|
- *> \brief \b DDRVSX
- *
- * =========== DOCUMENTATION ===========
- *
- * Online html documentation available at
- * http://www.netlib.org/lapack/explore-html/
- *
- * Definition:
- * ===========
- *
- * SUBROUTINE DDRVSX( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
- * NIUNIT, NOUNIT, A, LDA, H, HT, WR, WI, WRT,
- * WIT, WRTMP, WITMP, VS, LDVS, VS1, RESULT, WORK,
- * LWORK, IWORK, BWORK, INFO )
- *
- * .. Scalar Arguments ..
- * INTEGER INFO, LDA, LDVS, LWORK, NIUNIT, NOUNIT, NSIZES,
- * $ NTYPES
- * DOUBLE PRECISION THRESH
- * ..
- * .. Array Arguments ..
- * LOGICAL BWORK( * ), DOTYPE( * )
- * INTEGER ISEED( 4 ), IWORK( * ), NN( * )
- * DOUBLE PRECISION A( LDA, * ), H( LDA, * ), HT( LDA, * ),
- * $ RESULT( 17 ), VS( LDVS, * ), VS1( LDVS, * ),
- * $ WI( * ), WIT( * ), WITMP( * ), WORK( * ),
- * $ WR( * ), WRT( * ), WRTMP( * )
- * ..
- *
- *
- *> \par Purpose:
- * =============
- *>
- *> \verbatim
- *>
- *> DDRVSX checks the nonsymmetric eigenvalue (Schur form) problem
- *> expert driver DGEESX.
- *>
- *> DDRVSX 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 DDRVSX 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 WR+sqrt(-1)*WI 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 WR+sqrt(-1)*WI are eigenvalues of T
- *> 1/ulp otherwise
- *> If workspace sufficient, also compare WR, WI 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 signs.
- *> (ULP = (first number larger than 1) - 1 )
- *> (5) A diagonal matrix with geometrically spaced entries
- *> 1, ..., ULP and random signs.
- *> (6) A diagonal matrix with "clustered" entries 1, ULP, ..., ULP
- *> and random signs.
- *>
- *> (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 orthogonal and
- *> T has evenly spaced entries 1, ..., ULP with random signs
- *> on the diagonal and random O(1) entries in the upper
- *> triangle.
- *>
- *> (10) A matrix of the form U' T U, where U is orthogonal and
- *> T has geometrically spaced entries 1, ..., ULP with random
- *> signs 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
- *> signs on the diagonal and random O(1) entries in the upper
- *> triangle.
- *>
- *> (12) A matrix of the form U' T U, where U is orthogonal and
- *> T has real or complex conjugate paired eigenvalues randomly
- *> chosen from ( ULP, 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 signs 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 signs 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 signs 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 real or complex conjugate paired
- *> eigenvalues randomly chosen from ( ULP, 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 DGEESX 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 DGEESX 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 DDRVSX to continue the same random number
- *> sequence.
- *> \endverbatim
- *>
- *> \param[in] THRESH
- *> \verbatim
- *> THRESH is DOUBLE PRECISION
- *> 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 DOUBLE PRECISION 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 DOUBLE PRECISION array, dimension (LDA, max(NN))
- *> Another copy of the test matrix A, modified by DGEESX.
- *> \endverbatim
- *>
- *> \param[out] HT
- *> \verbatim
- *> HT is DOUBLE PRECISION array, dimension (LDA, max(NN))
- *> Yet another copy of the test matrix A, modified by DGEESX.
- *> \endverbatim
- *>
- *> \param[out] WR
- *> \verbatim
- *> WR is DOUBLE PRECISION array, dimension (max(NN))
- *> \endverbatim
- *>
- *> \param[out] WI
- *> \verbatim
- *> WI is DOUBLE PRECISION array, dimension (max(NN))
- *>
- *> The real and imaginary parts of the eigenvalues of A.
- *> On exit, WR + WI*i are the eigenvalues of the matrix in A.
- *> \endverbatim
- *>
- *> \param[out] WRT
- *> \verbatim
- *> WRT is DOUBLE PRECISION array, dimension (max(NN))
- *> \endverbatim
- *>
- *> \param[out] WIT
- *> \verbatim
- *> WIT is DOUBLE PRECISION array, dimension (max(NN))
- *>
- *> Like WR, WI, these arrays contain the eigenvalues of A,
- *> but those computed when DGEESX only computes a partial
- *> eigendecomposition, i.e. not Schur vectors
- *> \endverbatim
- *>
- *> \param[out] WRTMP
- *> \verbatim
- *> WRTMP is DOUBLE PRECISION array, dimension (max(NN))
- *> \endverbatim
- *>
- *> \param[out] WITMP
- *> \verbatim
- *> WITMP is DOUBLE PRECISION array, dimension (max(NN))
- *>
- *> More temporary storage for eigenvalues.
- *> \endverbatim
- *>
- *> \param[out] VS
- *> \verbatim
- *> VS is DOUBLE PRECISION 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 DOUBLE PRECISION array, dimension (LDVS, max(NN))
- *> VS1 holds another copy of the computed Schur vectors.
- *> \endverbatim
- *>
- *> \param[out] RESULT
- *> \verbatim
- *> RESULT is DOUBLE PRECISION 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 DOUBLE PRECISION array, dimension (LWORK)
- *> \endverbatim
- *>
- *> \param[in] LWORK
- *> \verbatim
- *> LWORK is INTEGER
- *> The number of entries in WORK. This must be at least
- *> max(3*NN(j),2*NN(j)**2) for all j.
- *> \endverbatim
- *>
- *> \param[out] IWORK
- *> \verbatim
- *> IWORK is INTEGER array, dimension (max(NN)*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, DLATMR, SLATMS, SLATME or DGET24 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 November 2011
- *
- *> \ingroup double_eig
- *
- * =====================================================================
- SUBROUTINE DDRVSX( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
- $ NIUNIT, NOUNIT, A, LDA, H, HT, WR, WI, WRT,
- $ WIT, WRTMP, WITMP, VS, LDVS, VS1, RESULT, WORK,
- $ LWORK, IWORK, BWORK, 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, LDVS, LWORK, NIUNIT, NOUNIT, NSIZES,
- $ NTYPES
- DOUBLE PRECISION THRESH
- * ..
- * .. Array Arguments ..
- LOGICAL BWORK( * ), DOTYPE( * )
- INTEGER ISEED( 4 ), IWORK( * ), NN( * )
- DOUBLE PRECISION A( LDA, * ), H( LDA, * ), HT( LDA, * ),
- $ RESULT( 17 ), VS( LDVS, * ), VS1( LDVS, * ),
- $ WI( * ), WIT( * ), WITMP( * ), WORK( * ),
- $ WR( * ), WRT( * ), WRTMP( * )
- * ..
- *
- * =====================================================================
- *
- * .. Parameters ..
- DOUBLE PRECISION ZERO, ONE
- PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
- INTEGER MAXTYP
- PARAMETER ( MAXTYP = 21 )
- * ..
- * .. Local Scalars ..
- LOGICAL BADNN
- CHARACTER*3 PATH
- INTEGER I, IINFO, IMODE, ITYPE, IWK, J, JCOL, JSIZE,
- $ JTYPE, MTYPES, N, NERRS, NFAIL, NMAX, NNWORK,
- $ NSLCT, NTEST, NTESTF, NTESTT
- DOUBLE PRECISION ANORM, COND, CONDS, OVFL, RCDEIN, RCDVIN,
- $ RTULP, RTULPI, ULP, ULPINV, UNFL
- * ..
- * .. Local Arrays ..
- CHARACTER ADUMMA( 1 )
- INTEGER IDUMMA( 1 ), IOLDSD( 4 ), ISLCT( 20 ),
- $ KCONDS( MAXTYP ), KMAGN( MAXTYP ),
- $ KMODE( MAXTYP ), KTYPE( MAXTYP )
- * ..
- * .. Arrays in Common ..
- LOGICAL SELVAL( 20 )
- DOUBLE PRECISION SELWI( 20 ), SELWR( 20 )
- * ..
- * .. Scalars in Common ..
- INTEGER SELDIM, SELOPT
- * ..
- * .. Common blocks ..
- COMMON / SSLCT / SELOPT, SELDIM, SELVAL, SELWR, SELWI
- * ..
- * .. External Functions ..
- DOUBLE PRECISION DLAMCH
- EXTERNAL DLAMCH
- * ..
- * .. External Subroutines ..
- EXTERNAL DGET24, DLABAD, DLASET, DLASUM, DLATME, DLATMR,
- $ DLATMS, 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 ) = 'Double precision'
- PATH( 2: 3 ) = 'SX'
- *
- * Check for errors
- *
- NTESTT = 0
- NTESTF = 0
- INFO = 0
- *
- * Important constants
- *
- BADNN = .FALSE.
- *
- * 12 is the largest dimension in the input file of precomputed
- * problems
- *
- NMAX = 12
- 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( 'DDRVSX', -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 = DLAMCH( 'Safe minimum' )
- OVFL = ONE / UNFL
- CALL DLABAD( UNFL, OVFL )
- ULP = DLAMCH( '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 DLASET( 'Full', LDA, N, ZERO, ZERO, A, LDA )
- IINFO = 0
- COND = ULPINV
- *
- * Special Matrices -- Identity & Jordan block
- *
- * Zero
- *
- IF( ITYPE.EQ.1 ) THEN
- 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 ) = ONE
- 80 CONTINUE
- *
- ELSE IF( ITYPE.EQ.4 ) THEN
- *
- * Diagonal Matrix, [Eigen]values Specified
- *
- CALL DLATMS( N, N, 'S', ISEED, 'S', WORK, IMODE, COND,
- $ ANORM, 0, 0, 'N', A, LDA, WORK( N+1 ),
- $ IINFO )
- *
- ELSE IF( ITYPE.EQ.5 ) THEN
- *
- * Symmetric, eigenvalues specified
- *
- CALL DLATMS( N, N, 'S', ISEED, 'S', WORK, 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
- *
- ADUMMA( 1 ) = ' '
- CALL DLATME( N, 'S', ISEED, WORK, IMODE, COND, ONE,
- $ ADUMMA, 'T', 'T', 'T', WORK( N+1 ), 4,
- $ CONDS, N, N, ANORM, A, LDA, WORK( 2*N+1 ),
- $ IINFO )
- *
- ELSE IF( ITYPE.EQ.7 ) THEN
- *
- * Diagonal, random eigenvalues
- *
- CALL DLATMR( N, N, 'S', ISEED, 'S', WORK, 6, ONE, ONE,
- $ 'T', 'N', WORK( N+1 ), 1, ONE,
- $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, 0, 0,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- *
- ELSE IF( ITYPE.EQ.8 ) THEN
- *
- * Symmetric, random eigenvalues
- *
- CALL DLATMR( N, N, 'S', ISEED, 'S', WORK, 6, ONE, ONE,
- $ 'T', 'N', WORK( N+1 ), 1, ONE,
- $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, N,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- *
- ELSE IF( ITYPE.EQ.9 ) THEN
- *
- * General, random eigenvalues
- *
- CALL DLATMR( N, N, 'S', ISEED, 'N', WORK, 6, ONE, ONE,
- $ 'T', 'N', WORK( N+1 ), 1, ONE,
- $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, N,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- IF( N.GE.4 ) THEN
- CALL DLASET( 'Full', 2, N, ZERO, ZERO, A, LDA )
- CALL DLASET( 'Full', N-3, 1, ZERO, ZERO, A( 3, 1 ),
- $ LDA )
- CALL DLASET( 'Full', N-3, 2, ZERO, ZERO, A( 3, N-1 ),
- $ LDA )
- CALL DLASET( 'Full', 1, N, ZERO, ZERO, A( N, 1 ),
- $ LDA )
- END IF
- *
- ELSE IF( ITYPE.EQ.10 ) THEN
- *
- * Triangular, random eigenvalues
- *
- CALL DLATMR( N, N, 'S', ISEED, 'N', WORK, 6, ONE, ONE,
- $ 'T', 'N', WORK( N+1 ), 1, ONE,
- $ WORK( 2*N+1 ), 1, ONE, 'N', IDUMMA, N, 0,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, 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 = 3*N
- ELSE
- NNWORK = MAX( 3*N, 2*N*N )
- END IF
- NNWORK = MAX( NNWORK, 1 )
- *
- CALL DGET24( .FALSE., JTYPE, THRESH, IOLDSD, NOUNIT, N,
- $ A, LDA, H, HT, WR, WI, WRT, WIT, WRTMP,
- $ WITMP, VS, LDVS, VS1, RCDEIN, RCDVIN, NSLCT,
- $ ISLCT, RESULT, WORK, NNWORK, IWORK, 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
- IF( N.EQ.0 )
- $ GO TO 200
- JTYPE = JTYPE + 1
- ISEED( 1 ) = JTYPE
- IF( NSLCT.GT.0 )
- $ 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 DGET24( .TRUE., 22, THRESH, ISEED, NOUNIT, N, A, LDA, H, HT,
- $ WR, WI, WRT, WIT, WRTMP, WITMP, VS, LDVS, VS1,
- $ RCDEIN, RCDVIN, NSLCT, ISLCT, RESULT, WORK, LWORK,
- $ IWORK, 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 DLASUM( PATH, NOUNIT, NERRS, NTESTT )
- *
- 9999 FORMAT( / 1X, A3, ' -- Real Schur Form Decomposition Expert ',
- $ 'Driver', / ' Matrix types (see DDRVSX 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 WR+sqrt(-1)*WI 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 WR, WI 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 WR+sqrt(-1)*WI 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 WR, WI same no matter what else computed ',
- $ '(sort), 1/ulp otherwise', /
- $ ' 13 = 0 if sorting succesful, 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( ' DDRVSX: ', A, ' returned INFO=', I6, '.', / 9X, 'N=',
- $ I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, ')' )
- *
- RETURN
- *
- * End of DDRVSX
- *
- END
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