LAPACK 3.12.0
LAPACK: Linear Algebra PACKage
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◆ sdrvvx()

subroutine sdrvvx ( integer  nsizes,
integer, dimension( * )  nn,
integer  ntypes,
logical, dimension( * )  dotype,
integer, dimension( 4 )  iseed,
real  thresh,
integer  niunit,
integer  nounit,
real, dimension( lda, * )  a,
integer  lda,
real, dimension( lda, * )  h,
real, dimension( * )  wr,
real, dimension( * )  wi,
real, dimension( * )  wr1,
real, dimension( * )  wi1,
real, dimension( ldvl, * )  vl,
integer  ldvl,
real, dimension( ldvr, * )  vr,
integer  ldvr,
real, dimension( ldlre, * )  lre,
integer  ldlre,
real, dimension( * )  rcondv,
real, dimension( * )  rcndv1,
real, dimension( * )  rcdvin,
real, dimension( * )  rconde,
real, dimension( * )  rcnde1,
real, dimension( * )  rcdein,
real, dimension( * )  scale,
real, dimension( * )  scale1,
real, dimension( 11 )  result,
real, dimension( * )  work,
integer  nwork,
integer, dimension( * )  iwork,
integer  info 
)

SDRVVX

Purpose:
    SDRVVX  checks the nonsymmetric eigenvalue problem expert driver
    SGEEVX.

    SDRVVX 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 SDRVVX 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 block diagonal matrix, with a 1x1 block for each
      real eigenvalue and a 2x2 block for each complex conjugate
      pair.  If eigenvalues j and j+1 are a complex conjugate pair,
      so WR(j) = WR(j+1) = wr and WI(j) = - WI(j+1) = wi, then the
      2 x 2 block corresponding to the pair will be:

              (  wr  wi  )
              ( -wi  wr  )

      Such a block multiplying an n x 2 matrix  ( ur ui ) on the
      right will be the same as multiplying  ur + i*ui  by  wr + i*wi.

    (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 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 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 SGEEVX 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 SGEEVX 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.
Parameters
[in]NSIZES
          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.
[in]NN
          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.
[in]NTYPES
          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. .
[in]DOTYPE
          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.
[in,out]ISEED
          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 SDRVVX to continue the same random number
          sequence.
[in]THRESH
          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.
[in]NIUNIT
          NIUNIT is INTEGER
          The FORTRAN unit number for reading in the data file of
          problems to solve.
[in]NOUNIT
          NOUNIT is INTEGER
          The FORTRAN unit number for printing out error messages
          (e.g., if a routine returns INFO not equal to 0.)
[out]A
          A is REAL 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.
[in]LDA
          LDA is INTEGER
          The leading dimension of the arrays A and H.
          LDA >= max(NN,12), since 12 is the dimension of the largest
          matrix in the precomputed input file.
[out]H
          H is REAL array, dimension
                      (LDA, max(NN,12))
          Another copy of the test matrix A, modified by SGEEVX.
[out]WR
          WR is REAL array, dimension (max(NN))
[out]WI
          WI is REAL 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.
[out]WR1
          WR1 is REAL array, dimension (max(NN,12))
[out]WI1
          WI1 is REAL array, dimension (max(NN,12))

          Like WR, WI, these arrays contain the eigenvalues of A,
          but those computed when SGEEVX only computes a partial
          eigendecomposition, i.e. not the eigenvalues and left
          and right eigenvectors.
[out]VL
          VL is REAL array, dimension
                      (LDVL, max(NN,12))
          VL holds the computed left eigenvectors.
[in]LDVL
          LDVL is INTEGER
          Leading dimension of VL. Must be at least max(1,max(NN,12)).
[out]VR
          VR is REAL array, dimension
                      (LDVR, max(NN,12))
          VR holds the computed right eigenvectors.
[in]LDVR
          LDVR is INTEGER
          Leading dimension of VR. Must be at least max(1,max(NN,12)).
[out]LRE
          LRE is REAL array, dimension
                      (LDLRE, max(NN,12))
          LRE holds the computed right or left eigenvectors.
[in]LDLRE
          LDLRE is INTEGER
          Leading dimension of LRE. Must be at least max(1,max(NN,12))
[out]RCONDV
          RCONDV is REAL array, dimension (N)
          RCONDV holds the computed reciprocal condition numbers
          for eigenvectors.
[out]RCNDV1
          RCNDV1 is REAL array, dimension (N)
          RCNDV1 holds more computed reciprocal condition numbers
          for eigenvectors.
[out]RCDVIN
          RCDVIN is REAL array, dimension (N)
          When COMP = .TRUE. RCDVIN holds the precomputed reciprocal
          condition numbers for eigenvectors to be compared with
          RCONDV.
[out]RCONDE
          RCONDE is REAL array, dimension (N)
          RCONDE holds the computed reciprocal condition numbers
          for eigenvalues.
[out]RCNDE1
          RCNDE1 is REAL array, dimension (N)
          RCNDE1 holds more computed reciprocal condition numbers
          for eigenvalues.
[out]RCDEIN
          RCDEIN is REAL array, dimension (N)
          When COMP = .TRUE. RCDEIN holds the precomputed reciprocal
          condition numbers for eigenvalues to be compared with
          RCONDE.
[out]SCALE
          SCALE is REAL array, dimension (N)
          Holds information describing balancing of matrix.
[out]SCALE1
          SCALE1 is REAL array, dimension (N)
          Holds information describing balancing of matrix.
[out]RESULT
          RESULT is REAL array, dimension (11)
          The values computed by the seven tests described above.
          The values are currently limited to 1/ulp, to avoid overflow.
[out]WORK
          WORK is REAL array, dimension (NWORK)
[in]NWORK
          NWORK is 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.
[out]IWORK
          IWORK is INTEGER array, dimension (2*max(NN,12))
[out]INFO
          INFO is INTEGER
          If 0,  then successful exit.
          If <0, then input parameter -INFO is incorrect.
          If >0, SLATMR, SLATMS, SLATME or SGET23 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.)
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.

Definition at line 515 of file sdrvvx.f.

520*
521* -- LAPACK test routine --
522* -- LAPACK is a software package provided by Univ. of Tennessee, --
523* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
524*
525* .. Scalar Arguments ..
526 INTEGER INFO, LDA, LDLRE, LDVL, LDVR, NIUNIT, NOUNIT,
527 $ NSIZES, NTYPES, NWORK
528 REAL THRESH
529* ..
530* .. Array Arguments ..
531 LOGICAL DOTYPE( * )
532 INTEGER ISEED( 4 ), IWORK( * ), NN( * )
533 REAL A( LDA, * ), H( LDA, * ), LRE( LDLRE, * ),
534 $ RCDEIN( * ), RCDVIN( * ), RCNDE1( * ),
535 $ RCNDV1( * ), RCONDE( * ), RCONDV( * ),
536 $ RESULT( 11 ), SCALE( * ), SCALE1( * ),
537 $ VL( LDVL, * ), VR( LDVR, * ), WI( * ),
538 $ WI1( * ), WORK( * ), WR( * ), WR1( * )
539* ..
540*
541* =====================================================================
542*
543* .. Parameters ..
544 REAL ZERO, ONE
545 parameter( zero = 0.0e0, one = 1.0e0 )
546 INTEGER MAXTYP
547 parameter( maxtyp = 21 )
548* ..
549* .. Local Scalars ..
550 LOGICAL BADNN
551 CHARACTER BALANC
552 CHARACTER*3 PATH
553 INTEGER I, IBAL, IINFO, IMODE, ITYPE, IWK, J, JCOL,
554 $ JSIZE, JTYPE, MTYPES, N, NERRS, NFAIL,
555 $ NMAX, NNWORK, NTEST, NTESTF, NTESTT
556 REAL ANORM, COND, CONDS, OVFL, RTULP, RTULPI, ULP,
557 $ ULPINV, UNFL
558* ..
559* .. Local Arrays ..
560 CHARACTER ADUMMA( 1 ), BAL( 4 )
561 INTEGER IDUMMA( 1 ), IOLDSD( 4 ), KCONDS( MAXTYP ),
562 $ KMAGN( MAXTYP ), KMODE( MAXTYP ),
563 $ KTYPE( MAXTYP )
564* ..
565* .. External Functions ..
566 REAL SLAMCH
567 EXTERNAL slamch
568* ..
569* .. External Subroutines ..
570 EXTERNAL sget23, slasum, slatme, slatmr, slatms, slaset,
571 $ xerbla
572* ..
573* .. Intrinsic Functions ..
574 INTRINSIC abs, max, min, sqrt
575* ..
576* .. Data statements ..
577 DATA ktype / 1, 2, 3, 5*4, 4*6, 6*6, 3*9 /
578 DATA kmagn / 3*1, 1, 1, 1, 2, 3, 4*1, 1, 1, 1, 1, 2,
579 $ 3, 1, 2, 3 /
580 DATA kmode / 3*0, 4, 3, 1, 4, 4, 4, 3, 1, 5, 4, 3,
581 $ 1, 5, 5, 5, 4, 3, 1 /
582 DATA kconds / 3*0, 5*0, 4*1, 6*2, 3*0 /
583 DATA bal / 'N', 'P', 'S', 'B' /
584* ..
585* .. Executable Statements ..
586*
587 path( 1: 1 ) = 'Single precision'
588 path( 2: 3 ) = 'VX'
589*
590* Check for errors
591*
592 ntestt = 0
593 ntestf = 0
594 info = 0
595*
596* Important constants
597*
598 badnn = .false.
599*
600* 12 is the largest dimension in the input file of precomputed
601* problems
602*
603 nmax = 12
604 DO 10 j = 1, nsizes
605 nmax = max( nmax, nn( j ) )
606 IF( nn( j ).LT.0 )
607 $ badnn = .true.
608 10 CONTINUE
609*
610* Check for errors
611*
612 IF( nsizes.LT.0 ) THEN
613 info = -1
614 ELSE IF( badnn ) THEN
615 info = -2
616 ELSE IF( ntypes.LT.0 ) THEN
617 info = -3
618 ELSE IF( thresh.LT.zero ) THEN
619 info = -6
620 ELSE IF( lda.LT.1 .OR. lda.LT.nmax ) THEN
621 info = -10
622 ELSE IF( ldvl.LT.1 .OR. ldvl.LT.nmax ) THEN
623 info = -17
624 ELSE IF( ldvr.LT.1 .OR. ldvr.LT.nmax ) THEN
625 info = -19
626 ELSE IF( ldlre.LT.1 .OR. ldlre.LT.nmax ) THEN
627 info = -21
628 ELSE IF( 6*nmax+2*nmax**2.GT.nwork ) THEN
629 info = -32
630 END IF
631*
632 IF( info.NE.0 ) THEN
633 CALL xerbla( 'SDRVVX', -info )
634 RETURN
635 END IF
636*
637* If nothing to do check on NIUNIT
638*
639 IF( nsizes.EQ.0 .OR. ntypes.EQ.0 )
640 $ GO TO 160
641*
642* More Important constants
643*
644 unfl = slamch( 'Safe minimum' )
645 ovfl = one / unfl
646 ulp = slamch( 'Precision' )
647 ulpinv = one / ulp
648 rtulp = sqrt( ulp )
649 rtulpi = one / rtulp
650*
651* Loop over sizes, types
652*
653 nerrs = 0
654*
655 DO 150 jsize = 1, nsizes
656 n = nn( jsize )
657 IF( nsizes.NE.1 ) THEN
658 mtypes = min( maxtyp, ntypes )
659 ELSE
660 mtypes = min( maxtyp+1, ntypes )
661 END IF
662*
663 DO 140 jtype = 1, mtypes
664 IF( .NOT.dotype( jtype ) )
665 $ GO TO 140
666*
667* Save ISEED in case of an error.
668*
669 DO 20 j = 1, 4
670 ioldsd( j ) = iseed( j )
671 20 CONTINUE
672*
673* Compute "A"
674*
675* Control parameters:
676*
677* KMAGN KCONDS KMODE KTYPE
678* =1 O(1) 1 clustered 1 zero
679* =2 large large clustered 2 identity
680* =3 small exponential Jordan
681* =4 arithmetic diagonal, (w/ eigenvalues)
682* =5 random log symmetric, w/ eigenvalues
683* =6 random general, w/ eigenvalues
684* =7 random diagonal
685* =8 random symmetric
686* =9 random general
687* =10 random triangular
688*
689 IF( mtypes.GT.maxtyp )
690 $ GO TO 90
691*
692 itype = ktype( jtype )
693 imode = kmode( jtype )
694*
695* Compute norm
696*
697 GO TO ( 30, 40, 50 )kmagn( jtype )
698*
699 30 CONTINUE
700 anorm = one
701 GO TO 60
702*
703 40 CONTINUE
704 anorm = ovfl*ulp
705 GO TO 60
706*
707 50 CONTINUE
708 anorm = unfl*ulpinv
709 GO TO 60
710*
711 60 CONTINUE
712*
713 CALL slaset( 'Full', lda, n, zero, zero, a, lda )
714 iinfo = 0
715 cond = ulpinv
716*
717* Special Matrices -- Identity & Jordan block
718*
719* Zero
720*
721 IF( itype.EQ.1 ) THEN
722 iinfo = 0
723*
724 ELSE IF( itype.EQ.2 ) THEN
725*
726* Identity
727*
728 DO 70 jcol = 1, n
729 a( jcol, jcol ) = anorm
730 70 CONTINUE
731*
732 ELSE IF( itype.EQ.3 ) THEN
733*
734* Jordan Block
735*
736 DO 80 jcol = 1, n
737 a( jcol, jcol ) = anorm
738 IF( jcol.GT.1 )
739 $ a( jcol, jcol-1 ) = one
740 80 CONTINUE
741*
742 ELSE IF( itype.EQ.4 ) THEN
743*
744* Diagonal Matrix, [Eigen]values Specified
745*
746 CALL slatms( n, n, 'S', iseed, 'S', work, imode, cond,
747 $ anorm, 0, 0, 'N', a, lda, work( n+1 ),
748 $ iinfo )
749*
750 ELSE IF( itype.EQ.5 ) THEN
751*
752* Symmetric, eigenvalues specified
753*
754 CALL slatms( n, n, 'S', iseed, 'S', work, imode, cond,
755 $ anorm, n, n, 'N', a, lda, work( n+1 ),
756 $ iinfo )
757*
758 ELSE IF( itype.EQ.6 ) THEN
759*
760* General, eigenvalues specified
761*
762 IF( kconds( jtype ).EQ.1 ) THEN
763 conds = one
764 ELSE IF( kconds( jtype ).EQ.2 ) THEN
765 conds = rtulpi
766 ELSE
767 conds = zero
768 END IF
769*
770 adumma( 1 ) = ' '
771 CALL slatme( n, 'S', iseed, work, imode, cond, one,
772 $ adumma, 'T', 'T', 'T', work( n+1 ), 4,
773 $ conds, n, n, anorm, a, lda, work( 2*n+1 ),
774 $ iinfo )
775*
776 ELSE IF( itype.EQ.7 ) THEN
777*
778* Diagonal, random eigenvalues
779*
780 CALL slatmr( n, n, 'S', iseed, 'S', work, 6, one, one,
781 $ 'T', 'N', work( n+1 ), 1, one,
782 $ work( 2*n+1 ), 1, one, 'N', idumma, 0, 0,
783 $ zero, anorm, 'NO', a, lda, iwork, iinfo )
784*
785 ELSE IF( itype.EQ.8 ) THEN
786*
787* Symmetric, random eigenvalues
788*
789 CALL slatmr( n, n, 'S', iseed, 'S', work, 6, one, one,
790 $ 'T', 'N', work( n+1 ), 1, one,
791 $ work( 2*n+1 ), 1, one, 'N', idumma, n, n,
792 $ zero, anorm, 'NO', a, lda, iwork, iinfo )
793*
794 ELSE IF( itype.EQ.9 ) THEN
795*
796* General, random eigenvalues
797*
798 CALL slatmr( n, n, 'S', iseed, 'N', work, 6, one, one,
799 $ 'T', 'N', work( n+1 ), 1, one,
800 $ work( 2*n+1 ), 1, one, 'N', idumma, n, n,
801 $ zero, anorm, 'NO', a, lda, iwork, iinfo )
802 IF( n.GE.4 ) THEN
803 CALL slaset( 'Full', 2, n, zero, zero, a, lda )
804 CALL slaset( 'Full', n-3, 1, zero, zero, a( 3, 1 ),
805 $ lda )
806 CALL slaset( 'Full', n-3, 2, zero, zero, a( 3, n-1 ),
807 $ lda )
808 CALL slaset( 'Full', 1, n, zero, zero, a( n, 1 ),
809 $ lda )
810 END IF
811*
812 ELSE IF( itype.EQ.10 ) THEN
813*
814* Triangular, random eigenvalues
815*
816 CALL slatmr( n, n, 'S', iseed, 'N', work, 6, one, one,
817 $ 'T', 'N', work( n+1 ), 1, one,
818 $ work( 2*n+1 ), 1, one, 'N', idumma, n, 0,
819 $ zero, anorm, 'NO', a, lda, iwork, iinfo )
820*
821 ELSE
822*
823 iinfo = 1
824 END IF
825*
826 IF( iinfo.NE.0 ) THEN
827 WRITE( nounit, fmt = 9992 )'Generator', iinfo, n, jtype,
828 $ ioldsd
829 info = abs( iinfo )
830 RETURN
831 END IF
832*
833 90 CONTINUE
834*
835* Test for minimal and generous workspace
836*
837 DO 130 iwk = 1, 3
838 IF( iwk.EQ.1 ) THEN
839 nnwork = 3*n
840 ELSE IF( iwk.EQ.2 ) THEN
841 nnwork = 6*n + n**2
842 ELSE
843 nnwork = 6*n + 2*n**2
844 END IF
845 nnwork = max( nnwork, 1 )
846*
847* Test for all balancing options
848*
849 DO 120 ibal = 1, 4
850 balanc = bal( ibal )
851*
852* Perform tests
853*
854 CALL sget23( .false., balanc, jtype, thresh, ioldsd,
855 $ nounit, n, a, lda, h, wr, wi, wr1, wi1,
856 $ vl, ldvl, vr, ldvr, lre, ldlre, rcondv,
857 $ rcndv1, rcdvin, rconde, rcnde1, rcdein,
858 $ scale, scale1, result, work, nnwork,
859 $ iwork, info )
860*
861* Check for RESULT(j) > THRESH
862*
863 ntest = 0
864 nfail = 0
865 DO 100 j = 1, 9
866 IF( result( j ).GE.zero )
867 $ ntest = ntest + 1
868 IF( result( j ).GE.thresh )
869 $ nfail = nfail + 1
870 100 CONTINUE
871*
872 IF( nfail.GT.0 )
873 $ ntestf = ntestf + 1
874 IF( ntestf.EQ.1 ) THEN
875 WRITE( nounit, fmt = 9999 )path
876 WRITE( nounit, fmt = 9998 )
877 WRITE( nounit, fmt = 9997 )
878 WRITE( nounit, fmt = 9996 )
879 WRITE( nounit, fmt = 9995 )thresh
880 ntestf = 2
881 END IF
882*
883 DO 110 j = 1, 9
884 IF( result( j ).GE.thresh ) THEN
885 WRITE( nounit, fmt = 9994 )balanc, n, iwk,
886 $ ioldsd, jtype, j, result( j )
887 END IF
888 110 CONTINUE
889*
890 nerrs = nerrs + nfail
891 ntestt = ntestt + ntest
892*
893 120 CONTINUE
894 130 CONTINUE
895 140 CONTINUE
896 150 CONTINUE
897*
898 160 CONTINUE
899*
900* Read in data from file to check accuracy of condition estimation.
901* Assume input eigenvalues are sorted lexicographically (increasing
902* by real part, then decreasing by imaginary part)
903*
904 jtype = 0
905 170 CONTINUE
906 READ( niunit, fmt = *, END = 220 )n
907*
908* Read input data until N=0
909*
910 IF( n.EQ.0 )
911 $ GO TO 220
912 jtype = jtype + 1
913 iseed( 1 ) = jtype
914 DO 180 i = 1, n
915 READ( niunit, fmt = * )( a( i, j ), j = 1, n )
916 180 CONTINUE
917 DO 190 i = 1, n
918 READ( niunit, fmt = * )wr1( i ), wi1( i ), rcdein( i ),
919 $ rcdvin( i )
920 190 CONTINUE
921 CALL sget23( .true., 'N', 22, thresh, iseed, nounit, n, a, lda, h,
922 $ wr, wi, wr1, wi1, vl, ldvl, vr, ldvr, lre, ldlre,
923 $ rcondv, rcndv1, rcdvin, rconde, rcnde1, rcdein,
924 $ scale, scale1, result, work, 6*n+2*n**2, iwork,
925 $ info )
926*
927* Check for RESULT(j) > THRESH
928*
929 ntest = 0
930 nfail = 0
931 DO 200 j = 1, 11
932 IF( result( j ).GE.zero )
933 $ ntest = ntest + 1
934 IF( result( j ).GE.thresh )
935 $ nfail = nfail + 1
936 200 CONTINUE
937*
938 IF( nfail.GT.0 )
939 $ ntestf = ntestf + 1
940 IF( ntestf.EQ.1 ) THEN
941 WRITE( nounit, fmt = 9999 )path
942 WRITE( nounit, fmt = 9998 )
943 WRITE( nounit, fmt = 9997 )
944 WRITE( nounit, fmt = 9996 )
945 WRITE( nounit, fmt = 9995 )thresh
946 ntestf = 2
947 END IF
948*
949 DO 210 j = 1, 11
950 IF( result( j ).GE.thresh ) THEN
951 WRITE( nounit, fmt = 9993 )n, jtype, j, result( j )
952 END IF
953 210 CONTINUE
954*
955 nerrs = nerrs + nfail
956 ntestt = ntestt + ntest
957 GO TO 170
958 220 CONTINUE
959*
960* Summary
961*
962 CALL slasum( path, nounit, nerrs, ntestt )
963*
964 9999 FORMAT( / 1x, a3, ' -- Real Eigenvalue-Eigenvector Decomposition',
965 $ ' Expert Driver', /
966 $ ' Matrix types (see SDRVVX for details): ' )
967*
968 9998 FORMAT( / ' Special Matrices:', / ' 1=Zero matrix. ',
969 $ ' ', ' 5=Diagonal: geometr. spaced entries.',
970 $ / ' 2=Identity matrix. ', ' 6=Diagona',
971 $ 'l: clustered entries.', / ' 3=Transposed Jordan block. ',
972 $ ' ', ' 7=Diagonal: large, evenly spaced.', / ' ',
973 $ '4=Diagonal: evenly spaced entries. ', ' 8=Diagonal: s',
974 $ 'mall, evenly spaced.' )
975 9997 FORMAT( ' Dense, Non-Symmetric Matrices:', / ' 9=Well-cond., ev',
976 $ 'enly spaced eigenvals.', ' 14=Ill-cond., geomet. spaced e',
977 $ 'igenals.', / ' 10=Well-cond., geom. spaced eigenvals. ',
978 $ ' 15=Ill-conditioned, clustered e.vals.', / ' 11=Well-cond',
979 $ 'itioned, clustered e.vals. ', ' 16=Ill-cond., random comp',
980 $ 'lex ', / ' 12=Well-cond., random complex ', ' ',
981 $ ' 17=Ill-cond., large rand. complx ', / ' 13=Ill-condi',
982 $ 'tioned, evenly spaced. ', ' 18=Ill-cond., small rand.',
983 $ ' complx ' )
984 9996 FORMAT( ' 19=Matrix with random O(1) entries. ', ' 21=Matrix ',
985 $ 'with small random entries.', / ' 20=Matrix with large ran',
986 $ 'dom entries. ', ' 22=Matrix read from input file', / )
987 9995 FORMAT( ' Tests performed with test threshold =', f8.2,
988 $ / / ' 1 = | A VR - VR W | / ( n |A| ulp ) ',
989 $ / ' 2 = | transpose(A) VL - VL W | / ( n |A| ulp ) ',
990 $ / ' 3 = | |VR(i)| - 1 | / ulp ',
991 $ / ' 4 = | |VL(i)| - 1 | / ulp ',
992 $ / ' 5 = 0 if W same no matter if VR or VL computed,',
993 $ ' 1/ulp otherwise', /
994 $ ' 6 = 0 if VR same no matter what else computed,',
995 $ ' 1/ulp otherwise', /
996 $ ' 7 = 0 if VL same no matter what else computed,',
997 $ ' 1/ulp otherwise', /
998 $ ' 8 = 0 if RCONDV same no matter what else computed,',
999 $ ' 1/ulp otherwise', /
1000 $ ' 9 = 0 if SCALE, ILO, IHI, ABNRM same no matter what else',
1001 $ ' computed, 1/ulp otherwise',
1002 $ / ' 10 = | RCONDV - RCONDV(precomputed) | / cond(RCONDV),',
1003 $ / ' 11 = | RCONDE - RCONDE(precomputed) | / cond(RCONDE),' )
1004 9994 FORMAT( ' BALANC=''', a1, ''',N=', i4, ',IWK=', i1, ', seed=',
1005 $ 4( i4, ',' ), ' type ', i2, ', test(', i2, ')=', g10.3 )
1006 9993 FORMAT( ' N=', i5, ', input example =', i3, ', test(', i2, ')=',
1007 $ g10.3 )
1008 9992 FORMAT( ' SDRVVX: ', a, ' returned INFO=', i6, '.', / 9x, 'N=',
1009 $ i6, ', JTYPE=', i6, ', ISEED=(', 3( i5, ',' ), i5, ')' )
1010*
1011 RETURN
1012*
1013* End of SDRVVX
1014*
subroutine xerbla(srname, info)
Definition cblat2.f:3285
real function slamch(cmach)
SLAMCH
Definition slamch.f:68
subroutine slaset(uplo, m, n, alpha, beta, a, lda)
SLASET initializes the off-diagonal elements and the diagonal elements of a matrix to given values.
Definition slaset.f:110
subroutine sget23(comp, balanc, jtype, thresh, iseed, nounit, n, a, lda, h, wr, wi, wr1, wi1, vl, ldvl, vr, ldvr, lre, ldlre, rcondv, rcndv1, rcdvin, rconde, rcnde1, rcdein, scale, scale1, result, work, lwork, iwork, info)
SGET23
Definition sget23.f:378
subroutine slasum(type, iounit, ie, nrun)
SLASUM
Definition slasum.f:41
subroutine slatme(n, dist, iseed, d, mode, cond, dmax, ei, rsign, upper, sim, ds, modes, conds, kl, ku, anorm, a, lda, work, info)
SLATME
Definition slatme.f:332
subroutine slatmr(m, n, dist, iseed, sym, d, mode, cond, dmax, rsign, grade, dl, model, condl, dr, moder, condr, pivtng, ipivot, kl, ku, sparse, anorm, pack, a, lda, iwork, info)
SLATMR
Definition slatmr.f:471
subroutine slatms(m, n, dist, iseed, sym, d, mode, cond, dmax, kl, ku, pack, a, lda, work, info)
SLATMS
Definition slatms.f:321
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