*> \brief \b CDRVSX * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * * Definition: * =========== * * SUBROUTINE CDRVSX( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH, * NIUNIT, NOUNIT, A, LDA, H, HT, W, WT, WTMP, VS, * LDVS, VS1, RESULT, WORK, LWORK, RWORK, BWORK, * INFO ) * * .. Scalar Arguments .. * INTEGER INFO, LDA, LDVS, LWORK, NIUNIT, NOUNIT, NSIZES, * $ NTYPES * REAL THRESH * .. * .. Array Arguments .. * LOGICAL BWORK( * ), DOTYPE( * ) * INTEGER ISEED( 4 ), NN( * ) * REAL RESULT( 17 ), RWORK( * ) * COMPLEX A( LDA, * ), H( LDA, * ), HT( LDA, * ), * $ VS( LDVS, * ), VS1( LDVS, * ), W( * ), * $ WORK( * ), WT( * ), WTMP( * ) * .. * * *> \par Purpose: * ============= *> *> \verbatim *> *> CDRVSX checks the nonsymmetric eigenvalue (Schur form) problem *> expert driver CGEESX. *> *> CDRVSX uses both test matrices generated randomly depending on *> data supplied in the calling sequence, as well as on data *> read from an input file and including precomputed condition *> numbers to which it compares the ones it computes. *> *> When CDRVSX 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, 15 *> tests will be performed: *> *> (1) 0 if T is in Schur form, 1/ulp otherwise *> (no sorting of eigenvalues) *> *> (2) | A - VS T VS' | / ( n |A| ulp ) *> *> Here VS is the matrix of Schur eigenvectors, and T is in Schur *> form (no sorting of eigenvalues). *> *> (3) | I - VS VS' | / ( n ulp ) (no sorting of eigenvalues). *> *> (4) 0 if W are eigenvalues of T *> 1/ulp otherwise *> (no sorting of eigenvalues) *> *> (5) 0 if T(with VS) = T(without VS), *> 1/ulp otherwise *> (no sorting of eigenvalues) *> *> (6) 0 if eigenvalues(with VS) = eigenvalues(without VS), *> 1/ulp otherwise *> (no sorting of eigenvalues) *> *> (7) 0 if T is in Schur form, 1/ulp otherwise *> (with sorting of eigenvalues) *> *> (8) | A - VS T VS' | / ( n |A| ulp ) *> *> Here VS is the matrix of Schur eigenvectors, and T is in Schur *> form (with sorting of eigenvalues). *> *> (9) | I - VS VS' | / ( n ulp ) (with sorting of eigenvalues). *> *> (10) 0 if W are eigenvalues of T *> 1/ulp otherwise *> If workspace sufficient, also compare W with and *> without reciprocal condition numbers *> (with sorting of eigenvalues) *> *> (11) 0 if T(with VS) = T(without VS), *> 1/ulp otherwise *> If workspace sufficient, also compare T with and without *> reciprocal condition numbers *> (with sorting of eigenvalues) *> *> (12) 0 if eigenvalues(with VS) = eigenvalues(without VS), *> 1/ulp otherwise *> If workspace sufficient, also compare VS with and without *> reciprocal condition numbers *> (with sorting of eigenvalues) *> *> (13) if sorting worked and SDIM is the number of *> eigenvalues which were SELECTed *> If workspace sufficient, also compare SDIM with and *> without reciprocal condition numbers *> *> (14) if RCONDE the same no matter if VS and/or RCONDV computed *> *> (15) if RCONDV the same no matter if VS and/or RCONDE computed *> *> The "sizes" 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) The zero matrix. *> (2) The identity matrix. *> (3) A (transposed) Jordan block, with 1's on the diagonal. *> *> (4) A diagonal matrix with evenly spaced entries *> 1, ..., ULP and random complex angles. *> (ULP = (first number larger than 1) - 1 ) *> (5) A diagonal matrix with geometrically spaced entries *> 1, ..., ULP and random complex angles. *> (6) A diagonal matrix with "clustered" entries 1, ULP, ..., ULP *> and random complex angles. *> *> (7) Same as (4), but multiplied by a constant near *> the overflow threshold *> (8) Same as (4), but multiplied by a constant near *> the underflow threshold *> *> (9) A matrix of the form U' T U, where U is unitary and *> T has evenly spaced entries 1, ..., ULP with random *> complex angles on the diagonal and random O(1) entries in *> the upper triangle. *> *> (10) A matrix of the form U' T U, where U is unitary and *> T has geometrically spaced entries 1, ..., ULP with random *> complex angles on the diagonal and random O(1) entries in *> the upper triangle. *> *> (11) A matrix of the form U' T U, where U is orthogonal and *> T has "clustered" entries 1, ULP,..., ULP with random *> complex angles on the diagonal and random O(1) entries in *> the upper triangle. *> *> (12) A matrix of the form U' T U, where U is unitary and *> T has complex eigenvalues randomly chosen from *> ULP < |z| < 1 and random O(1) entries in the upper *> triangle. *> *> (13) A matrix of the form X' T X, where X has condition *> SQRT( ULP ) and T has evenly spaced entries 1, ..., ULP *> with random complex angles on the diagonal and random O(1) *> entries in the upper triangle. *> *> (14) A matrix of the form X' T X, where X has condition *> SQRT( ULP ) and T has geometrically spaced entries *> 1, ..., ULP with random complex angles on the diagonal *> and random O(1) entries in the upper triangle. *> *> (15) A matrix of the form X' T X, where X has condition *> SQRT( ULP ) and T has "clustered" entries 1, ULP,..., ULP *> with random complex angles on the diagonal and random O(1) *> entries in the upper triangle. *> *> (16) A matrix of the form X' T X, where X has condition *> SQRT( ULP ) and T has complex eigenvalues randomly chosen *> from ULP < |z| < 1 and random O(1) entries in the upper *> triangle. *> *> (17) Same as (16), but multiplied by a constant *> near the overflow threshold *> (18) Same as (16), but multiplied by a constant *> near the underflow threshold *> *> (19) Nonsymmetric matrix with random entries chosen from (-1,1). *> If N is at least 4, all entries in first two rows and last *> row, and first column and last two columns are zero. *> (20) Same as (19), but multiplied by a constant *> near the overflow threshold *> (21) Same as (19), but multiplied by a constant *> near the underflow threshold *> *> In addition, an input file will be read from logical unit number *> NIUNIT. The file contains matrices along with precomputed *> eigenvalues and reciprocal condition numbers for the eigenvalue *> average and right invariant subspace. For these matrices, in *> addition to tests (1) to (15) we will compute the following two *> tests: *> *> (16) |RCONDE - RCDEIN| / cond(RCONDE) *> *> RCONDE is the reciprocal average eigenvalue condition number *> computed by CGEESX and RCDEIN (the precomputed true value) *> is supplied as input. cond(RCONDE) is the condition number *> of RCONDE, and takes errors in computing RCONDE into account, *> so that the resulting quantity should be O(ULP). cond(RCONDE) *> is essentially given by norm(A)/RCONDV. *> *> (17) |RCONDV - RCDVIN| / cond(RCONDV) *> *> RCONDV is the reciprocal right invariant subspace condition *> number computed by CGEESX and RCDVIN (the precomputed true *> value) is supplied as input. cond(RCONDV) is the condition *> number of RCONDV, and takes errors in computing RCONDV into *> account, so that the resulting quantity should be O(ULP). *> cond(RCONDV) is essentially given by norm(A)/RCONDE. *> \endverbatim * * Arguments: * ========== * *> \param[in] NSIZES *> \verbatim *> NSIZES is INTEGER *> The number of sizes of matrices to use. NSIZES must be at *> least zero. If it is zero, no randomly generated matrices *> are tested, but any test matrices read from NIUNIT will be *> tested. *> \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. NTYPES must be at least *> zero. If it is zero, no randomly generated test matrices *> are tested, but and test matrices read from NIUNIT will be *> tested. 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 CDRVSX 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] NIUNIT *> \verbatim *> NIUNIT is INTEGER *> The FORTRAN unit number for reading in the data file of *> problems to solve. *> \endverbatim *> *> \param[in] NOUNIT *> \verbatim *> NOUNIT is INTEGER *> The FORTRAN unit number for printing out error messages *> (e.g., if a routine returns INFO not equal to 0.) *> \endverbatim *> *> \param[out] A *> \verbatim *> A is COMPLEX array, dimension (LDA, max(NN)) *> Used to hold the matrix whose eigenvalues are to be *> computed. On exit, A contains the last matrix actually used. *> \endverbatim *> *> \param[in] LDA *> \verbatim *> LDA is INTEGER *> The leading dimension of A, and H. LDA must be at *> least 1 and at least max( NN ). *> \endverbatim *> *> \param[out] H *> \verbatim *> H is COMPLEX array, dimension (LDA, max(NN)) *> Another copy of the test matrix A, modified by CGEESX. *> \endverbatim *> *> \param[out] HT *> \verbatim *> HT is COMPLEX array, dimension (LDA, max(NN)) *> Yet another copy of the test matrix A, modified by CGEESX. *> \endverbatim *> *> \param[out] W *> \verbatim *> W is COMPLEX array, dimension (max(NN)) *> The computed eigenvalues of A. *> \endverbatim *> *> \param[out] WT *> \verbatim *> WT is COMPLEX array, dimension (max(NN)) *> Like W, this array contains the eigenvalues of A, *> but those computed when CGEESX only computes a partial *> eigendecomposition, i.e. not Schur vectors *> \endverbatim *> *> \param[out] WTMP *> \verbatim *> WTMP is COMPLEX array, dimension (max(NN)) *> More temporary storage for eigenvalues. *> \endverbatim *> *> \param[out] VS *> \verbatim *> VS is COMPLEX array, dimension (LDVS, max(NN)) *> VS holds the computed Schur vectors. *> \endverbatim *> *> \param[in] LDVS *> \verbatim *> LDVS is INTEGER *> Leading dimension of VS. Must be at least max(1,max(NN)). *> \endverbatim *> *> \param[out] VS1 *> \verbatim *> VS1 is COMPLEX array, dimension (LDVS, max(NN)) *> VS1 holds another copy of the computed Schur vectors. *> \endverbatim *> *> \param[out] RESULT *> \verbatim *> RESULT is REAL array, dimension (17) *> The values computed by the 17 tests described above. *> The values are currently limited to 1/ulp, to avoid overflow. *> \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(1,2*NN(j)**2) for all j. *> \endverbatim *> *> \param[out] RWORK *> \verbatim *> RWORK is REAL array, dimension (max(NN)) *> \endverbatim *> *> \param[out] BWORK *> \verbatim *> BWORK is LOGICAL array, dimension (max(NN)) *> \endverbatim *> *> \param[out] INFO *> \verbatim *> INFO is INTEGER *> If 0, successful exit. *> <0, input parameter -INFO is incorrect *> >0, CLATMR, CLATMS, CLATME or CGET24 returned an error *> code and INFO is its absolute value *> *>----------------------------------------------------------------------- *> *> Some Local Variables and Parameters: *> ---- ----- --------- --- ---------- *> ZERO, ONE Real 0 and 1. *> MAXTYP The number of types defined. *> NMAX Largest value in NN. *> NERRS The number of tests which have exceeded THRESH *> COND, CONDS, *> IMODE Values to be passed to the matrix generators. *> ANORM Norm of A; passed to matrix generators. *> *> OVFL, UNFL Overflow and underflow thresholds. *> ULP, ULPINV Finest relative precision and its inverse. *> RTULP, RTULPI Square roots of the previous 4 values. *> The following four arrays decode JTYPE: *> KTYPE(j) The general type (1-10) for type "j". *> KMODE(j) The MODE value to be passed to the matrix *> generator for type "j". *> KMAGN(j) The order of magnitude ( O(1), *> O(overflow^(1/2) ), O(underflow^(1/2) ) *> KCONDS(j) Selectw whether CONDS is to be 1 or *> 1/sqrt(ulp). (0 means irrelevant.) *> \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 CDRVSX( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH, $ NIUNIT, NOUNIT, A, LDA, H, HT, W, WT, WTMP, VS, $ LDVS, VS1, RESULT, WORK, LWORK, RWORK, BWORK, $ 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, LDVS, LWORK, NIUNIT, NOUNIT, NSIZES, $ NTYPES REAL THRESH * .. * .. Array Arguments .. LOGICAL BWORK( * ), DOTYPE( * ) INTEGER ISEED( 4 ), NN( * ) REAL RESULT( 17 ), RWORK( * ) COMPLEX A( LDA, * ), H( LDA, * ), HT( LDA, * ), $ VS( LDVS, * ), VS1( LDVS, * ), W( * ), $ WORK( * ), WT( * ), WTMP( * ) * .. * * ===================================================================== * * .. Parameters .. COMPLEX CZERO PARAMETER ( CZERO = ( 0.0E+0, 0.0E+0 ) ) COMPLEX CONE PARAMETER ( CONE = ( 1.0E+0, 0.0E+0 ) ) REAL ZERO, ONE PARAMETER ( ZERO = 0.0E+0, ONE = 1.0E+0 ) INTEGER MAXTYP PARAMETER ( MAXTYP = 21 ) * .. * .. Local Scalars .. LOGICAL BADNN CHARACTER*3 PATH INTEGER I, IINFO, IMODE, ISRT, ITYPE, IWK, J, JCOL, $ JSIZE, JTYPE, MTYPES, N, NERRS, NFAIL, $ NMAX, NNWORK, NSLCT, NTEST, NTESTF, NTESTT REAL ANORM, COND, CONDS, OVFL, RCDEIN, RCDVIN, $ RTULP, RTULPI, ULP, ULPINV, UNFL * .. * .. Local Arrays .. INTEGER IDUMMA( 1 ), IOLDSD( 4 ), ISLCT( 20 ), $ KCONDS( MAXTYP ), KMAGN( MAXTYP ), $ KMODE( MAXTYP ), KTYPE( MAXTYP ) * .. * .. Arrays in Common .. LOGICAL SELVAL( 20 ) REAL SELWI( 20 ), SELWR( 20 ) * .. * .. Scalars in Common .. INTEGER SELDIM, SELOPT * .. * .. Common blocks .. COMMON / SSLCT / SELOPT, SELDIM, SELVAL, SELWR, SELWI * .. * .. External Functions .. REAL SLAMCH EXTERNAL SLAMCH * .. * .. External Subroutines .. EXTERNAL CGET24, CLATME, CLATMR, CLATMS, CLASET, SLABAD, $ SLASUM, XERBLA * .. * .. Intrinsic Functions .. INTRINSIC ABS, MAX, MIN, SQRT * .. * .. Data statements .. DATA KTYPE / 1, 2, 3, 5*4, 4*6, 6*6, 3*9 / DATA KMAGN / 3*1, 1, 1, 1, 2, 3, 4*1, 1, 1, 1, 1, 2, $ 3, 1, 2, 3 / DATA KMODE / 3*0, 4, 3, 1, 4, 4, 4, 3, 1, 5, 4, 3, $ 1, 5, 5, 5, 4, 3, 1 / DATA KCONDS / 3*0, 5*0, 4*1, 6*2, 3*0 / * .. * .. Executable Statements .. * PATH( 1: 1 ) = 'Complex precision' PATH( 2: 3 ) = 'SX' * * Check for errors * NTESTT = 0 NTESTF = 0 INFO = 0 * * Important constants * BADNN = .FALSE. * * 8 is the largest dimension in the input file of precomputed * problems * NMAX = 8 DO 10 J = 1, NSIZES NMAX = MAX( NMAX, NN( J ) ) IF( NN( J ).LT.0 ) $ BADNN = .TRUE. 10 CONTINUE * * 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( NIUNIT.LE.0 ) THEN INFO = -7 ELSE IF( NOUNIT.LE.0 ) THEN INFO = -8 ELSE IF( LDA.LT.1 .OR. LDA.LT.NMAX ) THEN INFO = -10 ELSE IF( LDVS.LT.1 .OR. LDVS.LT.NMAX ) THEN INFO = -20 ELSE IF( MAX( 3*NMAX, 2*NMAX**2 ).GT.LWORK ) THEN INFO = -24 END IF * IF( INFO.NE.0 ) THEN CALL XERBLA( 'CDRVSX', -INFO ) RETURN END IF * * If nothing to do check on NIUNIT * IF( NSIZES.EQ.0 .OR. NTYPES.EQ.0 ) $ GO TO 150 * * More Important constants * UNFL = SLAMCH( 'Safe minimum' ) OVFL = ONE / UNFL CALL SLABAD( UNFL, OVFL ) ULP = SLAMCH( 'Precision' ) ULPINV = ONE / ULP RTULP = SQRT( ULP ) RTULPI = ONE / RTULP * * Loop over sizes, types * NERRS = 0 * DO 140 JSIZE = 1, NSIZES N = NN( JSIZE ) IF( NSIZES.NE.1 ) THEN MTYPES = MIN( MAXTYP, NTYPES ) ELSE MTYPES = MIN( MAXTYP+1, NTYPES ) END IF * DO 130 JTYPE = 1, MTYPES IF( .NOT.DOTYPE( JTYPE ) ) $ GO TO 130 * * Save ISEED in case of an error. * DO 20 J = 1, 4 IOLDSD( J ) = ISEED( J ) 20 CONTINUE * * Compute "A" * * Control parameters: * * KMAGN KCONDS KMODE KTYPE * =1 O(1) 1 clustered 1 zero * =2 large large clustered 2 identity * =3 small exponential Jordan * =4 arithmetic diagonal, (w/ eigenvalues) * =5 random log symmetric, w/ eigenvalues * =6 random general, w/ eigenvalues * =7 random diagonal * =8 random symmetric * =9 random general * =10 random triangular * IF( MTYPES.GT.MAXTYP ) $ GO TO 90 * ITYPE = KTYPE( JTYPE ) IMODE = KMODE( JTYPE ) * * Compute norm * GO TO ( 30, 40, 50 )KMAGN( JTYPE ) * 30 CONTINUE ANORM = ONE GO TO 60 * 40 CONTINUE ANORM = OVFL*ULP GO TO 60 * 50 CONTINUE ANORM = UNFL*ULPINV GO TO 60 * 60 CONTINUE * CALL CLASET( 'Full', LDA, N, CZERO, CZERO, A, LDA ) IINFO = 0 COND = ULPINV * * Special Matrices -- Identity & Jordan block * IF( ITYPE.EQ.1 ) THEN * * Zero * IINFO = 0 * ELSE IF( ITYPE.EQ.2 ) THEN * * Identity * DO 70 JCOL = 1, N A( JCOL, JCOL ) = ANORM 70 CONTINUE * ELSE IF( ITYPE.EQ.3 ) THEN * * Jordan Block * DO 80 JCOL = 1, N A( JCOL, JCOL ) = ANORM IF( JCOL.GT.1 ) $ A( JCOL, JCOL-1 ) = CONE 80 CONTINUE * ELSE IF( ITYPE.EQ.4 ) THEN * * Diagonal Matrix, [Eigen]values Specified * CALL CLATMS( N, N, 'S', ISEED, 'H', RWORK, IMODE, COND, $ ANORM, 0, 0, 'N', A, LDA, WORK( N+1 ), $ IINFO ) * ELSE IF( ITYPE.EQ.5 ) THEN * * Symmetric, eigenvalues specified * CALL CLATMS( N, N, 'S', ISEED, 'H', RWORK, IMODE, COND, $ ANORM, N, N, 'N', A, LDA, WORK( N+1 ), $ IINFO ) * ELSE IF( ITYPE.EQ.6 ) THEN * * General, eigenvalues specified * IF( KCONDS( JTYPE ).EQ.1 ) THEN CONDS = ONE ELSE IF( KCONDS( JTYPE ).EQ.2 ) THEN CONDS = RTULPI ELSE CONDS = ZERO END IF * CALL CLATME( N, 'D', ISEED, WORK, IMODE, COND, CONE, $ 'T', 'T', 'T', RWORK, 4, CONDS, N, N, ANORM, $ A, LDA, WORK( 2*N+1 ), IINFO ) * ELSE IF( ITYPE.EQ.7 ) THEN * * Diagonal, random eigenvalues * CALL CLATMR( N, N, 'D', ISEED, 'N', WORK, 6, ONE, CONE, $ 'T', 'N', WORK( N+1 ), 1, ONE, $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, 0, 0, $ ZERO, ANORM, 'NO', A, LDA, IDUMMA, IINFO ) * ELSE IF( ITYPE.EQ.8 ) THEN * * Symmetric, random eigenvalues * CALL CLATMR( N, N, 'D', ISEED, 'H', WORK, 6, ONE, CONE, $ 'T', 'N', WORK( N+1 ), 1, ONE, $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, N, $ ZERO, ANORM, 'NO', A, LDA, IDUMMA, IINFO ) * ELSE IF( ITYPE.EQ.9 ) THEN * * General, random eigenvalues * CALL CLATMR( N, N, 'D', ISEED, 'N', WORK, 6, ONE, CONE, $ 'T', 'N', WORK( N+1 ), 1, ONE, $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, N, $ ZERO, ANORM, 'NO', A, LDA, IDUMMA, IINFO ) IF( N.GE.4 ) THEN CALL CLASET( 'Full', 2, N, CZERO, CZERO, A, LDA ) CALL CLASET( 'Full', N-3, 1, CZERO, CZERO, A( 3, 1 ), $ LDA ) CALL CLASET( 'Full', N-3, 2, CZERO, CZERO, $ A( 3, N-1 ), LDA ) CALL CLASET( 'Full', 1, N, CZERO, CZERO, A( N, 1 ), $ LDA ) END IF * ELSE IF( ITYPE.EQ.10 ) THEN * * Triangular, random eigenvalues * CALL CLATMR( N, N, 'D', ISEED, 'N', WORK, 6, ONE, CONE, $ 'T', 'N', WORK( N+1 ), 1, ONE, $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, 0, $ ZERO, ANORM, 'NO', A, LDA, IDUMMA, IINFO ) * ELSE * IINFO = 1 END IF * IF( IINFO.NE.0 ) THEN WRITE( NOUNIT, FMT = 9991 )'Generator', IINFO, N, JTYPE, $ IOLDSD INFO = ABS( IINFO ) RETURN END IF * 90 CONTINUE * * Test for minimal and generous workspace * DO 120 IWK = 1, 2 IF( IWK.EQ.1 ) THEN NNWORK = 2*N ELSE NNWORK = MAX( 2*N, N*( N+1 ) / 2 ) END IF NNWORK = MAX( NNWORK, 1 ) * CALL CGET24( .FALSE., JTYPE, THRESH, IOLDSD, NOUNIT, N, $ A, LDA, H, HT, W, WT, WTMP, VS, LDVS, VS1, $ RCDEIN, RCDVIN, NSLCT, ISLCT, 0, RESULT, $ WORK, NNWORK, RWORK, BWORK, INFO ) * * Check for RESULT(j) > THRESH * NTEST = 0 NFAIL = 0 DO 100 J = 1, 15 IF( RESULT( J ).GE.ZERO ) $ NTEST = NTEST + 1 IF( RESULT( J ).GE.THRESH ) $ NFAIL = NFAIL + 1 100 CONTINUE * IF( NFAIL.GT.0 ) $ NTESTF = NTESTF + 1 IF( NTESTF.EQ.1 ) THEN WRITE( NOUNIT, FMT = 9999 )PATH WRITE( NOUNIT, FMT = 9998 ) WRITE( NOUNIT, FMT = 9997 ) WRITE( NOUNIT, FMT = 9996 ) WRITE( NOUNIT, FMT = 9995 )THRESH WRITE( NOUNIT, FMT = 9994 ) NTESTF = 2 END IF * DO 110 J = 1, 15 IF( RESULT( J ).GE.THRESH ) THEN WRITE( NOUNIT, FMT = 9993 )N, IWK, IOLDSD, JTYPE, $ J, RESULT( J ) END IF 110 CONTINUE * NERRS = NERRS + NFAIL NTESTT = NTESTT + NTEST * 120 CONTINUE 130 CONTINUE 140 CONTINUE * 150 CONTINUE * * Read in data from file to check accuracy of condition estimation * Read input data until N=0 * JTYPE = 0 160 CONTINUE READ( NIUNIT, FMT = *, END = 200 )N, NSLCT, ISRT IF( N.EQ.0 ) $ GO TO 200 JTYPE = JTYPE + 1 ISEED( 1 ) = JTYPE READ( NIUNIT, FMT = * )( ISLCT( I ), I = 1, NSLCT ) DO 170 I = 1, N READ( NIUNIT, FMT = * )( A( I, J ), J = 1, N ) 170 CONTINUE READ( NIUNIT, FMT = * )RCDEIN, RCDVIN * CALL CGET24( .TRUE., 22, THRESH, ISEED, NOUNIT, N, A, LDA, H, HT, $ W, WT, WTMP, VS, LDVS, VS1, RCDEIN, RCDVIN, NSLCT, $ ISLCT, ISRT, RESULT, WORK, LWORK, RWORK, BWORK, $ INFO ) * * Check for RESULT(j) > THRESH * NTEST = 0 NFAIL = 0 DO 180 J = 1, 17 IF( RESULT( J ).GE.ZERO ) $ NTEST = NTEST + 1 IF( RESULT( J ).GE.THRESH ) $ NFAIL = NFAIL + 1 180 CONTINUE * IF( NFAIL.GT.0 ) $ NTESTF = NTESTF + 1 IF( NTESTF.EQ.1 ) THEN WRITE( NOUNIT, FMT = 9999 )PATH WRITE( NOUNIT, FMT = 9998 ) WRITE( NOUNIT, FMT = 9997 ) WRITE( NOUNIT, FMT = 9996 ) WRITE( NOUNIT, FMT = 9995 )THRESH WRITE( NOUNIT, FMT = 9994 ) NTESTF = 2 END IF DO 190 J = 1, 17 IF( RESULT( J ).GE.THRESH ) THEN WRITE( NOUNIT, FMT = 9992 )N, JTYPE, J, RESULT( J ) END IF 190 CONTINUE * NERRS = NERRS + NFAIL NTESTT = NTESTT + NTEST GO TO 160 200 CONTINUE * * Summary * CALL SLASUM( PATH, NOUNIT, NERRS, NTESTT ) * 9999 FORMAT( / 1X, A3, ' -- Complex Schur Form Decomposition Expert ', $ 'Driver', / ' Matrix types (see CDRVSX for details): ' ) * 9998 FORMAT( / ' Special Matrices:', / ' 1=Zero matrix. ', $ ' ', ' 5=Diagonal: geometr. spaced entries.', $ / ' 2=Identity matrix. ', ' 6=Diagona', $ 'l: clustered entries.', / ' 3=Transposed Jordan block. ', $ ' ', ' 7=Diagonal: large, evenly spaced.', / ' ', $ '4=Diagonal: evenly spaced entries. ', ' 8=Diagonal: s', $ 'mall, evenly spaced.' ) 9997 FORMAT( ' Dense, Non-Symmetric Matrices:', / ' 9=Well-cond., ev', $ 'enly spaced eigenvals.', ' 14=Ill-cond., geomet. spaced e', $ 'igenals.', / ' 10=Well-cond., geom. spaced eigenvals. ', $ ' 15=Ill-conditioned, clustered e.vals.', / ' 11=Well-cond', $ 'itioned, clustered e.vals. ', ' 16=Ill-cond., random comp', $ 'lex ', / ' 12=Well-cond., random complex ', ' ', $ ' 17=Ill-cond., large rand. complx ', / ' 13=Ill-condi', $ 'tioned, evenly spaced. ', ' 18=Ill-cond., small rand.', $ ' complx ' ) 9996 FORMAT( ' 19=Matrix with random O(1) entries. ', ' 21=Matrix ', $ 'with small random entries.', / ' 20=Matrix with large ran', $ 'dom entries. ', / ) 9995 FORMAT( ' Tests performed with test threshold =', F8.2, $ / ' ( A denotes A on input and T denotes A on output)', $ / / ' 1 = 0 if T in Schur form (no sort), ', $ ' 1/ulp otherwise', / $ ' 2 = | A - VS T transpose(VS) | / ( n |A| ulp ) (no sort)', $ / ' 3 = | I - VS transpose(VS) | / ( n ulp ) (no sort) ', $ / ' 4 = 0 if W are eigenvalues of T (no sort),', $ ' 1/ulp otherwise', / $ ' 5 = 0 if T same no matter if VS computed (no sort),', $ ' 1/ulp otherwise', / $ ' 6 = 0 if W same no matter if VS computed (no sort)', $ ', 1/ulp otherwise' ) 9994 FORMAT( ' 7 = 0 if T in Schur form (sort), ', ' 1/ulp otherwise', $ / ' 8 = | A - VS T transpose(VS) | / ( n |A| ulp ) (sort)', $ / ' 9 = | I - VS transpose(VS) | / ( n ulp ) (sort) ', $ / ' 10 = 0 if W are eigenvalues of T (sort),', $ ' 1/ulp otherwise', / $ ' 11 = 0 if T same no matter what else computed (sort),', $ ' 1/ulp otherwise', / $ ' 12 = 0 if W same no matter what else computed ', $ '(sort), 1/ulp otherwise', / $ ' 13 = 0 if sorting successful, 1/ulp otherwise', $ / ' 14 = 0 if RCONDE same no matter what else computed,', $ ' 1/ulp otherwise', / $ ' 15 = 0 if RCONDv same no matter what else computed,', $ ' 1/ulp otherwise', / $ ' 16 = | RCONDE - RCONDE(precomputed) | / cond(RCONDE),', $ / ' 17 = | RCONDV - RCONDV(precomputed) | / cond(RCONDV),' ) 9993 FORMAT( ' N=', I5, ', IWK=', I2, ', seed=', 4( I4, ',' ), $ ' type ', I2, ', test(', I2, ')=', G10.3 ) 9992 FORMAT( ' N=', I5, ', input example =', I3, ', test(', I2, ')=', $ G10.3 ) 9991 FORMAT( ' CDRVSX: ', A, ' returned INFO=', I6, '.', / 9X, 'N=', $ I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, ')' ) * RETURN * * End of CDRVSX * END