 ) / 2000, 1631, 1101, $ 129 / DATA ( MM( 97, J ), J = 1, 4 ) / 3375, 1925, 717, $ 1141 / DATA ( MM( 98, J ), J = 1, 4 ) / 1621, 3912, 51, $ 249 / DATA ( MM( 99, J ), J = 1, 4 ) / 3090, 1398, 981, $ 3917 / DATA ( MM( 100, J ), J = 1, 4 ) / 3765, 1349, 1978, $ 2481 / DATA ( MM( 101, J ), J = 1, 4 ) / 1149, 1441, 1813, $ 3941 / DATA ( MM( 102, J ), J = 1, 4 ) / 3146, 2224, 3881, $ 2217 / DATA ( MM( 103, J ), J = 1, 4 ) / 33, 2411, 76, $ 2749 / DATA ( MM( 104, J ), J = 1, 4 ) / 3082, 1907, 3846, $ 3041 / DATA ( MM( 105, J ), J = 1, 4 ) / 2741, 3192, 3694, $ 1877 / DATA ( MM( 106, J ), J = 1, 4 ) / 359, 2786, 1682, $ 345 / DATA ( MM( 107, J ), J = 1, 4 ) / 3316, 382, 124, $ 2861 / DATA ( MM( 108, J ), J = 1, 4 ) / 1749, 37, 1660, $ 1809 / DATA ( MM( 109, J ), J = 1, 4 ) / 185, 759, 3997, $ 3141 / DATA ( MM( 110, J ), J = 1, 4 ) / 2784, 2948, 479, $ 2825 / DATA ( MM( 111, J ), J = 1, 4 ) / 2202, 1862, 1141, $ 157 / DATA ( MM( 112, J ), J = 1, 4 ) / 2199, 3802, 886, $ 2881 / DATA ( MM( 113, J ), J = 1, 4 ) / 1364, 2423, 3514, $ 3637 / DATA ( MM( 114, J ), J = 1, 4 ) / 1244, 2051, 1301, $ 1465 / DATA ( MM( 115, J ), J = 1, 4 ) / 2020, 2295, 3604, $ 2829 / DATA ( MM( 116, J ), J = 1, 4 ) / 3160, 1332, 1888, $ 2161 / DATA ( MM( 117, J ), J = 1, 4 ) / 2785, 1832, 1836, $ 3365 / DATA ( MM( 118, J ), J = 1, 4 ) / 2772, 2405, 1990, $ 361 / DATA ( MM( 119, J ), J = 1, 4 ) / 1217, 3638, 2058, $ 2685 / DATA ( MM( 120, J ), J = 1, 4 ) / 1822, 3661, 692, $ 3745 / DATA ( MM( 121, J ), J = 1, 4 ) / 1245, 327, 1194, $ 2325 / DATA ( MM( 122, J ), J = 1, 4 ) / 2252, 3660, 20, $ 3609 / DATA ( MM( 123, J ), J = 1, 4 ) / 3904, 716, 3285, $ 3821 / DATA ( MM( 124, J ), J = 1, 4 ) / 2774, 1842, 2046, $ 3537 / DATA ( MM( 125, J ), J = 1, 4 ) / 997, 3987, 2107, $ 517 / DATA ( MM( 126, J ), J = 1, 4 ) / 2573, 1368, 3508, $ 3017 / DATA ( MM( 127, J ), J = 1, 4 ) / 1148, 1848, 3525, $ 2141 / DATA ( MM( 128, J ), J = 1, 4 ) / 545, 2366, 3801, $ 1537 / * .. * .. Executable Statements .. * I1 = ISEED( 1 ) I2 = ISEED( 2 ) I3 = ISEED( 3 ) I4 = ISEED( 4 ) * DO 10 I = 1, MIN( N, LV ) * * Multiply the seed by i-th power of the multiplier modulo 2**48 * IT4 = I4*MM( I, 4 ) IT3 = IT4 / IPW2 IT4 = IT4 - IPW2*IT3 IT3 = IT3 + I3*MM( I, 4 ) + I4*MM( I, 3 ) IT2 = IT3 / IPW2 IT3 = IT3 - IPW2*IT2 IT2 = IT2 + I2*MM( I, 4 ) + I3*MM( I, 3 ) + I4*MM( I, 2 ) IT1 = IT2 / IPW2 IT2 = IT2 - IPW2*IT1 IT1 = IT1 + I1*MM( I, 4 ) + I2*MM( I, 3 ) + I3*MM( I, 2 ) + $ I4*MM( I, 1 ) IT1 = MOD( IT1, IPW2 ) * * Convert 48-bit integer to a real number in the interval (0,1) * X( I ) = R*( DBLE( IT1 )+R*( DBLE( IT2 )+R*( DBLE( IT3 )+R* $ DBLE( IT4 ) ) ) ) 10 CONTINUE * * Return final value of seed * ISEED( 1 ) = IT1 ISEED( 2 ) = IT2 ISEED( 3 ) = IT3 ISEED( 4 ) = IT4 RETURN * * End of DLARUV * END