Files
lapack/TESTING/EIG/cdrvvx.f
T

820 lines
30 KiB
FortranFixed

SUBROUTINE CDRVVX( NSIZES, NN, NTYPES, DOTYPE, ISEED, THRESH,
$ NIUNIT, NOUNIT, A, LDA, H, W, W1, VL, LDVL, VR,
$ LDVR, LRE, LDLRE, RCONDV, RCNDV1, RCDVIN,
$ RCONDE, RCNDE1, RCDEIN, SCALE, SCALE1, RESULT,
$ WORK, NWORK, RWORK, INFO )
*
* -- LAPACK test routine (version 3.1) --
* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
* November 2006
*
* .. Scalar Arguments ..
INTEGER INFO, LDA, LDLRE, LDVL, LDVR, NIUNIT, NOUNIT,
$ NSIZES, NTYPES, NWORK
REAL THRESH
* ..
* .. Array Arguments ..
LOGICAL DOTYPE( * )
INTEGER ISEED( 4 ), NN( * )
REAL RCDEIN( * ), RCDVIN( * ), RCNDE1( * ),
$ RCNDV1( * ), RCONDE( * ), RCONDV( * ),
$ RESULT( 11 ), RWORK( * ), SCALE( * ),
$ SCALE1( * )
COMPLEX A( LDA, * ), H( LDA, * ), LRE( LDLRE, * ),
$ VL( LDVL, * ), VR( LDVR, * ), W( * ), W1( * ),
$ WORK( * )
* ..
*
* Purpose
* =======
*
* CDRVVX checks the nonsymmetric eigenvalue problem expert driver
* CGEEVX.
*
* CDRVVX 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 CDRVVX is called, a number of matrix "sizes" ("n's") and a
* number of matrix "types" are specified in the calling sequence.
* For each size ("n") and each type of matrix, one matrix will be
* generated and used to test the nonsymmetric eigenroutines. For
* each matrix, 9 tests will be performed:
*
* (1) | A * VR - VR * W | / ( n |A| ulp )
*
* Here VR is the matrix of unit right eigenvectors.
* W is a diagonal matrix with diagonal entries W(j).
*
* (2) | A**H * VL - VL * W**H | / ( n |A| ulp )
*
* Here VL is the matrix of unit left eigenvectors, A**H is the
* conjugate transpose of A, and W is as above.
*
* (3) | |VR(i)| - 1 | / ulp and largest component real
*
* VR(i) denotes the i-th column of VR.
*
* (4) | |VL(i)| - 1 | / ulp and largest component real
*
* VL(i) denotes the i-th column of VL.
*
* (5) W(full) = W(partial)
*
* W(full) denotes the eigenvalues computed when VR, VL, RCONDV
* and RCONDE are also computed, and W(partial) denotes the
* eigenvalues computed when only some of VR, VL, RCONDV, and
* RCONDE are computed.
*
* (6) VR(full) = VR(partial)
*
* VR(full) denotes the right eigenvectors computed when VL, RCONDV
* and RCONDE are computed, and VR(partial) denotes the result
* when only some of VL and RCONDV are computed.
*
* (7) VL(full) = VL(partial)
*
* VL(full) denotes the left eigenvectors computed when VR, RCONDV
* and RCONDE are computed, and VL(partial) denotes the result
* when only some of VR and RCONDV are computed.
*
* (8) 0 if SCALE, ILO, IHI, ABNRM (full) =
* SCALE, ILO, IHI, ABNRM (partial)
* 1/ulp otherwise
*
* SCALE, ILO, IHI and ABNRM describe how the matrix is balanced.
* (full) is when VR, VL, RCONDE and RCONDV are also computed, and
* (partial) is when some are not computed.
*
* (9) RCONDV(full) = RCONDV(partial)
*
* RCONDV(full) denotes the reciprocal condition numbers of the
* right eigenvectors computed when VR, VL and RCONDE are also
* computed. RCONDV(partial) denotes the reciprocal condition
* numbers when only some of VR, VL and RCONDE are 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 unitary 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 |z| < 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 eigenvalues
* and right eigenvectors. For these matrices, in addition to tests
* (1) to (9) we will compute the following two tests:
*
* (10) |RCONDV - RCDVIN| / cond(RCONDV)
*
* RCONDV is the reciprocal right eigenvector condition number
* computed by CGEEVX 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.
*
* (11) |RCONDE - RCDEIN| / cond(RCONDE)
*
* RCONDE is the reciprocal eigenvalue condition number
* computed by CGEEVX 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.
*
* Arguments
* ==========
*
* NSIZES (input) 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.
*
* NN (input) 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.
*
* NTYPES (input) 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. .
*
* DOTYPE (input) 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.
*
* ISEED (input/output) 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 CDRVVX to continue the same random number
* sequence.
*
* THRESH (input) 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.
*
* NIUNIT (input) INTEGER
* The FORTRAN unit number for reading in the data file of
* problems to solve.
*
* NOUNIT (input) INTEGER
* The FORTRAN unit number for printing out error messages
* (e.g., if a routine returns INFO not equal to 0.)
*
* A (workspace) COMPLEX array, dimension (LDA, max(NN,12))
* Used to hold the matrix whose eigenvalues are to be
* computed. On exit, A contains the last matrix actually used.
*
* LDA (input) INTEGER
* The leading dimension of A, and H. LDA must be at
* least 1 and at least max( NN, 12 ). (12 is the
* dimension of the largest matrix on the precomputed
* input file.)
*
* H (workspace) COMPLEX array, dimension (LDA, max(NN,12))
* Another copy of the test matrix A, modified by CGEEVX.
*
* W (workspace) COMPLEX array, dimension (max(NN,12))
* Contains the eigenvalues of A.
*
* W1 (workspace) COMPLEX array, dimension (max(NN,12))
* Like W, this array contains the eigenvalues of A,
* but those computed when CGEEVX only computes a partial
* eigendecomposition, i.e. not the eigenvalues and left
* and right eigenvectors.
*
* VL (workspace) COMPLEX array, dimension (LDVL, max(NN,12))
* VL holds the computed left eigenvectors.
*
* LDVL (input) INTEGER
* Leading dimension of VL. Must be at least max(1,max(NN,12)).
*
* VR (workspace) COMPLEX array, dimension (LDVR, max(NN,12))
* VR holds the computed right eigenvectors.
*
* LDVR (input) INTEGER
* Leading dimension of VR. Must be at least max(1,max(NN,12)).
*
* LRE (workspace) COMPLEX array, dimension (LDLRE, max(NN,12))
* LRE holds the computed right or left eigenvectors.
*
* LDLRE (input) INTEGER
* Leading dimension of LRE. Must be at least max(1,max(NN,12))
*
* RESULT (output) REAL array, dimension (11)
* The values computed by the seven tests described above.
* The values are currently limited to 1/ulp, to avoid
* overflow.
*
* WORK (workspace) COMPLEX array, dimension (NWORK)
*
* NWORK (input) INTEGER
* The number of entries in WORK. This must be at least
* max(6*12+2*12**2,6*NN(j)+2*NN(j)**2) =
* max( 360 ,6*NN(j)+2*NN(j)**2) for all j.
*
* RWORK (workspace) REAL array, dimension (2*max(NN,12))
*
* INFO (output) INTEGER
* If 0, then successful exit.
* If <0, then input paramter -INFO is incorrect.
* If >0, CLATMR, CLATMS, CLATME or CGET23 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 or 12.
* 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.)
*
* =====================================================================
*
* .. 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 BALANC
CHARACTER*3 PATH
INTEGER I, IBAL, IINFO, IMODE, ISRT, ITYPE, IWK, J,
$ JCOL, JSIZE, JTYPE, MTYPES, N, NERRS,
$ NFAIL, NMAX, NNWORK, NTEST, NTESTF, NTESTT
REAL ANORM, COND, CONDS, OVFL, RTULP, RTULPI, ULP,
$ ULPINV, UNFL, WI, WR
* ..
* .. Local Arrays ..
CHARACTER BAL( 4 )
INTEGER IDUMMA( 1 ), IOLDSD( 4 ), KCONDS( MAXTYP ),
$ KMAGN( MAXTYP ), KMODE( MAXTYP ),
$ KTYPE( MAXTYP )
* ..
* .. External Functions ..
REAL SLAMCH
EXTERNAL SLAMCH
* ..
* .. External Subroutines ..
EXTERNAL CGET23, CLATME, CLATMR, CLATMS, CLASET, SLABAD,
$ SLASUM, XERBLA
* ..
* .. Intrinsic Functions ..
INTRINSIC ABS, CMPLX, 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 /
DATA BAL / 'N', 'P', 'S', 'B' /
* ..
* .. Executable Statements ..
*
PATH( 1: 1 ) = 'Complex precision'
PATH( 2: 3 ) = 'VX'
*
* Check for errors
*
NTESTT = 0
NTESTF = 0
INFO = 0
*
* Important constants
*
BADNN = .FALSE.
*
* 7 is the largest dimension in the input file of precomputed
* problems
*
NMAX = 7
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( LDA.LT.1 .OR. LDA.LT.NMAX ) THEN
INFO = -10
ELSE IF( LDVL.LT.1 .OR. LDVL.LT.NMAX ) THEN
INFO = -15
ELSE IF( LDVR.LT.1 .OR. LDVR.LT.NMAX ) THEN
INFO = -17
ELSE IF( LDLRE.LT.1 .OR. LDLRE.LT.NMAX ) THEN
INFO = -19
ELSE IF( 6*NMAX+2*NMAX**2.GT.NWORK ) THEN
INFO = -30
END IF
*
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'CDRVVX', -INFO )
RETURN
END IF
*
* If nothing to do check on NIUNIT
*
IF( NSIZES.EQ.0 .OR. NTYPES.EQ.0 )
$ GO TO 160
*
* 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 150 JSIZE = 1, NSIZES
N = NN( JSIZE )
IF( NSIZES.NE.1 ) THEN
MTYPES = MIN( MAXTYP, NTYPES )
ELSE
MTYPES = MIN( MAXTYP+1, NTYPES )
END IF
*
DO 140 JTYPE = 1, MTYPES
IF( .NOT.DOTYPE( JTYPE ) )
$ GO TO 140
*
* 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
*
* 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 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, 'S', 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 = 9992 )'Generator', IINFO, N, JTYPE,
$ IOLDSD
INFO = ABS( IINFO )
RETURN
END IF
*
90 CONTINUE
*
* Test for minimal and generous workspace
*
DO 130 IWK = 1, 3
IF( IWK.EQ.1 ) THEN
NNWORK = 2*N
ELSE IF( IWK.EQ.2 ) THEN
NNWORK = 2*N + N**2
ELSE
NNWORK = 6*N + 2*N**2
END IF
NNWORK = MAX( NNWORK, 1 )
*
* Test for all balancing options
*
DO 120 IBAL = 1, 4
BALANC = BAL( IBAL )
*
* Perform tests
*
CALL CGET23( .FALSE., 0, BALANC, JTYPE, THRESH,
$ IOLDSD, NOUNIT, N, A, LDA, H, W, W1, VL,
$ LDVL, VR, LDVR, LRE, LDLRE, RCONDV,
$ RCNDV1, RCDVIN, RCONDE, RCNDE1, RCDEIN,
$ SCALE, SCALE1, RESULT, WORK, NNWORK,
$ RWORK, INFO )
*
* Check for RESULT(j) > THRESH
*
NTEST = 0
NFAIL = 0
DO 100 J = 1, 9
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
NTESTF = 2
END IF
*
DO 110 J = 1, 9
IF( RESULT( J ).GE.THRESH ) THEN
WRITE( NOUNIT, FMT = 9994 )BALANC, 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
*
160 CONTINUE
*
* Read in data from file to check accuracy of condition estimation.
* Assume input eigenvalues are sorted lexicographically (increasing
* by real part, then decreasing by imaginary part)
*
JTYPE = 0
170 CONTINUE
READ( NIUNIT, FMT = *, END = 220 )N, ISRT
*
* Read input data until N=0
*
IF( N.EQ.0 )
$ GO TO 220
JTYPE = JTYPE + 1
ISEED( 1 ) = JTYPE
DO 180 I = 1, N
READ( NIUNIT, FMT = * )( A( I, J ), J = 1, N )
180 CONTINUE
DO 190 I = 1, N
READ( NIUNIT, FMT = * )WR, WI, RCDEIN( I ), RCDVIN( I )
W1( I ) = CMPLX( WR, WI )
190 CONTINUE
CALL CGET23( .TRUE., ISRT, 'N', 22, THRESH, ISEED, NOUNIT, N, A,
$ LDA, H, W, W1, VL, LDVL, VR, LDVR, LRE, LDLRE,
$ RCONDV, RCNDV1, RCDVIN, RCONDE, RCNDE1, RCDEIN,
$ SCALE, SCALE1, RESULT, WORK, 6*N+2*N**2, RWORK,
$ INFO )
*
* Check for RESULT(j) > THRESH
*
NTEST = 0
NFAIL = 0
DO 200 J = 1, 11
IF( RESULT( J ).GE.ZERO )
$ NTEST = NTEST + 1
IF( RESULT( J ).GE.THRESH )
$ NFAIL = NFAIL + 1
200 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
NTESTF = 2
END IF
*
DO 210 J = 1, 11
IF( RESULT( J ).GE.THRESH ) THEN
WRITE( NOUNIT, FMT = 9993 )N, JTYPE, J, RESULT( J )
END IF
210 CONTINUE
*
NERRS = NERRS + NFAIL
NTESTT = NTESTT + NTEST
GO TO 170
220 CONTINUE
*
* Summary
*
CALL SLASUM( PATH, NOUNIT, NERRS, NTESTT )
*
9999 FORMAT( / 1X, A3, ' -- Complex Eigenvalue-Eigenvector ',
$ 'Decomposition Expert Driver',
$ / ' Matrix types (see CDRVVX 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. ', ' 22=Matrix read from input file', / )
9995 FORMAT( ' Tests performed with test threshold =', F8.2,
$ / / ' 1 = | A VR - VR W | / ( n |A| ulp ) ',
$ / ' 2 = | transpose(A) VL - VL W | / ( n |A| ulp ) ',
$ / ' 3 = | |VR(i)| - 1 | / ulp ',
$ / ' 4 = | |VL(i)| - 1 | / ulp ',
$ / ' 5 = 0 if W same no matter if VR or VL computed,',
$ ' 1/ulp otherwise', /
$ ' 6 = 0 if VR same no matter what else computed,',
$ ' 1/ulp otherwise', /
$ ' 7 = 0 if VL same no matter what else computed,',
$ ' 1/ulp otherwise', /
$ ' 8 = 0 if RCONDV same no matter what else computed,',
$ ' 1/ulp otherwise', /
$ ' 9 = 0 if SCALE, ILO, IHI, ABNRM same no matter what else',
$ ' computed, 1/ulp otherwise',
$ / ' 10 = | RCONDV - RCONDV(precomputed) | / cond(RCONDV),',
$ / ' 11 = | RCONDE - RCONDE(precomputed) | / cond(RCONDE),' )
9994 FORMAT( ' BALANC=''', A1, ''',N=', I4, ',IWK=', I1, ', seed=',
$ 4( I4, ',' ), ' type ', I2, ', test(', I2, ')=', G10.3 )
9993 FORMAT( ' N=', I5, ', input example =', I3, ', test(', I2, ')=',
$ G10.3 )
9992 FORMAT( ' CDRVVX: ', A, ' returned INFO=', I6, '.', / 9X, 'N=',
$ I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ), I5, ')' )
*
RETURN
*
* End of CDRVVX
*
END