*> \brief \b CDRVGG * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * * Definition: * =========== * * SUBROUTINE CDRVGG( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH, * THRSHN, NOUNIT, A, LDA, B, S, T, S2, T2, Q, * LDQ, Z, ALPHA1, BETA1, ALPHA2, BETA2, VL, VR, * WORK, LWORK, RWORK, RESULT, INFO ) * * .. Scalar Arguments .. * INTEGER INFO, LDA, LDQ, LWORK, NOUNIT, NSIZES, NTYPES * REAL THRESH, THRSHN * .. * .. Array Arguments .. * * *> \par Purpose: * ============= *> *> \verbatim *> *> CDRVGG checks the nonsymmetric generalized eigenvalue driver *> routines. *> T T T *> CGEGS factors A and B as Q S Z and Q T Z , where means *> transpose, T is upper triangular, S is in generalized Schur form *> (upper triangular), and Q and Z are unitary. It also *> computes the generalized eigenvalues (alpha(1),beta(1)), ..., *> (alpha(n),beta(n)), where alpha(j)=S(j,j) and beta(j)=T(j,j) -- *> thus, w(j) = alpha(j)/beta(j) is a root of the generalized *> eigenvalue problem *> *> det( A - w(j) B ) = 0 *> *> and m(j) = beta(j)/alpha(j) is a root of the essentially equivalent *> problem *> *> det( m(j) A - B ) = 0 *> *> CGEGV computes the generalized eigenvalues (alpha(1),beta(1)), ..., *> (alpha(n),beta(n)), the matrix L whose columns contain the *> generalized left eigenvectors l, and the matrix R whose columns *> contain the generalized right eigenvectors r for the pair (A,B). *> *> When CDRVGG 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, one matrix will be generated and used *> to test the nonsymmetric eigenroutines. For each matrix, 7 *> tests will be performed and compared with the threshhold THRESH: *> *> Results from CGEGS: *> *> H *> (1) | A - Q S Z | / ( |A| n ulp ) *> *> H *> (2) | B - Q T Z | / ( |B| n ulp ) *> *> H *> (3) | I - QQ | / ( n ulp ) *> *> H *> (4) | I - ZZ | / ( n ulp ) *> *> (5) maximum over j of D(j) where: *> *> |alpha(j) - S(j,j)| |beta(j) - T(j,j)| *> D(j) = ------------------------ + ----------------------- *> max(|alpha(j)|,|S(j,j)|) max(|beta(j)|,|T(j,j)|) *> *> Results from CGEGV: *> *> (6) max over all left eigenvalue/-vector pairs (beta/alpha,l) of *> *> | l**H * (beta A - alpha B) | / ( ulp max( |beta A|, |alpha B| ) ) *> *> where l**H is the conjugate tranpose of l. *> *> (7) max over all right eigenvalue/-vector pairs (beta/alpha,r) of *> *> | (beta A - alpha B) r | / ( ulp max( |beta A|, |alpha B| ) ) *> *> 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 unitary 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, *> CDRVGG does nothing. It must be at least zero. *> \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. The values must be at least *> zero. *> \endverbatim *> *> \param[in] NTYPES *> \verbatim *> NTYPES is INTEGER *> The number of elements in DOTYPE. If it is zero, CDRVGG *> 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 CDRVGG 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] THRSHN *> \verbatim *> THRSHN is REAL *> Threshhold for reporting eigenvector normalization error. *> If the normalization of any eigenvector differs from 1 by *> more than THRSHN*ulp, then a special error message will be *> printed. (This is handled separately from the other tests, *> since only a compiler or programming error should cause an *> error message, at least if THRSHN is at least 5--10.) *> \endverbatim *> *> \param[in] NOUNIT *> \verbatim *> NOUNIT is INTEGER *> The FORTRAN unit number for printing out error messages *> (e.g., if a routine returns IINFO 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, T, S2, and T2. *> 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 upper triangular matrix computed from A by CGEGS. *> \endverbatim *> *> \param[out] T *> \verbatim *> T is COMPLEX array, dimension (LDA, max(NN)) *> The upper triangular matrix computed from B by CGEGS. *> \endverbatim *> *> \param[out] S2 *> \verbatim *> S2 is COMPLEX array, dimension (LDA, max(NN)) *> The matrix computed from A by CGEGV. This will be the *> Schur (upper triangular) form of some matrix related to A, *> but will not, in general, be the same as S. *> \endverbatim *> *> \param[out] T2 *> \verbatim *> T2 is COMPLEX array, dimension (LDA, max(NN)) *> The matrix computed from B by CGEGV. This will be the *> Schur form of some matrix related to B, but will not, in *> general, be the same as T. *> \endverbatim *> *> \param[out] Q *> \verbatim *> Q is COMPLEX array, dimension (LDQ, max(NN)) *> The (left) unitary matrix computed by CGEGS. *> \endverbatim *> *> \param[in] LDQ *> \verbatim *> LDQ is INTEGER *> The leading dimension of Q, Z, VL, and VR. 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) unitary matrix computed by CGEGS. *> \endverbatim *> *> \param[out] ALPHA1 *> \verbatim *> ALPHA1 is COMPLEX array, dimension (max(NN)) *> \endverbatim *> *> \param[out] BETA1 *> \verbatim *> BETA1 is COMPLEX array, dimension (max(NN)) *> *> The generalized eigenvalues of (A,B) computed by CGEGS. *> ALPHA1(k) / BETA1(k) is the k-th generalized eigenvalue of *> the matrices in A and B. *> \endverbatim *> *> \param[out] ALPHA2 *> \verbatim *> ALPHA2 is COMPLEX array, dimension (max(NN)) *> \endverbatim *> *> \param[out] BETA2 *> \verbatim *> BETA2 is COMPLEX array, dimension (max(NN)) *> *> The generalized eigenvalues of (A,B) computed by CGEGV. *> ALPHA2(k) / BETA2(k) is the k-th generalized eigenvalue of *> the matrices in A and B. *> \endverbatim *> *> \param[out] VL *> \verbatim *> VL is COMPLEX array, dimension (LDQ, max(NN)) *> The (lower triangular) left eigenvector matrix for the *> matrices in A and B. *> \endverbatim *> *> \param[out] VR *> \verbatim *> VR is COMPLEX array, dimension (LDQ, max(NN)) *> The (upper triangular) right eigenvector matrix for the *> matrices in A and B. *> \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. This must be at least *> MAX( 2*N, N*(NB+1), (k+1)*(2*k+N+1) ), where "k" is the *> sum of the blocksize and number-of-shifts for CHGEQZ, and *> NB is the greatest of the blocksizes for CGEQRF, CUNMQR, *> and CUNGQR. (The blocksizes and the number-of-shifts are *> retrieved through calls to ILAENV.) *> \endverbatim *> *> \param[out] RWORK *> \verbatim *> RWORK is REAL array, dimension (8*N) *> \endverbatim *> *> \param[out] RESULT *> \verbatim *> RESULT is REAL array, dimension (7) *> 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 November 2011 * *> \ingroup complex_eig * * ===================================================================== SUBROUTINE CDRVGG( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH, $ THRSHN, NOUNIT, A, LDA, B, S, T, S2, T2, Q, $ LDQ, Z, ALPHA1, BETA1, ALPHA2, BETA2, VL, VR, $ WORK, LWORK, RWORK, RESULT, INFO ) * * -- LAPACK test routine (version 3.4.0) -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * November 2011 * * .. Scalar Arguments .. INTEGER INFO, LDA, LDQ, LWORK, NOUNIT, NSIZES, NTYPES REAL THRESH, THRSHN * .. * .. Array Arguments .. * * ===================================================================== * LOGICAL DOTYPE( * ) INTEGER ISEED( 4 ), NN( * ) REAL RESULT( * ), RWORK( * ) COMPLEX A( LDA, * ), ALPHA1( * ), ALPHA2( * ), $ B( LDA, * ), BETA1( * ), BETA2( * ), $ Q( LDQ, * ), S( LDA, * ), S2( LDA, * ), $ T( LDA, * ), T2( LDA, * ), VL( LDQ, * ), $ VR( LDQ, * ), 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 I1, IADD, IINFO, IN, J, JC, JR, JSIZE, JTYPE, $ LWKOPT, MTYPES, N, N1, NB, NBZ, NERRS, NMATS, $ NMAX, NS, NTEST, NTESTT REAL SAFMAX, SAFMIN, TEMP1, TEMP2, ULP, ULPINV COMPLEX CTEMP, X * .. * .. 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 DUMMA( 4 ), RMAGN( 0: 3 ) * .. * .. External Functions .. INTEGER ILAENV REAL SLAMCH COMPLEX CLARND EXTERNAL ILAENV, SLAMCH, CLARND * .. * .. External Subroutines .. EXTERNAL ALASVM, CGEGS, CGEGV, CGET51, CGET52, CLACPY, $ CLARFG, CLASET, CLATM4, CUNM2R, SLABAD, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, AIMAG, CONJG, MAX, MIN, REAL, SIGN * .. * .. Statement Functions .. REAL ABS1 * .. * .. Statement Function definitions .. ABS1( X ) = ABS( REAL( X ) ) + ABS( AIMAG( X ) ) * .. * .. 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 * * Maximum blocksize and shift -- we assume that blocksize and number * of shifts are monotone increasing functions of N. * 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 ) ) NBZ = ILAENV( 1, 'CHGEQZ', 'SII', NMAX, 1, NMAX, 0 ) NS = ILAENV( 4, 'CHGEQZ', 'SII', NMAX, 1, NMAX, 0 ) I1 = NBZ + NS LWKOPT = MAX( 2*NMAX, NMAX*( NB+1 ), ( 2*I1+NMAX+1 )*( I1+1 ) ) * * Check for errors * 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 = -10 ELSE IF( LDQ.LE.1 .OR. LDQ.LT.NMAX ) THEN INFO = -19 ELSE IF( LWKOPT.GT.LWORK ) THEN INFO = -30 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'CDRVGG', -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 160 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 150 JTYPE = 1, MTYPES IF( .NOT.DOTYPE( JTYPE ) ) $ GO TO 150 NMATS = NMATS + 1 NTEST = 0 * * Save ISEED in case of an error. * DO 20 J = 1, 4 IOLDSD( J ) = ISEED( J ) 20 CONTINUE * * Initialize RESULT * DO 30 J = 1, 7 RESULT( J ) = ZERO 30 CONTINUE * * Compute 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, IBSIGN: 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 110 IINFO = 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 50 JC = 1, N - 1 DO 40 JR = JC, N Q( JR, JC ) = CLARND( 3, ISEED ) Z( JR, JC ) = CLARND( 3, ISEED ) 40 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 50 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 70 JC = 1, N DO 60 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 ) 60 CONTINUE 70 CONTINUE CALL CUNM2R( 'L', 'N', N, N, N-1, Q, LDQ, WORK, A, $ LDA, WORK( 2*N+1 ), IINFO ) IF( IINFO.NE.0 ) $ GO TO 100 CALL CUNM2R( 'R', 'C', N, N, N-1, Z, LDQ, WORK( N+1 ), $ A, LDA, WORK( 2*N+1 ), IINFO ) IF( IINFO.NE.0 ) $ GO TO 100 CALL CUNM2R( 'L', 'N', N, N, N-1, Q, LDQ, WORK, B, $ LDA, WORK( 2*N+1 ), IINFO ) IF( IINFO.NE.0 ) $ GO TO 100 CALL CUNM2R( 'R', 'C', N, N, N-1, Z, LDQ, WORK( N+1 ), $ B, LDA, WORK( 2*N+1 ), IINFO ) IF( IINFO.NE.0 ) $ GO TO 100 END IF ELSE * * Random matrices * DO 90 JC = 1, N DO 80 JR = 1, N A( JR, JC ) = RMAGN( KAMAGN( JTYPE ) )* $ CLARND( 4, ISEED ) B( JR, JC ) = RMAGN( KBMAGN( JTYPE ) )* $ CLARND( 4, ISEED ) 80 CONTINUE 90 CONTINUE END IF * 100 CONTINUE * IF( IINFO.NE.0 ) THEN WRITE( NOUNIT, FMT = 9999 )'Generator', IINFO, N, JTYPE, $ IOLDSD INFO = ABS( IINFO ) RETURN END IF * 110 CONTINUE * * Call CGEGS to compute H, T, Q, Z, alpha, and beta. * CALL CLACPY( ' ', N, N, A, LDA, S, LDA ) CALL CLACPY( ' ', N, N, B, LDA, T, LDA ) NTEST = 1 RESULT( 1 ) = ULPINV * CALL CGEGS( 'V', 'V', N, S, LDA, T, LDA, ALPHA1, BETA1, Q, $ LDQ, Z, LDQ, WORK, LWORK, RWORK, IINFO ) IF( IINFO.NE.0 ) THEN WRITE( NOUNIT, FMT = 9999 )'CGEGS', IINFO, N, JTYPE, $ IOLDSD INFO = ABS( IINFO ) GO TO 130 END IF * NTEST = 4 * * Do tests 1--4 * CALL CGET51( 1, N, A, LDA, S, LDA, Q, LDQ, Z, LDQ, WORK, $ RWORK, RESULT( 1 ) ) CALL CGET51( 1, N, B, LDA, T, LDA, Q, LDQ, Z, LDQ, WORK, $ RWORK, RESULT( 2 ) ) CALL CGET51( 3, N, B, LDA, T, LDA, Q, LDQ, Q, LDQ, WORK, $ RWORK, RESULT( 3 ) ) CALL CGET51( 3, N, B, LDA, T, LDA, Z, LDQ, Z, LDQ, WORK, $ RWORK, RESULT( 4 ) ) * * Do test 5: compare eigenvalues with diagonals. * TEMP1 = ZERO * DO 120 J = 1, N TEMP2 = ( ABS1( ALPHA1( J )-S( J, J ) ) / $ MAX( SAFMIN, ABS1( ALPHA1( J ) ), ABS1( S( J, $ J ) ) )+ABS1( BETA1( J )-T( J, J ) ) / $ MAX( SAFMIN, ABS1( BETA1( J ) ), ABS1( T( J, $ J ) ) ) ) / ULP TEMP1 = MAX( TEMP1, TEMP2 ) 120 CONTINUE RESULT( 5 ) = TEMP1 * * Call CGEGV to compute S2, T2, VL, and VR, do tests. * * Eigenvalues and Eigenvectors * CALL CLACPY( ' ', N, N, A, LDA, S2, LDA ) CALL CLACPY( ' ', N, N, B, LDA, T2, LDA ) NTEST = 6 RESULT( 6 ) = ULPINV * CALL CGEGV( 'V', 'V', N, S2, LDA, T2, LDA, ALPHA2, BETA2, $ VL, LDQ, VR, LDQ, WORK, LWORK, RWORK, IINFO ) IF( IINFO.NE.0 ) THEN WRITE( NOUNIT, FMT = 9999 )'CGEGV', IINFO, N, JTYPE, $ IOLDSD INFO = ABS( IINFO ) GO TO 130 END IF * NTEST = 7 * * Do Tests 6 and 7 * CALL CGET52( .TRUE., N, A, LDA, B, LDA, VL, LDQ, ALPHA2, $ BETA2, WORK, RWORK, DUMMA( 1 ) ) RESULT( 6 ) = DUMMA( 1 ) IF( DUMMA( 2 ).GT.THRSHN ) THEN WRITE( NOUNIT, FMT = 9998 )'Left', 'CGEGV', DUMMA( 2 ), $ N, JTYPE, IOLDSD END IF * CALL CGET52( .FALSE., N, A, LDA, B, LDA, VR, LDQ, ALPHA2, $ BETA2, WORK, RWORK, DUMMA( 1 ) ) RESULT( 7 ) = DUMMA( 1 ) IF( DUMMA( 2 ).GT.THRESH ) THEN WRITE( NOUNIT, FMT = 9998 )'Right', 'CGEGV', DUMMA( 2 ), $ N, JTYPE, IOLDSD END IF * * End of Loop -- Check for RESULT(j) > THRESH * 130 CONTINUE * NTESTT = NTESTT + NTEST * * Print out tests which fail. * DO 140 JR = 1, NTEST 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 )'CGG' * * Matrix types * WRITE( NOUNIT, FMT = 9996 ) WRITE( NOUNIT, FMT = 9995 ) WRITE( NOUNIT, FMT = 9994 )'Unitary' * * Tests performed * WRITE( NOUNIT, FMT = 9993 )'unitary', '*', $ 'conjugate transpose', ( '*', J = 1, 5 ) * 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 140 CONTINUE * 150 CONTINUE 160 CONTINUE * * Summary * CALL ALASVM( 'CGG', NOUNIT, NERRS, NTESTT, 0 ) RETURN * 9999 FORMAT( ' CDRVGG: ', A, ' returned INFO=', I6, '.', / 9X, 'N=', $ I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, ')' ) * 9998 FORMAT( ' CDRVGG: ', A, ' Eigenvectors from ', A, ' incorrectly ', $ 'normalized.', / ' Bits of error=', 0P, G10.3, ',', 9X, $ 'N=', I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, $ ')' ) * 9997 FORMAT( / 1X, A3, $ ' -- Complex Generalized eigenvalue problem driver' ) * 9996 FORMAT( ' Matrix types (see CDRVGG 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: (S is Schur, T is triangular, ', $ 'Q and Z are ', A, ',', / 20X, $ 'l and r are the appropriate left and right', / 19X, $ 'eigenvectors, resp., a is alpha, b is beta, and', / 19X, A, $ ' means ', A, '.)', / ' 1 = | A - Q S Z', A, $ ' | / ( |A| n ulp ) 2 = | B - Q T Z', A, $ ' | / ( |B| n ulp )', / ' 3 = | I - QQ', A, $ ' | / ( n ulp ) 4 = | I - ZZ', A, $ ' | / ( n ulp )', / $ ' 5 = difference between (alpha,beta) and diagonals of', $ ' (S,T)', / ' 6 = max | ( b A - a B )', A, $ ' l | / const. 7 = max | ( b A - a B ) r | / const.', $ / 1X ) 9992 FORMAT( ' Matrix order=', I5, ', type=', I2, ', seed=', $ 4( I4, ',' ), ' result ', I3, ' is', 0P, F8.2 ) 9991 FORMAT( ' Matrix order=', I5, ', type=', I2, ', seed=', $ 4( I4, ',' ), ' result ', I3, ' is', 1P, E10.3 ) * * End of CDRVGG * END