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Cloned library LAPACK-3.11.0 with extra build files for internal package management.
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LAPACK-3.11.0/TESTING/EIG/schkdmd.f90

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! This is a test program for checking the implementations of
! the implementations of the following subroutines
!
! SGEDMD for computation of the
! Dynamic Mode Decomposition (DMD)
! SGEDMDQ for computation of a
! QR factorization based compressed DMD
!
! Developed and supported by:
! ===========================
! Developed and coded by Zlatko Drmac, Faculty of Science,
! University of Zagreb; drmac@math.hr
! In cooperation with
! AIMdyn Inc., Santa Barbara, CA.
! ========================================================
! How to run the code (compiler, link info)
! ========================================================
! Compile as FORTRAN 90 (or later) and link with BLAS and
! LAPACK libraries.
! NOTE: The code is developed and tested on top of the
! Intel MKL library (versions 2022.0.3 and 2022.2.0),
! using the Intel Fortran compiler.
!
! For developers of the C++ implementation
! ========================================================
! See the LAPACK++ and Template Numerical Toolkit (TNT)
!
! Note on a development of the GPU HP implementation
! ========================================================
! Work in progress. See CUDA, MAGMA, SLATE.
! NOTE: The four SVD subroutines used in this code are
! included as a part of R&D and for the completeness.
! This was also an opportunity to test those SVD codes.
! If the scaling option is used all four are essentially
! equally good. For implementations on HP platforms,
! one can use whichever SVD is available.
!... .........................................................
! NOTE:
! When using the Intel MKL 2022.0.3 the subroutine xGESVDQ
! (optionally used in xGEDMD) may cause access violation
! error for x = S, D, C, Z, but only if called with the
! work space query. (At least in our Windows 10 MSVS 2019.)
! The problem can be mitigated by downloading the source
! code of xGESVDQ from the LAPACK repository and use it
! localy instead of the one in the MKL. This seems to
! indicate that the problem is indeed in the MKL.
! This problem did not appear whith Intel MKL 2022.2.0.
!
! NOTE:
! xGESDD seems to have a problem with workspace. In some
! cases the length of the optimal workspace is returned
! smaller than the minimal workspace, as specified in the
! code. As a precaution, all optimal workspaces are
! set as MAX(minimal, optimal).
! Latest implementations of complex xGESDD have different
! length of the real worksapce. We use max value over
! two versions.
!............................................................
!............................................................
!
PROGRAM DMD_TEST
use iso_fortran_env, only: real32
IMPLICIT NONE
integer, parameter :: WP = real32
!............................................................
REAL(KIND=WP), PARAMETER :: ONE = 1.0_WP
REAL(KIND=WP), PARAMETER :: ZERO = 0.0_WP
!............................................................
REAL(KIND=WP), ALLOCATABLE, DIMENSION(:,:) :: &
A, AC, EIGA, LAMBDA, LAMBDAQ, F, F1, F2,&
Z, Z1, S, AU, W, VA, X, X0, Y, Y0, Y1
REAL(KIND=WP), ALLOCATABLE, DIMENSION(:) :: &
DA, DL, DR, REIG, REIGA, REIGQ, IEIG, &
IEIGA, IEIGQ, RES, RES1, RESEX, SINGVX,&
SINGVQX, WORK
INTEGER , ALLOCATABLE, DIMENSION(:) :: IWORK
REAL(KIND=WP) :: AB(2,2), WDUMMY(2)
INTEGER :: IDUMMY(2), ISEED(4), RJOBDATA(8)
REAL(KIND=WP) :: ANORM, COND, CONDL, CONDR, DMAX, EPS, &
TOL, TOL2, SVDIFF, TMP, TMP_AU, &
TMP_FQR, TMP_REZ, TMP_REZQ, TMP_ZXW, &
TMP_EX, XNORM, YNORM
!............................................................
INTEGER :: K, KQ, LDF, LDS, LDA, LDAU, LDW, LDX, LDY, &
LDZ, LIWORK, LWORK, M, N, L, LLOOP, NRNK
INTEGER :: i, iJOBREF, iJOBZ, iSCALE, INFO, KDIFF, &
NFAIL, NFAIL_AU, NFAIL_F_QR, NFAIL_REZ, &
NFAIL_REZQ, NFAIL_SVDIFF, NFAIL_TOTAL, NFAILQ_TOTAL, &
NFAIL_Z_XV, MODE, MODEL, MODER, WHTSVD
INTEGER iNRNK, iWHTSVD, K_TRAJ, LWMINOPT
CHARACTER(LEN=1) GRADE, JOBREF, JOBZ, PIVTNG, RSIGN, &
SCALE, RESIDS, WANTQ, WANTR
LOGICAL TEST_QRDMD
!..... external subroutines (BLAS and LAPACK)
EXTERNAL SAXPY, SGEEV, SGEMM, SGEMV, SLACPY, SLASCL
EXTERNAL SLARNV, SLATMR
!.....external subroutines DMD package, part 1
! subroutines under test
EXTERNAL SGEDMD, SGEDMDQ
!..... external functions (BLAS and LAPACK)
EXTERNAL SLAMCH, SLANGE, SNRM2
REAL(KIND=WP) :: SLAMCH, SLANGE, SNRM2
EXTERNAL LSAME
LOGICAL LSAME
INTRINSIC ABS, INT, MIN, MAX
!............................................................
! The test is always in pairs : ( SGEDMD and SGEDMDQ )
! because the test includes comparing the results (in pairs).
!.....................................................................................
TEST_QRDMD = .TRUE. ! This code by default performs tests on SGEDMDQ
! Since the QR factorizations based algorithm is designed for
! single trajectory data, only single trajectory tests will
! be performed with xGEDMDQ.
WANTQ = 'Q'
WANTR = 'R'
!.................................................................................
EPS = SLAMCH( 'P' ) ! machine precision SP
! Global counters of failures of some particular tests
NFAIL = 0
NFAIL_REZ = 0
NFAIL_REZQ = 0
NFAIL_Z_XV = 0
NFAIL_F_QR = 0
NFAIL_AU = 0
KDIFF = 0
NFAIL_SVDIFF = 0
NFAIL_TOTAL = 0
NFAILQ_TOTAL = 0
DO LLOOP = 1, 4
WRITE(*,*) 'L Loop Index = ', LLOOP
! Set the dimensions of the problem ...
WRITE(*,*) 'M = '
READ(*,*) M
WRITE(*,*) M
! ... and the number of snapshots.
WRITE(*,*) 'N = '
READ(*,*) N
WRITE(*,*) N
! ... Test the dimensions
IF ( ( MIN(M,N) == 0 ) .OR. ( M < N ) ) THEN
WRITE(*,*) 'Bad dimensions. Required: M >= N > 0.'
STOP
END IF
!.............
! The seed inside the LLOOP so that each pass can be reproduced easily.
ISEED(1) = 4
ISEED(2) = 3
ISEED(3) = 2
ISEED(4) = 1
LDA = M
LDF = M
LDX = MAX(M,N+1)
LDY = MAX(M,N+1)
LDW = N
LDZ = M
LDAU = MAX(M,N+1)
LDS = N
TMP_ZXW = ZERO
TMP_AU = ZERO
TMP_REZ = ZERO
TMP_REZQ = ZERO
SVDIFF = ZERO
TMP_EX = ZERO
!
! Test the subroutines on real data snapshots. All
! computation is done in real arithmetic, even when
! Koopman eigenvalues and modes are real.
!
! Allocate memory space
ALLOCATE( A(LDA,M) )
ALLOCATE( AC(LDA,M) )
ALLOCATE( DA(M) )
ALLOCATE( DL(M) )
ALLOCATE( F(LDF,N+1) )
ALLOCATE( F1(LDF,N+1) )
ALLOCATE( F2(LDF,N+1) )
ALLOCATE( X(LDX,N) )
ALLOCATE( X0(LDX,N) )
ALLOCATE( SINGVX(N) )
ALLOCATE( SINGVQX(N) )
ALLOCATE( Y(LDY,N+1) )
ALLOCATE( Y0(LDY,N+1) )
ALLOCATE( Y1(M,N+1) )
ALLOCATE( Z(LDZ,N) )
ALLOCATE( Z1(LDZ,N) )
ALLOCATE( RES(N) )
ALLOCATE( RES1(N) )
ALLOCATE( RESEX(N) )
ALLOCATE( REIG(N) )
ALLOCATE( IEIG(N) )
ALLOCATE( REIGQ(N) )
ALLOCATE( IEIGQ(N) )
ALLOCATE( REIGA(M) )
ALLOCATE( IEIGA(M) )
ALLOCATE( VA(LDA,M) )
ALLOCATE( LAMBDA(N,2) )
ALLOCATE( LAMBDAQ(N,2) )
ALLOCATE( EIGA(M,2) )
ALLOCATE( W(LDW,N) )
ALLOCATE( AU(LDAU,N) )
ALLOCATE( S(N,N) )
TOL = M*EPS
! This mimics O(M*N)*EPS bound for accumulated roundoff error.
! The factor 10 is somewhat arbitrary.
TOL2 = 10*M*N*EPS
!.............
DO K_TRAJ = 1, 2
! Number of intial conditions in the simulation/trajectories (1 or 2)
COND = 1.0D8
DMAX = 1.0D2
RSIGN = 'F'
GRADE = 'N'
MODEL = 6
CONDL = 1.0D2
MODER = 6
CONDR = 1.0D2
PIVTNG = 'N'
! Loop over all parameter MODE values for ZLATMR (+1,..,+6)
DO MODE = 1, 6
ALLOCATE( IWORK(2*M) )
ALLOCATE(DR(N))
CALL SLATMR( M, M, 'S', ISEED, 'N', DA, MODE, COND, &
DMAX, RSIGN, GRADE, DL, MODEL, CONDL, &
DR, MODER, CONDR, PIVTNG, IWORK, M, M, &
ZERO, -ONE, 'N', A, LDA, IWORK(M+1), INFO )
DEALLOCATE(IWORK)
DEALLOCATE(DR)
LWORK = 4*M+1
ALLOCATE(WORK(LWORK))
AC = A
CALL SGEEV( 'N','V', M, AC, M, REIGA, IEIGA, VA, M, &
VA, M, WORK, LWORK, INFO ) ! LAPACK CALL
DEALLOCATE(WORK)
TMP = ZERO
DO i = 1, M
EIGA(i,1) = REIGA(i)
EIGA(i,2) = IEIGA(i)
TMP = MAX( TMP, SQRT(REIGA(i)**2+IEIGA(i)**2))
END DO
! Scale A to have the desirable spectral radius.
CALL SLASCL( 'G', 0, 0, TMP, ONE, M, M, A, M, INFO )
CALL SLASCL( 'G', 0, 0, TMP, ONE, M, 2, EIGA, M, INFO )
! Compute the norm of A
ANORM = SLANGE( 'F', N, N, A, M, WDUMMY )
IF ( K_TRAJ == 2 ) THEN
! generate data with two inital conditions
CALL SLARNV(2, ISEED, M, F1(1,1) )
F1(1:M,1) = 1.0E-10*F1(1:M,1)
DO i = 1, N/2
CALL SGEMV( 'N', M, M, ONE, A, M, F1(1,i), 1, ZERO, &
F1(1,i+1), 1 )
END DO
X0(1:M,1:N/2) = F1(1:M,1:N/2)
Y0(1:M,1:N/2) = F1(1:M,2:N/2+1)
CALL SLARNV(2, ISEED, M, F1(1,1) )
DO i = 1, N-N/2
CALL SGEMV( 'N', M, M, ONE, A, M, F1(1,i), 1, ZERO, &
F1(1,i+1), 1 )
END DO
X0(1:M,N/2+1:N) = F1(1:M,1:N-N/2)
Y0(1:M,N/2+1:N) = F1(1:M,2:N-N/2+1)
ELSE
! single trajectory
CALL SLARNV(2, ISEED, M, F(1,1) )
DO i = 1, N
CALL SGEMV( 'N', M, M, ONE, A, M, F(1,i), 1, ZERO, &
F(1,i+1), 1 )
END DO
X0(1:M,1:N) = F(1:M,1:N)
Y0(1:M,1:N) = F(1:M,2:N+1)
END IF
XNORM = SLANGE( 'F', M, N, X0, LDX, WDUMMY )
YNORM = SLANGE( 'F', M, N, Y0, LDX, WDUMMY )
!............................................................
DO iJOBZ = 1, 4
SELECT CASE ( iJOBZ )
CASE(1)
JOBZ = 'V' ! Ritz vectors will be computed
RESIDS = 'R' ! Residuals will be computed
CASE(2)
JOBZ = 'V'
RESIDS = 'N'
CASE(3)
JOBZ = 'F' ! Ritz vectors in factored form
RESIDS = 'N'
CASE(4)
JOBZ = 'N'
RESIDS = 'N'
END SELECT
DO iJOBREF = 1, 3
SELECT CASE ( iJOBREF )
CASE(1)
JOBREF = 'R' ! Data for refined Ritz vectors
CASE(2)
JOBREF = 'E' ! Exact DMD vectors
CASE(3)
JOBREF = 'N'
END SELECT
DO iSCALE = 1, 4
SELECT CASE ( iSCALE )
CASE(1)
SCALE = 'S' ! X data normalized
CASE(2)
SCALE = 'C' ! X normalized, consist. check
CASE(3)
SCALE = 'Y' ! Y data normalized
CASE(4)
SCALE = 'N'
END SELECT
DO iNRNK = -1, -2, -1
! Two truncation strategies. The "-2" case for R&D
! purposes only - it uses possibly low accuracy small
! singular values, in which case the formulas used in
! the DMD are highly sensitive.
NRNK = iNRNK
DO iWHTSVD = 1, 4
! Check all four options to compute the POD basis
! via the SVD.
WHTSVD = iWHTSVD
DO LWMINOPT = 1, 2
! Workspace query for the minimal (1) and for the optimal
! (2) workspace lengths determined by workspace query.
X(1:M,1:N) = X0(1:M,1:N)
Y(1:M,1:N) = Y0(1:M,1:N)
! SGEDMD: Workspace query and workspace allocation
CALL SGEDMD( SCALE, JOBZ, RESIDS, JOBREF, WHTSVD, M, &
N, X, LDX, Y, LDY, NRNK, TOL, K, REIG, IEIG, Z, &
LDZ, RES, AU, LDAU, W, LDW, S, LDS, WDUMMY, -1, &
IDUMMY, -1, INFO )
LIWORK = IDUMMY(1)
ALLOCATE( IWORK(LIWORK) )
LWORK = INT(WDUMMY(LWMINOPT))
ALLOCATE( WORK(LWORK) )
! SGEDMD test: CALL SGEDMD
CALL SGEDMD( SCALE, JOBZ, RESIDS, JOBREF, WHTSVD, M, &
N, X, LDX, Y, LDY, NRNK, TOL, K, REIG, IEIG, Z, &
LDZ, RES, AU, LDAU, W, LDW, S, LDS, WORK, LWORK,&
IWORK, LIWORK, INFO )
SINGVX(1:N) = WORK(1:N)
!...... SGEDMD check point
IF ( LSAME(JOBZ,'V') ) THEN
! Check that Z = X*W, on return from SGEDMD
! This checks that the returned aigenvectors in Z are
! the product of the SVD'POD basis returned in X
! and the eigenvectors of the rayleigh quotient
! returned in W
CALL SGEMM( 'N', 'N', M, K, K, ONE, X, LDX, W, LDW, &
ZERO, Z1, LDZ )
TMP = ZERO
DO i = 1, K
CALL SAXPY( M, -ONE, Z(1,i), 1, Z1(1,i), 1)
TMP = MAX(TMP, SNRM2( M, Z1(1,i), 1 ) )
END DO
TMP_ZXW = MAX(TMP_ZXW, TMP )
IF ( TMP_ZXW > 10*M*EPS ) THEN
NFAIL_Z_XV = NFAIL_Z_XV + 1
END IF
END IF
!...... SGEDMD check point
IF ( LSAME(JOBREF,'R') ) THEN
! The matrix A*U is returned for computing refined Ritz vectors.
! Check that A*U is computed correctly using the formula
! A*U = Y * V * inv(SIGMA). This depends on the
! accuracy in the computed singular values and vectors of X.
! See the paper for an error analysis.
! Note that the left singular vectors of the input matrix X
! are returned in the array X.
CALL SGEMM( 'N', 'N', M, K, M, ONE, A, LDA, X, LDX, &
ZERO, Z1, LDZ )
TMP = ZERO
DO i = 1, K
CALL SAXPY( M, -ONE, AU(1,i), 1, Z1(1,i), 1)
TMP = MAX( TMP, SNRM2( M, Z1(1,i),1 ) * &
SINGVX(K)/(ANORM*SINGVX(1)) )
END DO
TMP_AU = MAX( TMP_AU, TMP )
IF ( TMP > TOL2 ) THEN
NFAIL_AU = NFAIL_AU + 1
END IF
ELSEIF ( LSAME(JOBREF,'E') ) THEN
! The unscaled vectors of the Exact DMD are computed.
! This option is included for the sake of completeness,
! for users who prefer the Exact DMD vectors. The
! returned vectors are in the real form, in the same way
! as the Ritz vectors. Here we just save the vectors
! and test them separately using a Matlab script.
CALL SGEMM( 'N', 'N', M, K, M, ONE, A, LDA, AU, LDAU, ZERO, Y1, M )
i=1
DO WHILE ( i <= K )
IF ( IEIG(i) == ZERO ) THEN
! have a real eigenvalue with real eigenvector
CALL SAXPY( M, -REIG(i), AU(1,i), 1, Y1(1,i), 1 )
RESEX(i) = SNRM2( M, Y1(1,i), 1) / SNRM2(M,AU(1,i),1)
i = i + 1
ELSE
! Have a complex conjugate pair
! REIG(i) +- sqrt(-1)*IMEIG(i).
! Since all computation is done in real
! arithmetic, the formula for the residual
! is recast for real representation of the
! complex conjugate eigenpair. See the
! description of RES.
AB(1,1) = REIG(i)
AB(2,1) = -IEIG(i)
AB(1,2) = IEIG(i)
AB(2,2) = REIG(i)
CALL SGEMM( 'N', 'N', M, 2, 2, -ONE, AU(1,i), &
M, AB, 2, ONE, Y1(1,i), M )
RESEX(i) = SLANGE( 'F', M, 2, Y1(1,i), M, &
WORK )/ SLANGE( 'F', M, 2, AU(1,i), M, &
WORK )
RESEX(i+1) = RESEX(i)
i = i + 2
END IF
END DO
END IF
!...... SGEDMD check point
IF ( LSAME(RESIDS, 'R') ) THEN
! Compare the residuals returned by SGEDMD with the
! explicitly computed residuals using the matrix A.
! Compute explicitly Y1 = A*Z
CALL SGEMM( 'N', 'N', M, K, M, ONE, A, LDA, Z, LDZ, ZERO, Y1, M )
! ... and then A*Z(:,i) - LAMBDA(i)*Z(:,i), using the real forms
! of the invariant subspaces that correspond to complex conjugate
! pairs of eigencalues. (See the description of Z in SGEDMD,)
i = 1
DO WHILE ( i <= K )
IF ( IEIG(i) == ZERO ) THEN
! have a real eigenvalue with real eigenvector
CALL SAXPY( M, -REIG(i), Z(1,i), 1, Y1(1,i), 1 )
RES1(i) = SNRM2( M, Y1(1,i), 1)
i = i + 1
ELSE
! Have a complex conjugate pair
! REIG(i) +- sqrt(-1)*IMEIG(i).
! Since all computation is done in real
! arithmetic, the formula for the residual
! is recast for real representation of the
! complex conjugate eigenpair. See the
! description of RES.
AB(1,1) = REIG(i)
AB(2,1) = -IEIG(i)
AB(1,2) = IEIG(i)
AB(2,2) = REIG(i)
CALL SGEMM( 'N', 'N', M, 2, 2, -ONE, Z(1,i), &
M, AB, 2, ONE, Y1(1,i), M )
RES1(i) = SLANGE( 'F', M, 2, Y1(1,i), M, &
WORK )
RES1(i+1) = RES1(i)
i = i + 2
END IF
END DO
TMP = ZERO
DO i = 1, K
TMP = MAX( TMP, ABS(RES(i) - RES1(i)) * &
SINGVX(K)/(ANORM*SINGVX(1)) )
END DO
TMP_REZ = MAX( TMP_REZ, TMP )
IF ( TMP > TOL2 ) THEN
NFAIL_REZ = NFAIL_REZ + 1
END IF
IF ( LSAME(JOBREF,'E') ) THEN
TMP = ZERO
DO i = 1, K
TMP = MAX( TMP, ABS(RES1(i) - RESEX(i))/(RES1(i)+RESEX(i)) )
END DO
TMP_EX = MAX(TMP_EX,TMP)
END IF
END IF
! ... store the results for inspection
DO i = 1, K
LAMBDA(i,1) = REIG(i)
LAMBDA(i,2) = IEIG(i)
END DO
DEALLOCATE(IWORK)
DEALLOCATE(WORK)
!======================================================================
! Now test the SGEDMDQ, if requested.
!======================================================================
IF ( TEST_QRDMD .AND. (K_TRAJ == 1) ) THEN
RJOBDATA(2) = 1
F1 = F
! SGEDMDQ test: Workspace query and workspace allocation
CALL SGEDMDQ( SCALE, JOBZ, RESIDS, WANTQ, WANTR, &
JOBREF, WHTSVD, M, N+1, F1, LDF, X, LDX, Y, &
LDY, NRNK, TOL, KQ, REIGQ, IEIGQ, Z, LDZ, &
RES, AU, LDAU, W, LDW, S, LDS, WDUMMY, &
-1, IDUMMY, -1, INFO )
LIWORK = IDUMMY(1)
ALLOCATE( IWORK(LIWORK) )
LWORK = INT(WDUMMY(LWMINOPT))
ALLOCATE(WORK(LWORK))
! SGEDMDQ test: CALL SGEDMDQ
CALL SGEDMDQ( SCALE, JOBZ, RESIDS, WANTQ, WANTR, &
JOBREF, WHTSVD, M, N+1, F1, LDF, X, LDX, Y, &
LDY, NRNK, TOL, KQ, REIGQ, IEIGQ, Z, LDZ, &
RES, AU, LDAU, W, LDW, S, LDS, &
WORK, LWORK, IWORK, LIWORK, INFO )
SINGVQX(1:KQ) = WORK(MIN(M,N+1)+1: MIN(M,N+1)+KQ)
!..... SGEDMDQ check point
IF ( KQ /= K ) THEN
KDIFF = KDIFF+1
END IF
TMP = ZERO
DO i = 1, MIN(K, KQ)
TMP = MAX(TMP, ABS(SINGVX(i)-SINGVQX(i)) / &
SINGVX(1) )
END DO
SVDIFF = MAX( SVDIFF, TMP )
IF ( TMP > M*N*EPS ) THEN
NFAIL_SVDIFF = NFAIL_SVDIFF + 1
END IF
!..... SGEDMDQ check point
IF ( LSAME(WANTQ,'Q') .AND. LSAME(WANTR,'R') ) THEN
! Check that the QR factors are computed and returned
! as requested. The residual ||F-Q*R||_F / ||F||_F
! is compared to M*N*EPS.
F2 = F
CALL SGEMM( 'N', 'N', M, N+1, MIN(M,N+1), -ONE, F1, &
LDF, Y, LDY, ONE, F2, LDF )
TMP_FQR = SLANGE( 'F', M, N+1, F2, LDF, WORK ) / &
SLANGE( 'F', M, N+1, F, LDF, WORK )
IF ( TMP_FQR > TOL2 ) THEN
NFAIL_F_QR = NFAIL_F_QR + 1
END IF
END IF
!..... SGEDMDQ checkpoint
IF ( LSAME(RESIDS, 'R') ) THEN
! Compare the residuals returned by SGEDMDQ with the
! explicitly computed residuals using the matrix A.
! Compute explicitly Y1 = A*Z
CALL SGEMM( 'N', 'N', M, KQ, M, ONE, A, M, Z, M, ZERO, Y1, M )
! ... and then A*Z(:,i) - LAMBDA(i)*Z(:,i), using the real forms
! of the invariant subspaces that correspond to complex conjugate
! pairs of eigencalues. (See the description of Z in SGEDMDQ)
i = 1
DO WHILE ( i <= KQ )
IF ( IEIGQ(i) == ZERO ) THEN
! have a real eigenvalue with real eigenvector
CALL SAXPY( M, -REIGQ(i), Z(1,i), 1, Y1(1,i), 1 )
! Y(1:M,i) = Y(1:M,i) - REIG(i)*Z(1:M,i)
RES1(i) = SNRM2( M, Y1(1,i), 1)
i = i + 1
ELSE
! Have a complex conjugate pair
! REIG(i) +- sqrt(-1)*IMEIG(i).
! Since all computation is done in real
! arithmetic, the formula for the residual
! is recast for real representation of the
! complex conjugate eigenpair. See the
! description of RES.
AB(1,1) = REIGQ(i)
AB(2,1) = -IEIGQ(i)
AB(1,2) = IEIGQ(i)
AB(2,2) = REIGQ(i)
CALL SGEMM( 'N', 'N', M, 2, 2, -ONE, Z(1,i), &
M, AB, 2, ONE, Y1(1,i), M ) ! BLAS CALL
! Y(1:M,i:i+1) = Y(1:M,i:i+1) - Z(1:M,i:i+1) * AB ! INTRINSIC
RES1(i) = SLANGE( 'F', M, 2, Y1(1,i), M, &
WORK ) ! LAPACK CALL
RES1(i+1) = RES1(i)
i = i + 2
END IF
END DO
TMP = ZERO
DO i = 1, KQ
TMP = MAX( TMP, ABS(RES(i) - RES1(i)) * &
SINGVQX(K)/(ANORM*SINGVQX(1)) )
END DO
TMP_REZQ = MAX( TMP_REZQ, TMP )
IF ( TMP > TOL2 ) THEN
NFAIL_REZQ = NFAIL_REZQ + 1
END IF
END IF
DO i = 1, KQ
LAMBDAQ(i,1) = REIGQ(i)
LAMBDAQ(i,2) = IEIGQ(i)
END DO
DEALLOCATE(WORK)
DEALLOCATE(IWORK)
END IF ! TEST_QRDMD
!======================================================================
END DO ! LWMINOPT
!write(*,*) 'LWMINOPT loop completed'
END DO ! WHTSVD LOOP
!write(*,*) 'WHTSVD loop completed'
END DO ! NRNK LOOP
!write(*,*) 'NRNK loop completed'
END DO ! SCALE LOOP
!write(*,*) 'SCALE loop completed'
END DO ! JOBF LOOP
!write(*,*) 'JOBREF loop completed'
END DO ! JOBZ LOOP
!write(*,*) 'JOBZ loop completed'
END DO ! MODE -6:6
!write(*,*) 'MODE loop completed'
END DO ! 1 or 2 trajectories
!write(*,*) 'trajectories loop completed'
DEALLOCATE(A)
DEALLOCATE(AC)
DEALLOCATE(DA)
DEALLOCATE(DL)
DEALLOCATE(F)
DEALLOCATE(F1)
DEALLOCATE(F2)
DEALLOCATE(X)
DEALLOCATE(X0)
DEALLOCATE(SINGVX)
DEALLOCATE(SINGVQX)
DEALLOCATE(Y)
DEALLOCATE(Y0)
DEALLOCATE(Y1)
DEALLOCATE(Z)
DEALLOCATE(Z1)
DEALLOCATE(RES)
DEALLOCATE(RES1)
DEALLOCATE(RESEX)
DEALLOCATE(REIG)
DEALLOCATE(IEIG)
DEALLOCATE(REIGQ)
DEALLOCATE(IEIGQ)
DEALLOCATE(REIGA)
DEALLOCATE(IEIGA)
DEALLOCATE(VA)
DEALLOCATE(LAMBDA)
DEALLOCATE(LAMBDAQ)
DEALLOCATE(EIGA)
DEALLOCATE(W)
DEALLOCATE(AU)
DEALLOCATE(S)
!............................................................
! Generate random M-by-M matrix A. Use DLATMR from
END DO ! LLOOP
WRITE(*,*) '>>>>>>>>>>>>>>>>>>>>>>>>>>'
WRITE(*,*) ' Test summary for SGEDMD :'
WRITE(*,*) '>>>>>>>>>>>>>>>>>>>>>>>>>>'
WRITE(*,*)
IF ( NFAIL_Z_XV == 0 ) THEN
WRITE(*,*) '>>>> Z - U*V test PASSED.'
ELSE
WRITE(*,*) 'Z - U*V test FAILED ', NFAIL_Z_XV, ' time(s)'
WRITE(*,*) 'Max error ||Z-U*V||_F was ', TMP_ZXW
NFAIL_TOTAL = NFAIL_TOTAL + NFAIL_Z_XV
END IF
IF ( NFAIL_AU == 0 ) THEN
WRITE(*,*) '>>>> A*U test PASSED. '
ELSE
WRITE(*,*) 'A*U test FAILED ', NFAIL_AU, ' time(s)'
WRITE(*,*) 'Max A*U test adjusted error measure was ', TMP_AU
WRITE(*,*) 'It should be up to O(M*N) times EPS, EPS = ', EPS
NFAIL_TOTAL = NFAIL_TOTAL + NFAIL_AU
END IF
IF ( NFAIL_REZ == 0 ) THEN
WRITE(*,*) '>>>> Rezidual computation test PASSED.'
ELSE
WRITE(*,*) 'Rezidual computation test FAILED ', NFAIL_REZ, 'time(s)'
WRITE(*,*) 'Max residual computing test adjusted error measure was ', TMP_REZ
WRITE(*,*) 'It should be up to O(M*N) times EPS, EPS = ', EPS
NFAIL_TOTAL = NFAIL_TOTAL + NFAIL_REZ
END IF
IF ( NFAIL_TOTAL == 0 ) THEN
WRITE(*,*) '>>>> SGEDMD :: ALL TESTS PASSED.'
ELSE
WRITE(*,*) NFAIL_TOTAL, 'FAILURES!'
WRITE(*,*) '>>>>>>>>>>>>>> SGEDMD :: TESTS FAILED. CHECK THE IMPLEMENTATION.'
END IF
IF ( TEST_QRDMD ) THEN
WRITE(*,*)
WRITE(*,*) '>>>>>>>>>>>>>>>>>>>>>>>>>>'
WRITE(*,*) ' Test summary for SGEDMDQ :'
WRITE(*,*) '>>>>>>>>>>>>>>>>>>>>>>>>>>'
WRITE(*,*)
IF ( NFAIL_SVDIFF == 0 ) THEN
WRITE(*,*) '>>>> SGEDMD and SGEDMDQ computed singular &
&values test PASSED.'
ELSE
WRITE(*,*) 'SGEDMD and SGEDMDQ discrepancies in &
&the singular values unacceptable ', &
NFAIL_SVDIFF, ' times. Test FAILED.'
WRITE(*,*) 'The maximal discrepancy in the singular values (relative to the norm) was ', SVDIFF
WRITE(*,*) 'It should be up to O(M*N) times EPS, EPS = ', EPS
NFAILQ_TOTAL = NFAILQ_TOTAL + NFAIL_SVDIFF
END IF
IF ( NFAIL_F_QR == 0 ) THEN
WRITE(*,*) '>>>> F - Q*R test PASSED.'
ELSE
WRITE(*,*) 'F - Q*R test FAILED ', NFAIL_F_QR, ' time(s)'
WRITE(*,*) 'The largest relative residual was ', TMP_FQR
WRITE(*,*) 'It should be up to O(M*N) times EPS, EPS = ', EPS
NFAILQ_TOTAL = NFAILQ_TOTAL + NFAIL_F_QR
END IF
IF ( NFAIL_REZQ == 0 ) THEN
WRITE(*,*) '>>>> Rezidual computation test PASSED.'
ELSE
WRITE(*,*) 'Rezidual computation test FAILED ', NFAIL_REZQ, 'time(s)'
WRITE(*,*) 'Max residual computing test adjusted error measure was ', TMP_REZQ
WRITE(*,*) 'It should be up to O(M*N) times EPS, EPS = ', EPS
NFAILQ_TOTAL = NFAILQ_TOTAL + NFAIL_REZQ
END IF
IF ( NFAILQ_TOTAL == 0 ) THEN
WRITE(*,*) '>>>>>>> SGEDMDQ :: ALL TESTS PASSED.'
ELSE
WRITE(*,*) NFAILQ_TOTAL, 'FAILURES!'
WRITE(*,*) '>>>>>>> SGEDMDQ :: TESTS FAILED. CHECK THE IMPLEMENTATION.'
END IF
END IF
WRITE(*,*)
WRITE(*,*) 'Test completed.'
STOP
END