c Che 515: Driver program for LAPACK routine DGEEV c for solving real eigenvalue problem A x = lambda x c September 16, 1998 c implicit double precision (a-h,o-z) parameter(ndim = 20, lwork = 6*ndim) dimension a(ndim,ndim) double precision lambdar(ndim), lambdai(ndim) double precision evecl(ndim,ndim), evecr(ndim,ndim) double precision work(lwork) c c Construct your matrix here. c do i=1,ndim do j=i,ndim a(i,j) = 0.d0 enddo a(i,i) = 1.d0 enddo c c Call DGEEV c call dgeev('N','N',ndim,a,ndim,lambdar,lambdai,evecl,ndim, & evecr,ndim,work,lwork,info) c do i=1,ndim write(40,*) lambdar(i), lambdai(i) enddo c stop end c SUBROUTINE DGEEV( JOBVL, JOBVR, N, A, LDA, WR, WI, VL, LDVL, VR, $ LDVR, WORK, LWORK, INFO ) * * -- LAPACK driver routine (version 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. 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. * * 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 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, DLABAD, 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 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 .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 ) THEN INFO = -13 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEEV ', -INFO ) 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 DGEBAK( JOB, SIDE, N, ILO, IHI, SCALE, M, V, LDV, $ INFO ) * * -- LAPACK routine (version 2.0) -- * 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 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER JOB 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. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) DOUBLE PRECISION SCLFAC PARAMETER ( SCLFAC = 1.0D+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 DGEHD2( N, ILO, IHI, A, LDA, TAU, WORK, INFO ) * * -- LAPACK routine (version 2.0) -- * 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 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. INTEGER IHI, ILO, INFO, LDA, LWORK, N * .. * .. Array Arguments .. DOUBLE PRECISION A( LDA, * ), TAU( * ), WORK( LWORK ) * .. * * 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. * * 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 .. INTEGER I, IB, IINFO, IWS, LDWORK, 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 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 ) ) THEN INFO = -8 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DGEHRD', -INFO ) 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 DHSEQR( JOB, COMPZ, N, ILO, IHI, H, LDH, WR, WI, Z, $ LDZ, WORK, LWORK, INFO ) * * -- LAPACK routine (version 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. CHARACTER COMPZ, 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) DOUBLE PRECISION array, dimension (N) * * LWORK (input) INTEGER * This argument is currently redundant. * * 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, 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, DLABAD, 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 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 END IF IF( INFO.NE.0 ) THEN CALL XERBLA( 'DHSEQR', -INFO ) 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 RETURN * * End of DHSEQR * END SUBROUTINE DLABAD( SMALL, LARGE ) * * -- LAPACK auxiliary routine (version 2.0) -- * 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 SLAMCH 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 DLACPY( UPLO, M, N, A, LDA, B, LDB ) * * -- LAPACK auxiliary routine (version 2.0) -- * 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 2.0) -- * 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 DLAHQR( WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, $ ILOZ, IHIZ, Z, LDZ, INFO ) * * -- LAPACK auxiliary routine (version 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * October 31, 1992 * * .. 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. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, ONE PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 ) 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 CS, 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, DLABAD, DLANV2, DLARFG, DROT * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN * .. * .. 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 H33 = H44 H43H34 = DAT2*S*S ELSE * * Prepare to use Wilkinson's double shift * H44 = H( I, I ) H33 = H( I-1, I-1 ) H43H34 = H( I, I-1 )*H( I-1, I ) 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 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * February 29, 1992 * * .. 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 (NB,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 2.0) -- * 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 DLANGE( NORM, M, N, A, LDA, WORK ) * * -- LAPACK auxiliary routine (version 2.0) -- * 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 2.0) -- * 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 SUBROUTINE DLANV2( A, B, C, D, RT1R, RT1I, RT2R, RT2I, CS, SN ) * * -- LAPACK auxiliary routine (version 2.0) -- * Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., * Courant Institute, Argonne National Lab, and Rice University * September 30, 1994 * * .. Scalar Arguments .. DOUBLE PRECISION 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 both real, abs(RT1R) >= abs(RT2R); if the * eigenvalues are a complex conjugate pair, RT1I > 0. * * CS (output) DOUBLE PRECISION * SN (output) DOUBLE PRECISION * Parameters of the rotation matrix. * * ===================================================================== * * .. Parameters .. DOUBLE PRECISION ZERO, HALF, ONE PARAMETER ( ZERO = 0.0D+0, HALF = 0.5D+0, ONE = 1.0D+0 ) * .. * .. Local Scalars .. DOUBLE PRECISION AA, BB, CC, CS1, DD, P, SAB, SAC, SIGMA, SN1, $ TAU, TEMP * .. * .. External Functions .. DOUBLE PRECISION DLAPY2 EXTERNAL DLAPY2 * .. * .. Intrinsic Functions .. INTRINSIC ABS, SIGN, SQRT * .. * .. Executable Statements .. * * Initialize CS and SN * CS = ONE SN = ZERO * IF( C.EQ.ZERO ) THEN 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 GO TO 10 ELSE * * Make diagonal elements equal * TEMP = A - D P = HALF*TEMP SIGMA = B + C TAU = DLAPY2( SIGMA, TEMP ) CS1 = SQRT( HALF*( ONE+ABS( SIGMA ) / TAU ) ) SN1 = -( P / ( TAU*CS1 ) )*SIGN( ONE, SIGMA ) * * Compute [ AA BB ] = [ A B ] [ CS1 -SN1 ] * [ CC DD ] [ C D ] [ SN1 CS1 ] * AA = A*CS1 + B*SN1 BB = -A*SN1 + B*CS1 CC = C*CS1 + D*SN1 DD = -C*SN1 + D*CS1 * * Compute [ A B ] = [ CS1 SN1 ] [ AA BB ] * [ C D ] [-SN1 CS1 ] [ CC DD ] * A = AA*CS1 + CC*SN1 B = BB*CS1 + DD*SN1 C = -AA*SN1 + CC*CS1 D = -BB*SN1 + DD*CS1 * * Accumulate transformation * TEMP = CS*CS1 - SN*SN1 SN = CS*SN1 + SN*CS1 CS = TEMP * 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 * 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 2.0) -- * 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 DLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK ) * * -- LAPACK auxiliary routine (version 2.0) -- * 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 2.0) -- * 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