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Werner Saar
2017-01-06 11:48:40 +01:00
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lapack-netlib/TESTING/EIG/cdrgev.f
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*> \brief \b CDRGEV
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
* Definition:
* ===========
*
* SUBROUTINE CDRGEV( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
* NOUNIT, A, LDA, B, S, T, Q, LDQ, Z, QE, LDQE,
* ALPHA, BETA, ALPHA1, BETA1, WORK, LWORK, RWORK,
* RESULT, INFO )
*
* .. Scalar Arguments ..
* INTEGER INFO, LDA, LDQ, LDQE, LWORK, NOUNIT, NSIZES,
* $ NTYPES
* REAL THRESH
* ..
* .. Array Arguments ..
* LOGICAL DOTYPE( * )
* INTEGER ISEED( 4 ), NN( * )
* REAL RESULT( * ), RWORK( * )
* COMPLEX A( LDA, * ), ALPHA( * ), ALPHA1( * ),
* $ B( LDA, * ), BETA( * ), BETA1( * ),
* $ Q( LDQ, * ), QE( LDQE, * ), S( LDA, * ),
* $ T( LDA, * ), WORK( * ), Z( LDQ, * )
* ..
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> CDRGEV checks the nonsymmetric generalized eigenvalue problem driver
*> routine CGGEV.
*>
*> CGGEV computes for a pair of n-by-n nonsymmetric matrices (A,B) the
*> generalized eigenvalues and, optionally, the left and right
*> eigenvectors.
*>
*> A generalized eigenvalue for a pair of matrices (A,B) is a scalar w
*> or a ratio alpha/beta = w, such that A - w*B is singular. It is
*> usually represented as the pair (alpha,beta), as there is reasonable
*> interpretation for beta=0, and even for both being zero.
*>
*> A right generalized eigenvector corresponding to a generalized
*> eigenvalue w for a pair of matrices (A,B) is a vector r such that
*> (A - wB) * r = 0. A left generalized eigenvector is a vector l such
*> that l**H * (A - wB) = 0, where l**H is the conjugate-transpose of l.
*>
*> When CDRGEV is called, a number of matrix "sizes" ("n's") and a
*> number of matrix "types" are specified. For each size ("n")
*> and each type of matrix, a pair of matrices (A, B) will be generated
*> and used for testing. For each matrix pair, the following tests
*> will be performed and compared with the threshold THRESH.
*>
*> Results from CGGEV:
*>
*> (1) max over all left eigenvalue/-vector pairs (alpha/beta,l) of
*>
*> | VL**H * (beta A - alpha B) |/( ulp max(|beta A|, |alpha B|) )
*>
*> where VL**H is the conjugate-transpose of VL.
*>
*> (2) | |VL(i)| - 1 | / ulp and whether largest component real
*>
*> VL(i) denotes the i-th column of VL.
*>
*> (3) max over all left eigenvalue/-vector pairs (alpha/beta,r) of
*>
*> | (beta A - alpha B) * VR | / ( ulp max(|beta A|, |alpha B|) )
*>
*> (4) | |VR(i)| - 1 | / ulp and whether largest component real
*>
*> VR(i) denotes the i-th column of VR.
*>
*> (5) W(full) = W(partial)
*> W(full) denotes the eigenvalues computed when both l and r
*> are also computed, and W(partial) denotes the eigenvalues
*> computed when only W, only W and r, or only W and l are
*> computed.
*>
*> (6) VL(full) = VL(partial)
*> VL(full) denotes the left eigenvectors computed when both l
*> and r are computed, and VL(partial) denotes the result
*> when only l is computed.
*>
*> (7) VR(full) = VR(partial)
*> VR(full) denotes the right eigenvectors computed when both l
*> and r are also computed, and VR(partial) denotes the result
*> when only l is computed.
*>
*>
*> Test Matrices
*> ---- --------
*>
*> The sizes of the test matrices are specified by an array
*> NN(1:NSIZES); the value of each element NN(j) specifies one size.
*> The "types" are specified by a logical array DOTYPE( 1:NTYPES ); if
*> DOTYPE(j) is .TRUE., then matrix type "j" will be generated.
*> Currently, the list of possible types is:
*>
*> (1) ( 0, 0 ) (a pair of zero matrices)
*>
*> (2) ( I, 0 ) (an identity and a zero matrix)
*>
*> (3) ( 0, I ) (an identity and a zero matrix)
*>
*> (4) ( I, I ) (a pair of identity matrices)
*>
*> t t
*> (5) ( J , J ) (a pair of transposed Jordan blocks)
*>
*> t ( I 0 )
*> (6) ( X, Y ) where X = ( J 0 ) and Y = ( t )
*> ( 0 I ) ( 0 J )
*> and I is a k x k identity and J a (k+1)x(k+1)
*> Jordan block; k=(N-1)/2
*>
*> (7) ( D, I ) where D is diag( 0, 1,..., N-1 ) (a diagonal
*> matrix with those diagonal entries.)
*> (8) ( I, D )
*>
*> (9) ( big*D, small*I ) where "big" is near overflow and small=1/big
*>
*> (10) ( small*D, big*I )
*>
*> (11) ( big*I, small*D )
*>
*> (12) ( small*I, big*D )
*>
*> (13) ( big*D, big*I )
*>
*> (14) ( small*D, small*I )
*>
*> (15) ( D1, D2 ) where D1 is diag( 0, 0, 1, ..., N-3, 0 ) and
*> D2 is diag( 0, N-3, N-4,..., 1, 0, 0 )
*> t t
*> (16) Q ( J , J ) Z where Q and Z are random orthogonal matrices.
*>
*> (17) Q ( T1, T2 ) Z where T1 and T2 are upper triangular matrices
*> with random O(1) entries above the diagonal
*> and diagonal entries diag(T1) =
*> ( 0, 0, 1, ..., N-3, 0 ) and diag(T2) =
*> ( 0, N-3, N-4,..., 1, 0, 0 )
*>
*> (18) Q ( T1, T2 ) Z diag(T1) = ( 0, 0, 1, 1, s, ..., s, 0 )
*> diag(T2) = ( 0, 1, 0, 1,..., 1, 0 )
*> s = machine precision.
*>
*> (19) Q ( T1, T2 ) Z diag(T1)=( 0,0,1,1, 1-d, ..., 1-(N-5)*d=s, 0 )
*> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0 )
*>
*> N-5
*> (20) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, 1, a, ..., a =s, 0 )
*> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
*>
*> (21) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, r1, r2, ..., r(N-4), 0 )
*> diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
*> where r1,..., r(N-4) are random.
*>
*> (22) Q ( big*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
*> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
*>
*> (23) Q ( small*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
*> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
*>
*> (24) Q ( small*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
*> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
*>
*> (25) Q ( big*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
*> diag(T2) = ( 0, 1, ..., 1, 0, 0 )
*>
*> (26) Q ( T1, T2 ) Z where T1 and T2 are random upper-triangular
*> matrices.
*>
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] NSIZES
*> \verbatim
*> NSIZES is INTEGER
*> The number of sizes of matrices to use. If it is zero,
*> CDRGES does nothing. NSIZES >= 0.
*> \endverbatim
*>
*> \param[in] NN
*> \verbatim
*> NN is INTEGER array, dimension (NSIZES)
*> An array containing the sizes to be used for the matrices.
*> Zero values will be skipped. NN >= 0.
*> \endverbatim
*>
*> \param[in] NTYPES
*> \verbatim
*> NTYPES is INTEGER
*> The number of elements in DOTYPE. If it is zero, CDRGEV
*> does nothing. It must be at least zero. If it is MAXTYP+1
*> and NSIZES is 1, then an additional type, MAXTYP+1 is
*> defined, which is to use whatever matrix is in A. This
*> is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
*> DOTYPE(MAXTYP+1) is .TRUE. .
*> \endverbatim
*>
*> \param[in] DOTYPE
*> \verbatim
*> DOTYPE is LOGICAL array, dimension (NTYPES)
*> If DOTYPE(j) is .TRUE., then for each size in NN a
*> matrix of that size and of type j will be generated.
*> If NTYPES is smaller than the maximum number of types
*> defined (PARAMETER MAXTYP), then types NTYPES+1 through
*> MAXTYP will not be generated. If NTYPES is larger
*> than MAXTYP, DOTYPE(MAXTYP+1) through DOTYPE(NTYPES)
*> will be ignored.
*> \endverbatim
*>
*> \param[in,out] ISEED
*> \verbatim
*> ISEED is INTEGER array, dimension (4)
*> On entry ISEED specifies the seed of the random number
*> generator. The array elements should be between 0 and 4095;
*> if not they will be reduced mod 4096. Also, ISEED(4) must
*> be odd. The random number generator uses a linear
*> congruential sequence limited to small integers, and so
*> should produce machine independent random numbers. The
*> values of ISEED are changed on exit, and can be used in the
*> next call to CDRGES to continue the same random number
*> sequence.
*> \endverbatim
*>
*> \param[in] THRESH
*> \verbatim
*> THRESH is REAL
*> A test will count as "failed" if the "error", computed as
*> described above, exceeds THRESH. Note that the error is
*> scaled to be O(1), so THRESH should be a reasonably small
*> multiple of 1, e.g., 10 or 100. In particular, it should
*> not depend on the precision (single vs. double) or the size
*> of the matrix. It must be at least zero.
*> \endverbatim
*>
*> \param[in] NOUNIT
*> \verbatim
*> NOUNIT is INTEGER
*> The FORTRAN unit number for printing out error messages
*> (e.g., if a routine returns IERR not equal to 0.)
*> \endverbatim
*>
*> \param[in,out] A
*> \verbatim
*> A is COMPLEX array, dimension(LDA, max(NN))
*> Used to hold the original A matrix. Used as input only
*> if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
*> DOTYPE(MAXTYP+1)=.TRUE.
*> \endverbatim
*>
*> \param[in] LDA
*> \verbatim
*> LDA is INTEGER
*> The leading dimension of A, B, S, and T.
*> It must be at least 1 and at least max( NN ).
*> \endverbatim
*>
*> \param[in,out] B
*> \verbatim
*> B is COMPLEX array, dimension(LDA, max(NN))
*> Used to hold the original B matrix. Used as input only
*> if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
*> DOTYPE(MAXTYP+1)=.TRUE.
*> \endverbatim
*>
*> \param[out] S
*> \verbatim
*> S is COMPLEX array, dimension (LDA, max(NN))
*> The Schur form matrix computed from A by CGGEV. On exit, S
*> contains the Schur form matrix corresponding to the matrix
*> in A.
*> \endverbatim
*>
*> \param[out] T
*> \verbatim
*> T is COMPLEX array, dimension (LDA, max(NN))
*> The upper triangular matrix computed from B by CGGEV.
*> \endverbatim
*>
*> \param[out] Q
*> \verbatim
*> Q is COMPLEX array, dimension (LDQ, max(NN))
*> The (left) eigenvectors matrix computed by CGGEV.
*> \endverbatim
*>
*> \param[in] LDQ
*> \verbatim
*> LDQ is INTEGER
*> The leading dimension of Q and Z. It must
*> be at least 1 and at least max( NN ).
*> \endverbatim
*>
*> \param[out] Z
*> \verbatim
*> Z is COMPLEX array, dimension( LDQ, max(NN) )
*> The (right) orthogonal matrix computed by CGGEV.
*> \endverbatim
*>
*> \param[out] QE
*> \verbatim
*> QE is COMPLEX array, dimension( LDQ, max(NN) )
*> QE holds the computed right or left eigenvectors.
*> \endverbatim
*>
*> \param[in] LDQE
*> \verbatim
*> LDQE is INTEGER
*> The leading dimension of QE. LDQE >= max(1,max(NN)).
*> \endverbatim
*>
*> \param[out] ALPHA
*> \verbatim
*> ALPHA is COMPLEX array, dimension (max(NN))
*> \endverbatim
*>
*> \param[out] BETA
*> \verbatim
*> BETA is COMPLEX array, dimension (max(NN))
*>
*> The generalized eigenvalues of (A,B) computed by CGGEV.
*> ( ALPHAR(k)+ALPHAI(k)*i ) / BETA(k) is the k-th
*> generalized eigenvalue of A and B.
*> \endverbatim
*>
*> \param[out] ALPHA1
*> \verbatim
*> ALPHA1 is COMPLEX array, dimension (max(NN))
*> \endverbatim
*>
*> \param[out] BETA1
*> \verbatim
*> BETA1 is COMPLEX array, dimension (max(NN))
*>
*> Like ALPHAR, ALPHAI, BETA, these arrays contain the
*> eigenvalues of A and B, but those computed when CGGEV only
*> computes a partial eigendecomposition, i.e. not the
*> eigenvalues and left and right eigenvectors.
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*> WORK is COMPLEX array, dimension (LWORK)
*> \endverbatim
*>
*> \param[in] LWORK
*> \verbatim
*> LWORK is INTEGER
*> The number of entries in WORK. LWORK >= N*(N+1)
*> \endverbatim
*>
*> \param[out] RWORK
*> \verbatim
*> RWORK is REAL array, dimension (8*N)
*> Real workspace.
*> \endverbatim
*>
*> \param[out] RESULT
*> \verbatim
*> RESULT is REAL array, dimension (2)
*> The values computed by the tests described above.
*> The values are currently limited to 1/ulp, to avoid overflow.
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*> INFO is INTEGER
*> = 0: successful exit
*> < 0: if INFO = -i, the i-th argument had an illegal value.
*> > 0: A routine returned an error code. INFO is the
*> absolute value of the INFO value returned.
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date June 2016
*
*> \ingroup complex_eig
*
* =====================================================================
SUBROUTINE CDRGEV( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
$ NOUNIT, A, LDA, B, S, T, Q, LDQ, Z, QE, LDQE,
$ ALPHA, BETA, ALPHA1, BETA1, WORK, LWORK, RWORK,
$ RESULT, INFO )
*
* -- LAPACK test routine (version 3.7.0) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
* June 2016
*
* .. Scalar Arguments ..
INTEGER INFO, LDA, LDQ, LDQE, LWORK, NOUNIT, NSIZES,
$ NTYPES
REAL THRESH
* ..
* .. Array Arguments ..
LOGICAL DOTYPE( * )
INTEGER ISEED( 4 ), NN( * )
REAL RESULT( * ), RWORK( * )
COMPLEX A( LDA, * ), ALPHA( * ), ALPHA1( * ),
$ B( LDA, * ), BETA( * ), BETA1( * ),
$ Q( LDQ, * ), QE( LDQE, * ), S( LDA, * ),
$ T( LDA, * ), WORK( * ), Z( LDQ, * )
* ..
*
* =====================================================================
*
* .. Parameters ..
REAL ZERO, ONE
PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 )
COMPLEX CZERO, CONE
PARAMETER ( CZERO = ( 0.0E+0, 0.0E+0 ),
$ CONE = ( 1.0E+0, 0.0E+0 ) )
INTEGER MAXTYP
PARAMETER ( MAXTYP = 26 )
* ..
* .. Local Scalars ..
LOGICAL BADNN
INTEGER I, IADD, IERR, IN, J, JC, JR, JSIZE, JTYPE,
$ MAXWRK, MINWRK, MTYPES, N, N1, NB, NERRS,
$ NMATS, NMAX, NTESTT
REAL SAFMAX, SAFMIN, ULP, ULPINV
COMPLEX CTEMP
* ..
* .. Local Arrays ..
LOGICAL LASIGN( MAXTYP ), LBSIGN( MAXTYP )
INTEGER IOLDSD( 4 ), KADD( 6 ), KAMAGN( MAXTYP ),
$ KATYPE( MAXTYP ), KAZERO( MAXTYP ),
$ KBMAGN( MAXTYP ), KBTYPE( MAXTYP ),
$ KBZERO( MAXTYP ), KCLASS( MAXTYP ),
$ KTRIAN( MAXTYP ), KZ1( 6 ), KZ2( 6 )
REAL RMAGN( 0: 3 )
* ..
* .. External Functions ..
INTEGER ILAENV
REAL SLAMCH
COMPLEX CLARND
EXTERNAL ILAENV, SLAMCH, CLARND
* ..
* .. External Subroutines ..
EXTERNAL ALASVM, CGET52, CGGEV, CLACPY, CLARFG, CLASET,
$ CLATM4, CUNM2R, SLABAD, XERBLA
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, CONJG, MAX, MIN, REAL, SIGN
* ..
* .. Data statements ..
DATA KCLASS / 15*1, 10*2, 1*3 /
DATA KZ1 / 0, 1, 2, 1, 3, 3 /
DATA KZ2 / 0, 0, 1, 2, 1, 1 /
DATA KADD / 0, 0, 0, 0, 3, 2 /
DATA KATYPE / 0, 1, 0, 1, 2, 3, 4, 1, 4, 4, 1, 1, 4,
$ 4, 4, 2, 4, 5, 8, 7, 9, 4*4, 0 /
DATA KBTYPE / 0, 0, 1, 1, 2, -3, 1, 4, 1, 1, 4, 4,
$ 1, 1, -4, 2, -4, 8*8, 0 /
DATA KAZERO / 6*1, 2, 1, 2*2, 2*1, 2*2, 3, 1, 3,
$ 4*5, 4*3, 1 /
DATA KBZERO / 6*1, 1, 2, 2*1, 2*2, 2*1, 4, 1, 4,
$ 4*6, 4*4, 1 /
DATA KAMAGN / 8*1, 2, 3, 2, 3, 2, 3, 7*1, 2, 3, 3,
$ 2, 1 /
DATA KBMAGN / 8*1, 3, 2, 3, 2, 2, 3, 7*1, 3, 2, 3,
$ 2, 1 /
DATA KTRIAN / 16*0, 10*1 /
DATA LASIGN / 6*.FALSE., .TRUE., .FALSE., 2*.TRUE.,
$ 2*.FALSE., 3*.TRUE., .FALSE., .TRUE.,
$ 3*.FALSE., 5*.TRUE., .FALSE. /
DATA LBSIGN / 7*.FALSE., .TRUE., 2*.FALSE.,
$ 2*.TRUE., 2*.FALSE., .TRUE., .FALSE., .TRUE.,
$ 9*.FALSE. /
* ..
* .. Executable Statements ..
*
* Check for errors
*
INFO = 0
*
BADNN = .FALSE.
NMAX = 1
DO 10 J = 1, NSIZES
NMAX = MAX( NMAX, NN( J ) )
IF( NN( J ).LT.0 )
$ BADNN = .TRUE.
10 CONTINUE
*
IF( NSIZES.LT.0 ) THEN
INFO = -1
ELSE IF( BADNN ) THEN
INFO = -2
ELSE IF( NTYPES.LT.0 ) THEN
INFO = -3
ELSE IF( THRESH.LT.ZERO ) THEN
INFO = -6
ELSE IF( LDA.LE.1 .OR. LDA.LT.NMAX ) THEN
INFO = -9
ELSE IF( LDQ.LE.1 .OR. LDQ.LT.NMAX ) THEN
INFO = -14
ELSE IF( LDQE.LE.1 .OR. LDQE.LT.NMAX ) THEN
INFO = -17
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.
*
MINWRK = 1
IF( INFO.EQ.0 .AND. LWORK.GE.1 ) THEN
MINWRK = NMAX*( NMAX+1 )
NB = MAX( 1, ILAENV( 1, 'CGEQRF', ' ', NMAX, NMAX, -1, -1 ),
$ ILAENV( 1, 'CUNMQR', 'LC', NMAX, NMAX, NMAX, -1 ),
$ ILAENV( 1, 'CUNGQR', ' ', NMAX, NMAX, NMAX, -1 ) )
MAXWRK = MAX( 2*NMAX, NMAX*( NB+1 ), NMAX*( NMAX+1 ) )
WORK( 1 ) = MAXWRK
END IF
*
IF( LWORK.LT.MINWRK )
$ INFO = -23
*
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'CDRGEV', -INFO )
RETURN
END IF
*
* Quick return if possible
*
IF( NSIZES.EQ.0 .OR. NTYPES.EQ.0 )
$ RETURN
*
ULP = SLAMCH( 'Precision' )
SAFMIN = SLAMCH( 'Safe minimum' )
SAFMIN = SAFMIN / ULP
SAFMAX = ONE / SAFMIN
CALL SLABAD( SAFMIN, SAFMAX )
ULPINV = ONE / ULP
*
* The values RMAGN(2:3) depend on N, see below.
*
RMAGN( 0 ) = ZERO
RMAGN( 1 ) = ONE
*
* Loop over sizes, types
*
NTESTT = 0
NERRS = 0
NMATS = 0
*
DO 220 JSIZE = 1, NSIZES
N = NN( JSIZE )
N1 = MAX( 1, N )
RMAGN( 2 ) = SAFMAX*ULP / REAL( N1 )
RMAGN( 3 ) = SAFMIN*ULPINV*N1
*
IF( NSIZES.NE.1 ) THEN
MTYPES = MIN( MAXTYP, NTYPES )
ELSE
MTYPES = MIN( MAXTYP+1, NTYPES )
END IF
*
DO 210 JTYPE = 1, MTYPES
IF( .NOT.DOTYPE( JTYPE ) )
$ GO TO 210
NMATS = NMATS + 1
*
* Save ISEED in case of an error.
*
DO 20 J = 1, 4
IOLDSD( J ) = ISEED( J )
20 CONTINUE
*
* Generate test matrices A and B
*
* Description of control parameters:
*
* KCLASS: =1 means w/o rotation, =2 means w/ rotation,
* =3 means random.
* KATYPE: the "type" to be passed to CLATM4 for computing A.
* KAZERO: the pattern of zeros on the diagonal for A:
* =1: ( xxx ), =2: (0, xxx ) =3: ( 0, 0, xxx, 0 ),
* =4: ( 0, xxx, 0, 0 ), =5: ( 0, 0, 1, xxx, 0 ),
* =6: ( 0, 1, 0, xxx, 0 ). (xxx means a string of
* non-zero entries.)
* KAMAGN: the magnitude of the matrix: =0: zero, =1: O(1),
* =2: large, =3: small.
* LASIGN: .TRUE. if the diagonal elements of A are to be
* multiplied by a random magnitude 1 number.
* KBTYPE, KBZERO, KBMAGN, LBSIGN: the same, but for B.
* KTRIAN: =0: don't fill in the upper triangle, =1: do.
* KZ1, KZ2, KADD: used to implement KAZERO and KBZERO.
* RMAGN: used to implement KAMAGN and KBMAGN.
*
IF( MTYPES.GT.MAXTYP )
$ GO TO 100
IERR = 0
IF( KCLASS( JTYPE ).LT.3 ) THEN
*
* Generate A (w/o rotation)
*
IF( ABS( KATYPE( JTYPE ) ).EQ.3 ) THEN
IN = 2*( ( N-1 ) / 2 ) + 1
IF( IN.NE.N )
$ CALL CLASET( 'Full', N, N, CZERO, CZERO, A, LDA )
ELSE
IN = N
END IF
CALL CLATM4( KATYPE( JTYPE ), IN, KZ1( KAZERO( JTYPE ) ),
$ KZ2( KAZERO( JTYPE ) ), LASIGN( JTYPE ),
$ RMAGN( KAMAGN( JTYPE ) ), ULP,
$ RMAGN( KTRIAN( JTYPE )*KAMAGN( JTYPE ) ), 2,
$ ISEED, A, LDA )
IADD = KADD( KAZERO( JTYPE ) )
IF( IADD.GT.0 .AND. IADD.LE.N )
$ A( IADD, IADD ) = RMAGN( KAMAGN( JTYPE ) )
*
* Generate B (w/o rotation)
*
IF( ABS( KBTYPE( JTYPE ) ).EQ.3 ) THEN
IN = 2*( ( N-1 ) / 2 ) + 1
IF( IN.NE.N )
$ CALL CLASET( 'Full', N, N, CZERO, CZERO, B, LDA )
ELSE
IN = N
END IF
CALL CLATM4( KBTYPE( JTYPE ), IN, KZ1( KBZERO( JTYPE ) ),
$ KZ2( KBZERO( JTYPE ) ), LBSIGN( JTYPE ),
$ RMAGN( KBMAGN( JTYPE ) ), ONE,
$ RMAGN( KTRIAN( JTYPE )*KBMAGN( JTYPE ) ), 2,
$ ISEED, B, LDA )
IADD = KADD( KBZERO( JTYPE ) )
IF( IADD.NE.0 .AND. IADD.LE.N )
$ B( IADD, IADD ) = RMAGN( KBMAGN( JTYPE ) )
*
IF( KCLASS( JTYPE ).EQ.2 .AND. N.GT.0 ) THEN
*
* Include rotations
*
* Generate Q, Z as Householder transformations times
* a diagonal matrix.
*
DO 40 JC = 1, N - 1
DO 30 JR = JC, N
Q( JR, JC ) = CLARND( 3, ISEED )
Z( JR, JC ) = CLARND( 3, ISEED )
30 CONTINUE
CALL CLARFG( N+1-JC, Q( JC, JC ), Q( JC+1, JC ), 1,
$ WORK( JC ) )
WORK( 2*N+JC ) = SIGN( ONE, REAL( Q( JC, JC ) ) )
Q( JC, JC ) = CONE
CALL CLARFG( N+1-JC, Z( JC, JC ), Z( JC+1, JC ), 1,
$ WORK( N+JC ) )
WORK( 3*N+JC ) = SIGN( ONE, REAL( Z( JC, JC ) ) )
Z( JC, JC ) = CONE
40 CONTINUE
CTEMP = CLARND( 3, ISEED )
Q( N, N ) = CONE
WORK( N ) = CZERO
WORK( 3*N ) = CTEMP / ABS( CTEMP )
CTEMP = CLARND( 3, ISEED )
Z( N, N ) = CONE
WORK( 2*N ) = CZERO
WORK( 4*N ) = CTEMP / ABS( CTEMP )
*
* Apply the diagonal matrices
*
DO 60 JC = 1, N
DO 50 JR = 1, N
A( JR, JC ) = WORK( 2*N+JR )*
$ CONJG( WORK( 3*N+JC ) )*
$ A( JR, JC )
B( JR, JC ) = WORK( 2*N+JR )*
$ CONJG( WORK( 3*N+JC ) )*
$ B( JR, JC )
50 CONTINUE
60 CONTINUE
CALL CUNM2R( 'L', 'N', N, N, N-1, Q, LDQ, WORK, A,
$ LDA, WORK( 2*N+1 ), IERR )
IF( IERR.NE.0 )
$ GO TO 90
CALL CUNM2R( 'R', 'C', N, N, N-1, Z, LDQ, WORK( N+1 ),
$ A, LDA, WORK( 2*N+1 ), IERR )
IF( IERR.NE.0 )
$ GO TO 90
CALL CUNM2R( 'L', 'N', N, N, N-1, Q, LDQ, WORK, B,
$ LDA, WORK( 2*N+1 ), IERR )
IF( IERR.NE.0 )
$ GO TO 90
CALL CUNM2R( 'R', 'C', N, N, N-1, Z, LDQ, WORK( N+1 ),
$ B, LDA, WORK( 2*N+1 ), IERR )
IF( IERR.NE.0 )
$ GO TO 90
END IF
ELSE
*
* Random matrices
*
DO 80 JC = 1, N
DO 70 JR = 1, N
A( JR, JC ) = RMAGN( KAMAGN( JTYPE ) )*
$ CLARND( 4, ISEED )
B( JR, JC ) = RMAGN( KBMAGN( JTYPE ) )*
$ CLARND( 4, ISEED )
70 CONTINUE
80 CONTINUE
END IF
*
90 CONTINUE
*
IF( IERR.NE.0 ) THEN
WRITE( NOUNIT, FMT = 9999 )'Generator', IERR, N, JTYPE,
$ IOLDSD
INFO = ABS( IERR )
RETURN
END IF
*
100 CONTINUE
*
DO 110 I = 1, 7
RESULT( I ) = -ONE
110 CONTINUE
*
* Call CGGEV to compute eigenvalues and eigenvectors.
*
CALL CLACPY( ' ', N, N, A, LDA, S, LDA )
CALL CLACPY( ' ', N, N, B, LDA, T, LDA )
CALL CGGEV( 'V', 'V', N, S, LDA, T, LDA, ALPHA, BETA, Q,
$ LDQ, Z, LDQ, WORK, LWORK, RWORK, IERR )
IF( IERR.NE.0 .AND. IERR.NE.N+1 ) THEN
RESULT( 1 ) = ULPINV
WRITE( NOUNIT, FMT = 9999 )'CGGEV1', IERR, N, JTYPE,
$ IOLDSD
INFO = ABS( IERR )
GO TO 190
END IF
*
* Do the tests (1) and (2)
*
CALL CGET52( .TRUE., N, A, LDA, B, LDA, Q, LDQ, ALPHA, BETA,
$ WORK, RWORK, RESULT( 1 ) )
IF( RESULT( 2 ).GT.THRESH ) THEN
WRITE( NOUNIT, FMT = 9998 )'Left', 'CGGEV1',
$ RESULT( 2 ), N, JTYPE, IOLDSD
END IF
*
* Do the tests (3) and (4)
*
CALL CGET52( .FALSE., N, A, LDA, B, LDA, Z, LDQ, ALPHA,
$ BETA, WORK, RWORK, RESULT( 3 ) )
IF( RESULT( 4 ).GT.THRESH ) THEN
WRITE( NOUNIT, FMT = 9998 )'Right', 'CGGEV1',
$ RESULT( 4 ), N, JTYPE, IOLDSD
END IF
*
* Do test (5)
*
CALL CLACPY( ' ', N, N, A, LDA, S, LDA )
CALL CLACPY( ' ', N, N, B, LDA, T, LDA )
CALL CGGEV( 'N', 'N', N, S, LDA, T, LDA, ALPHA1, BETA1, Q,
$ LDQ, Z, LDQ, WORK, LWORK, RWORK, IERR )
IF( IERR.NE.0 .AND. IERR.NE.N+1 ) THEN
RESULT( 1 ) = ULPINV
WRITE( NOUNIT, FMT = 9999 )'CGGEV2', IERR, N, JTYPE,
$ IOLDSD
INFO = ABS( IERR )
GO TO 190
END IF
*
DO 120 J = 1, N
IF( ALPHA( J ).NE.ALPHA1( J ) .OR. BETA( J ).NE.
$ BETA1( J ) )RESULT( 5 ) = ULPINV
120 CONTINUE
*
* Do test (6): Compute eigenvalues and left eigenvectors,
* and test them
*
CALL CLACPY( ' ', N, N, A, LDA, S, LDA )
CALL CLACPY( ' ', N, N, B, LDA, T, LDA )
CALL CGGEV( 'V', 'N', N, S, LDA, T, LDA, ALPHA1, BETA1, QE,
$ LDQE, Z, LDQ, WORK, LWORK, RWORK, IERR )
IF( IERR.NE.0 .AND. IERR.NE.N+1 ) THEN
RESULT( 1 ) = ULPINV
WRITE( NOUNIT, FMT = 9999 )'CGGEV3', IERR, N, JTYPE,
$ IOLDSD
INFO = ABS( IERR )
GO TO 190
END IF
*
DO 130 J = 1, N
IF( ALPHA( J ).NE.ALPHA1( J ) .OR. BETA( J ).NE.
$ BETA1( J ) )RESULT( 6 ) = ULPINV
130 CONTINUE
*
DO 150 J = 1, N
DO 140 JC = 1, N
IF( Q( J, JC ).NE.QE( J, JC ) )
$ RESULT( 6 ) = ULPINV
140 CONTINUE
150 CONTINUE
*
* Do test (7): Compute eigenvalues and right eigenvectors,
* and test them
*
CALL CLACPY( ' ', N, N, A, LDA, S, LDA )
CALL CLACPY( ' ', N, N, B, LDA, T, LDA )
CALL CGGEV( 'N', 'V', N, S, LDA, T, LDA, ALPHA1, BETA1, Q,
$ LDQ, QE, LDQE, WORK, LWORK, RWORK, IERR )
IF( IERR.NE.0 .AND. IERR.NE.N+1 ) THEN
RESULT( 1 ) = ULPINV
WRITE( NOUNIT, FMT = 9999 )'CGGEV4', IERR, N, JTYPE,
$ IOLDSD
INFO = ABS( IERR )
GO TO 190
END IF
*
DO 160 J = 1, N
IF( ALPHA( J ).NE.ALPHA1( J ) .OR. BETA( J ).NE.
$ BETA1( J ) )RESULT( 7 ) = ULPINV
160 CONTINUE
*
DO 180 J = 1, N
DO 170 JC = 1, N
IF( Z( J, JC ).NE.QE( J, JC ) )
$ RESULT( 7 ) = ULPINV
170 CONTINUE
180 CONTINUE
*
* End of Loop -- Check for RESULT(j) > THRESH
*
190 CONTINUE
*
NTESTT = NTESTT + 7
*
* Print out tests which fail.
*
DO 200 JR = 1, 7
IF( RESULT( JR ).GE.THRESH ) THEN
*
* If this is the first test to fail,
* print a header to the data file.
*
IF( NERRS.EQ.0 ) THEN
WRITE( NOUNIT, FMT = 9997 )'CGV'
*
* Matrix types
*
WRITE( NOUNIT, FMT = 9996 )
WRITE( NOUNIT, FMT = 9995 )
WRITE( NOUNIT, FMT = 9994 )'Orthogonal'
*
* Tests performed
*
WRITE( NOUNIT, FMT = 9993 )
*
END IF
NERRS = NERRS + 1
IF( RESULT( JR ).LT.10000.0 ) THEN
WRITE( NOUNIT, FMT = 9992 )N, JTYPE, IOLDSD, JR,
$ RESULT( JR )
ELSE
WRITE( NOUNIT, FMT = 9991 )N, JTYPE, IOLDSD, JR,
$ RESULT( JR )
END IF
END IF
200 CONTINUE
*
210 CONTINUE
220 CONTINUE
*
* Summary
*
CALL ALASVM( 'CGV', NOUNIT, NERRS, NTESTT, 0 )
*
WORK( 1 ) = MAXWRK
*
RETURN
*
9999 FORMAT( ' CDRGEV: ', A, ' returned INFO=', I6, '.', / 3X, 'N=',
$ I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, ')' )
*
9998 FORMAT( ' CDRGEV: ', A, ' Eigenvectors from ', A, ' incorrectly ',
$ 'normalized.', / ' Bits of error=', 0P, G10.3, ',', 3X,
$ 'N=', I4, ', JTYPE=', I3, ', ISEED=(', 3( I4, ',' ), I5,
$ ')' )
*
9997 FORMAT( / 1X, A3, ' -- Complex Generalized eigenvalue problem ',
$ 'driver' )
*
9996 FORMAT( ' Matrix types (see CDRGEV for details): ' )
*
9995 FORMAT( ' Special Matrices:', 23X,
$ '(J''=transposed Jordan block)',
$ / ' 1=(0,0) 2=(I,0) 3=(0,I) 4=(I,I) 5=(J'',J'') ',
$ '6=(diag(J'',I), diag(I,J''))', / ' Diagonal Matrices: ( ',
$ 'D=diag(0,1,2,...) )', / ' 7=(D,I) 9=(large*D, small*I',
$ ') 11=(large*I, small*D) 13=(large*D, large*I)', /
$ ' 8=(I,D) 10=(small*D, large*I) 12=(small*I, large*D) ',
$ ' 14=(small*D, small*I)', / ' 15=(D, reversed D)' )
9994 FORMAT( ' Matrices Rotated by Random ', A, ' Matrices U, V:',
$ / ' 16=Transposed Jordan Blocks 19=geometric ',
$ 'alpha, beta=0,1', / ' 17=arithm. alpha&beta ',
$ ' 20=arithmetic alpha, beta=0,1', / ' 18=clustered ',
$ 'alpha, beta=0,1 21=random alpha, beta=0,1',
$ / ' Large & Small Matrices:', / ' 22=(large, small) ',
$ '23=(small,large) 24=(small,small) 25=(large,large)',
$ / ' 26=random O(1) matrices.' )
*
9993 FORMAT( / ' Tests performed: ',
$ / ' 1 = max | ( b A - a B )''*l | / const.,',
$ / ' 2 = | |VR(i)| - 1 | / ulp,',
$ / ' 3 = max | ( b A - a B )*r | / const.',
$ / ' 4 = | |VL(i)| - 1 | / ulp,',
$ / ' 5 = 0 if W same no matter if r or l computed,',
$ / ' 6 = 0 if l same no matter if l computed,',
$ / ' 7 = 0 if r same no matter if r computed,', / 1X )
9992 FORMAT( ' Matrix order=', I5, ', type=', I2, ', seed=',
$ 4( I4, ',' ), ' result ', I2, ' is', 0P, F8.2 )
9991 FORMAT( ' Matrix order=', I5, ', type=', I2, ', seed=',
$ 4( I4, ',' ), ' result ', I2, ' is', 1P, E10.3 )
*
* End of CDRGEV
*
END