dsyevr.f

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*> \brief <b> DSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices</b>
*
*  =========== DOCUMENTATION ===========
*
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*            http://www.netlib.org/lapack/explore-html/
*
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*> [TXT]</a>
*
*  Definition:
*  ===========
*
*       SUBROUTINE DSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU,
*                          ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK,
*                          IWORK, LIWORK, INFO )
*
*       .. Scalar Arguments ..
*       CHARACTER          JOBZ, RANGE, UPLO
*       INTEGER            IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N
*       DOUBLE PRECISION   ABSTOL, VL, VU
*       ..
*       .. Array Arguments ..
*       INTEGER            ISUPPZ( * ), IWORK( * )
*       DOUBLE PRECISION   A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * )
*       ..
*
*
*> \par Purpose:
*  =============
*>
*> \verbatim
*>
*> DSYEVR computes selected eigenvalues and, optionally, eigenvectors
*> of a real symmetric matrix A. Eigenvalues and eigenvectors can be
*> selected by specifying either a range of values or a range of indices
*> for the desired eigenvalues. Invocations with different choices for
*> these parameters may result in the computation of slightly different
*> eigenvalues and/or eigenvectors for the same matrix. The reason for
*> this behavior is that there exists a variety of algorithms (each
*> performing best for a particular set of options) with DSYEVR
*> attempting to select the best based on the various parameters. In all
*> cases, the computed values are accurate within the limits of finite
*> precision arithmetic.
*>
*> DSYEVR first reduces the matrix A to tridiagonal form T with a call
*> to DSYTRD.  Then, whenever possible, DSYEVR calls DSTEMR to compute
*> the eigenspectrum using Relatively Robust Representations.  DSTEMR
*> computes eigenvalues by the dqds algorithm, while orthogonal
*> eigenvectors are computed from various "good" L D L^T representations
*> (also known as Relatively Robust Representations). Gram-Schmidt
*> orthogonalization is avoided as far as possible. More specifically,
*> the various steps of the algorithm are as follows.
*>
*> For each unreduced block (submatrix) of T,
*>    (a) Compute T - sigma I  = L D L^T, so that L and D
*>        define all the wanted eigenvalues to high relative accuracy.
*>        This means that small relative changes in the entries of D and L
*>        cause only small relative changes in the eigenvalues and
*>        eigenvectors. The standard (unfactored) representation of the
*>        tridiagonal matrix T does not have this property in general.
*>    (b) Compute the eigenvalues to suitable accuracy.
*>        If the eigenvectors are desired, the algorithm attains full
*>        accuracy of the computed eigenvalues only right before
*>        the corresponding vectors have to be computed, see steps c) and d).
*>    (c) For each cluster of close eigenvalues, select a new
*>        shift close to the cluster, find a new factorization, and refine
*>        the shifted eigenvalues to suitable accuracy.
*>    (d) For each eigenvalue with a large enough relative separation compute
*>        the corresponding eigenvector by forming a rank revealing twisted
*>        factorization. Go back to (c) for any clusters that remain.
*>
*> The desired accuracy of the output can be specified by the input
*> parameter ABSTOL.
*>
*> For more details, see DSTEMR's documentation and:
*> - Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations
*>   to compute orthogonal eigenvectors of symmetric tridiagonal matrices,"
*>   Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004.
*> - Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and
*>   Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25,
*>   2004.  Also LAPACK Working Note 154.
*> - Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric
*>   tridiagonal eigenvalue/eigenvector problem",
*>   Computer Science Division Technical Report No. UCB/CSD-97-971,
*>   UC Berkeley, May 1997.
*>
*>
*> Note 1 : DSYEVR calls DSTEMR when the full spectrum is requested
*> on machines which conform to the ieee-754 floating point standard.
*> DSYEVR calls DSTEBZ and DSTEIN on non-ieee machines and
*> when partial spectrum requests are made.
*>
*> Normal execution of DSTEMR may create NaNs and infinities and
*> hence may abort due to a floating point exception in environments
*> which do not handle NaNs and infinities in the ieee standard default
*> manner.
*> \endverbatim
*
*  Arguments:
*  ==========
*
*> \param[in] JOBZ
*> \verbatim
*>          JOBZ is CHARACTER*1
*>          = 'N':  Compute eigenvalues only;
*>          = 'V':  Compute eigenvalues and eigenvectors.
*>
*>          This parameter influences the choice of the algorithm and
*>          may alter the computed values.
*> \endverbatim
*>
*> \param[in] RANGE
*> \verbatim
*>          RANGE is CHARACTER*1
*>          = 'A': all eigenvalues will be found.
*>          = 'V': all eigenvalues in the half-open interval (VL,VU]
*>                 will be found.
*>          = 'I': the IL-th through IU-th eigenvalues will be found.
*>          For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and
*>          DSTEIN are called
*>
*>          This parameter influences the choice of the algorithm and
*>          may alter the computed values.
*> \endverbatim
*>
*> \param[in] UPLO
*> \verbatim
*>          UPLO is CHARACTER*1
*>          = 'U':  Upper triangle of A is stored;
*>          = 'L':  Lower triangle of A is stored.
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*>          N is INTEGER
*>          The order of the matrix A.  N >= 0.
*> \endverbatim
*>
*> \param[in,out] A
*> \verbatim
*>          A is DOUBLE PRECISION array, dimension (LDA, N)
*>          On entry, the symmetric matrix A.  If UPLO = 'U', the
*>          leading N-by-N upper triangular part of A contains the
*>          upper triangular part of the matrix A.  If UPLO = 'L',
*>          the leading N-by-N lower triangular part of A contains
*>          the lower triangular part of the matrix A.
*>          On exit, the lower triangle (if UPLO='L') or the upper
*>          triangle (if UPLO='U') of A, including the diagonal, is
*>          destroyed.
*> \endverbatim
*>
*> \param[in] LDA
*> \verbatim
*>          LDA is INTEGER
*>          The leading dimension of the array A.  LDA >= max(1,N).
*> \endverbatim
*>
*> \param[in] VL
*> \verbatim
*>          VL is DOUBLE PRECISION
*>          If RANGE='V', the lower bound of the interval to
*>          be searched for eigenvalues. VL < VU.
*>          Not referenced if RANGE = 'A' or 'I'.
*> \endverbatim
*>
*> \param[in] VU
*> \verbatim
*>          VU is DOUBLE PRECISION
*>          If RANGE='V', the upper bound of the interval to
*>          be searched for eigenvalues. VL < VU.
*>          Not referenced if RANGE = 'A' or 'I'.
*> \endverbatim
*>
*> \param[in] IL
*> \verbatim
*>          IL is INTEGER
*>          If RANGE='I', the index of the
*>          smallest eigenvalue to be returned.
*>          1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
*>          Not referenced if RANGE = 'A' or 'V'.
*> \endverbatim
*>
*> \param[in] IU
*> \verbatim
*>          IU is INTEGER
*>          If RANGE='I', the index of the
*>          largest eigenvalue to be returned.
*>          1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
*>          Not referenced if RANGE = 'A' or 'V'.
*> \endverbatim
*>
*> \param[in] ABSTOL
*> \verbatim
*>          ABSTOL is DOUBLE PRECISION
*>          The absolute error tolerance for the eigenvalues.
*>          An approximate eigenvalue is accepted as converged
*>          when it is determined to lie in an interval [a,b]
*>          of width less than or equal to
*>
*>                  ABSTOL + EPS *   max( |a|,|b| ) ,
*>
*>          where EPS is the machine precision.  If ABSTOL is less than
*>          or equal to zero, then  EPS*|T|  will be used in its place,
*>          where |T| is the 1-norm of the tridiagonal matrix obtained
*>          by reducing A to tridiagonal form.
*>
*>          See "Computing Small Singular Values of Bidiagonal Matrices
*>          with Guaranteed High Relative Accuracy," by Demmel and
*>          Kahan, LAPACK Working Note #3.
*>
*>          If high relative accuracy is important, set ABSTOL to
*>          DLAMCH( 'Safe minimum' ).  Doing so will guarantee that
*>          eigenvalues are computed to high relative accuracy when
*>          possible in future releases.  The current code does not
*>          make any guarantees about high relative accuracy, but
*>          future releases will. See J. Barlow and J. Demmel,
*>          "Computing Accurate Eigensystems of Scaled Diagonally
*>          Dominant Matrices", LAPACK Working Note #7, for a discussion
*>          of which matrices define their eigenvalues to high relative
*>          accuracy.
*> \endverbatim
*>
*> \param[out] M
*> \verbatim
*>          M is INTEGER
*>          The total number of eigenvalues found.  0 <= M <= N.
*>          If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
*> \endverbatim
*>
*> \param[out] W
*> \verbatim
*>          W is DOUBLE PRECISION array, dimension (N)
*>          The first M elements contain the selected eigenvalues in
*>          ascending order.
*> \endverbatim
*>
*> \param[out] Z
*> \verbatim
*>          Z is DOUBLE PRECISION array, dimension (LDZ, max(1,M))
*>          If JOBZ = 'V', then if INFO = 0, the first M columns of Z
*>          contain the orthonormal eigenvectors of the matrix A
*>          corresponding to the selected eigenvalues, with the i-th
*>          column of Z holding the eigenvector associated with W(i).
*>          If JOBZ = 'N', then Z is not referenced.
*>          Note: the user must ensure that at least max(1,M) columns are
*>          supplied in the array Z; if RANGE = 'V', the exact value of M
*>          is not known in advance and an upper bound must be used.
*>          Supplying N columns is always safe.
*> \endverbatim
*>
*> \param[in] LDZ
*> \verbatim
*>          LDZ is INTEGER
*>          The leading dimension of the array Z.  LDZ >= 1, and if
*>          JOBZ = 'V', LDZ >= max(1,N).
*> \endverbatim
*>
*> \param[out] ISUPPZ
*> \verbatim
*>          ISUPPZ is INTEGER array, dimension ( 2*max(1,M) )
*>          The support of the eigenvectors in Z, i.e., the indices
*>          indicating the nonzero elements in Z. The i-th eigenvector
*>          is nonzero only in elements ISUPPZ( 2*i-1 ) through
*>          ISUPPZ( 2*i ). This is an output of DSTEMR (tridiagonal
*>          matrix). The support of the eigenvectors of A is typically
*>          1:N because of the orthogonal transformations applied by DORMTR.
*>          Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*>          WORK is DOUBLE PRECISION array, dimension (MAX(1,LWORK))
*>          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*> \endverbatim
*>
*> \param[in] LWORK
*> \verbatim
*>          LWORK is INTEGER
*>          The dimension of the array WORK.
*>          If N <= 1, LWORK >= 1, else LWORK >= 26*N.
*>          For optimal efficiency, LWORK >= (NB+6)*N,
*>          where NB is the max of the blocksize for DSYTRD and DORMTR
*>          returned by ILAENV.
*>
*>          If LWORK = -1, then a workspace query is assumed; the routine
*>          only calculates the optimal size of the WORK array, returns
*>          this value as the first entry of the WORK array, and no error
*>          message related to LWORK is issued by XERBLA.
*> \endverbatim
*>
*> \param[out] IWORK
*> \verbatim
*>          IWORK is INTEGER array, dimension (MAX(1,LIWORK))
*>          On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*> \endverbatim
*>
*> \param[in] LIWORK
*> \verbatim
*>          LIWORK is INTEGER
*>          The dimension of the array IWORK.
*>          If N <= 1, LIWORK >= 1, else LIWORK >= 10*N.
*>
*>          If LIWORK = -1, then a workspace query is assumed; the
*>          routine only calculates the optimal size of the IWORK array,
*>          returns this value as the first entry of the IWORK array, and
*>          no error message related to LIWORK is issued by XERBLA.
*> \endverbatim
*>
*> \param[out] INFO
*> \verbatim
*>          INFO is INTEGER
*>          = 0:  successful exit
*>          < 0:  if INFO = -i, the i-th argument had an illegal value
*>          > 0:  Internal error
*> \endverbatim
*
*  Authors:
*  ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \ingroup heevr
*
*> \par Contributors:
*  ==================
*>
*>     Inderjit Dhillon, IBM Almaden, USA \n
*>     Osni Marques, LBNL/NERSC, USA \n
*>     Ken Stanley, Computer Science Division, University of
*>       California at Berkeley, USA \n
*>     Jason Riedy, Computer Science Division, University of
*>       California at Berkeley, USA \n
*>
*  =====================================================================
      SUBROUTINE dsyevr( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL,
     $                   IU,
     $                   ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK,
     $                   IWORK, LIWORK, INFO )
*
*  -- LAPACK driver routine --
*  -- LAPACK is a software package provided by Univ. of Tennessee,    --
*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
*
*     .. Scalar Arguments ..
      CHARACTER          JOBZ, RANGE, UPLO
      INTEGER            IL, INFO, IU, LDA, LDZ, LIWORK, LWORK, M, N
      DOUBLE PRECISION   ABSTOL, VL, VU
*     ..
*     .. Array Arguments ..
      INTEGER            ISUPPZ( * ), IWORK( * )
      DOUBLE PRECISION   A( LDA, * ), W( * ), WORK( * ), Z( LDZ, * )
*     ..
*
* =====================================================================
*
*     .. Parameters ..
      DOUBLE PRECISION   ZERO, ONE, TWO
      PARAMETER          ( ZERO = 0.0d+0, one = 1.0d+0, two = 2.0d+0 )
*     ..
*     .. Local Scalars ..
      LOGICAL            ALLEIG, INDEIG, LOWER, LQUERY, VALEIG, WANTZ,
     $                   TRYRAC
      CHARACTER          ORDER
      INTEGER            I, IEEEOK, IINFO, IMAX, INDD, INDDD, INDE,
     $                   INDEE, INDIBL, INDIFL, INDISP, INDIWO, INDTAU,
     $                   indwk, indwkn, iscale, j, jj, liwmin,
     $                   llwork, llwrkn, lwkopt, lwmin, nb, nsplit
      DOUBLE PRECISION   ABSTLL, ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN,
     $                   SIGMA, SMLNUM, TMP1, VLL, VUU
*     ..
*     .. External Functions ..
      LOGICAL            LSAME
      INTEGER            ILAENV
      DOUBLE PRECISION   DLAMCH, DLANSY
      EXTERNAL           lsame, ilaenv, dlamch, dlansy
*     ..
*     .. External Subroutines ..
      EXTERNAL           dcopy, dormtr, dscal, dstebz, dstemr,
     $                   dstein,
     $                   dsterf, dswap, dsytrd, xerbla
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          max, min, sqrt
*     ..
*     .. Executable Statements ..
*
*     Test the input parameters.
*
      ieeeok = ilaenv( 10, 'DSYEVR', 'N', 1, 2, 3, 4 )
*
      lower = lsame( uplo, 'L' )
      wantz = lsame( jobz, 'V' )
      alleig = lsame( range, 'A' )
      valeig = lsame( range, 'V' )
      indeig = lsame( range, 'I' )
*
      lquery = ( ( lwork.EQ.-1 ) .OR. ( liwork.EQ.-1 ) )
*
      IF( n.LE.1 ) THEN
         lwmin  = 1
         liwmin = 1
      ELSE
         lwmin  = 26*n
         liwmin = 10*n
      END IF
*
      info = 0
      IF( .NOT.( wantz .OR. lsame( jobz, 'N' ) ) ) THEN
         info = -1
      ELSE IF( .NOT.( alleig .OR. valeig .OR. indeig ) ) THEN
         info = -2
      ELSE IF( .NOT.( lower .OR. lsame( uplo, 'U' ) ) ) THEN
         info = -3
      ELSE IF( n.LT.0 ) THEN
         info = -4
      ELSE IF( lda.LT.max( 1, n ) ) THEN
         info = -6
      ELSE
         IF( valeig ) THEN
            IF( n.GT.0 .AND. vu.LE.vl )
     $         info = -8
         ELSE IF( indeig ) THEN
            IF( il.LT.1 .OR. il.GT.max( 1, n ) ) THEN
               info = -9
            ELSE IF( iu.LT.min( n, il ) .OR. iu.GT.n ) THEN
               info = -10
            END IF
         END IF
      END IF
      IF( info.EQ.0 ) THEN
         IF( ldz.LT.1 .OR. ( wantz .AND. ldz.LT.n ) ) THEN
            info = -15
         ELSE IF( lwork.LT.lwmin .AND. .NOT.lquery ) THEN
            info = -18
         ELSE IF( liwork.LT.liwmin .AND. .NOT.lquery ) THEN
            info = -20
         END IF
      END IF
*
      IF( info.EQ.0 ) THEN
         nb = ilaenv( 1, 'DSYTRD', uplo, n, -1, -1, -1 )
         nb = max( nb, ilaenv( 1, 'DORMTR', uplo, n, -1, -1, -1 ) )
         lwkopt = max( ( nb+1 )*n, lwmin )
         work( 1 ) = lwkopt
         iwork( 1 ) = liwmin
      END IF
*
      IF( info.NE.0 ) THEN
         CALL xerbla( 'DSYEVR', -info )
         RETURN
      ELSE IF( lquery ) THEN
         RETURN
      END IF
*
*     Quick return if possible
*
      m = 0
      IF( n.EQ.0 ) THEN
         work( 1 ) = 1
         RETURN
      END IF
*
      IF( n.EQ.1 ) THEN
         work( 1 ) = 1
         IF( alleig .OR. indeig ) THEN
            m = 1
            w( 1 ) = a( 1, 1 )
         ELSE
            IF( vl.LT.a( 1, 1 ) .AND. vu.GE.a( 1, 1 ) ) THEN
               m = 1
               w( 1 ) = a( 1, 1 )
            END IF
         END IF
         IF( wantz ) THEN
            z( 1, 1 ) = one
            isuppz( 1 ) = 1
            isuppz( 2 ) = 1
         END IF
         RETURN
      END IF
*
*     Get machine constants.
*
      safmin = dlamch( 'Safe minimum' )
      eps = dlamch( 'Precision' )
      smlnum = safmin / eps
      bignum = one / smlnum
      rmin = sqrt( smlnum )
      rmax = min( sqrt( bignum ), one / sqrt( sqrt( safmin ) ) )
*
*     Scale matrix to allowable range, if necessary.
*
      iscale = 0
      abstll = abstol
      IF (valeig) THEN
         vll = vl
         vuu = vu
      END IF
      anrm = dlansy( 'M', uplo, n, a, lda, work )
      IF( anrm.GT.zero .AND. anrm.LT.rmin ) THEN
         iscale = 1
         sigma = rmin / anrm
      ELSE IF( anrm.GT.rmax ) THEN
         iscale = 1
         sigma = rmax / anrm
      END IF
      IF( iscale.EQ.1 ) THEN
         IF( lower ) THEN
            DO 10 j = 1, n
               CALL dscal( n-j+1, sigma, a( j, j ), 1 )
   10       CONTINUE
         ELSE
            DO 20 j = 1, n
               CALL dscal( j, sigma, a( 1, j ), 1 )
   20       CONTINUE
         END IF
         IF( abstol.GT.0 )
     $      abstll = abstol*sigma
         IF( valeig ) THEN
            vll = vl*sigma
            vuu = vu*sigma
         END IF
      END IF
 
*     Initialize indices into workspaces.  Note: The IWORK indices are
*     used only if DSTERF or DSTEMR fail.
 
*     WORK(INDTAU:INDTAU+N-1) stores the scalar factors of the
*     elementary reflectors used in DSYTRD.
      indtau = 1
*     WORK(INDD:INDD+N-1) stores the tridiagonal's diagonal entries.
      indd = indtau + n
*     WORK(INDE:INDE+N-1) stores the off-diagonal entries of the
*     tridiagonal matrix from DSYTRD.
      inde = indd + n
*     WORK(INDDD:INDDD+N-1) is a copy of the diagonal entries over
*     -written by DSTEMR (the DSTERF path copies the diagonal to W).
      inddd = inde + n
*     WORK(INDEE:INDEE+N-1) is a copy of the off-diagonal entries over
*     -written while computing the eigenvalues in DSTERF and DSTEMR.
      indee = inddd + n
*     INDWK is the starting offset of the left-over workspace, and
*     LLWORK is the remaining workspace size.
      indwk = indee + n
      llwork = lwork - indwk + 1
 
*     IWORK(INDIBL:INDIBL+M-1) corresponds to IBLOCK in DSTEBZ and
*     stores the block indices of each of the M<=N eigenvalues.
      indibl = 1
*     IWORK(INDISP:INDISP+NSPLIT-1) corresponds to ISPLIT in DSTEBZ and
*     stores the starting and finishing indices of each block.
      indisp = indibl + n
*     IWORK(INDIFL:INDIFL+N-1) stores the indices of eigenvectors
*     that corresponding to eigenvectors that fail to converge in
*     DSTEIN.  This information is discarded; if any fail, the driver
*     returns INFO > 0.
      indifl = indisp + n
*     INDIWO is the offset of the remaining integer workspace.
      indiwo = indifl + n
 
*
*     Call DSYTRD to reduce symmetric matrix to tridiagonal form.
*
      CALL dsytrd( uplo, n, a, lda, work( indd ), work( inde ),
     $             work( indtau ), work( indwk ), llwork, iinfo )
*
*     If all eigenvalues are desired
*     then call DSTERF or DSTEMR and DORMTR.
*
      IF( ( alleig .OR. ( indeig .AND. il.EQ.1 .AND. iu.EQ.n ) ) .AND.
     $    ieeeok.EQ.1 ) THEN
         IF( .NOT.wantz ) THEN
            CALL dcopy( n, work( indd ), 1, w, 1 )
            CALL dcopy( n-1, work( inde ), 1, work( indee ), 1 )
            CALL dsterf( n, w, work( indee ), info )
         ELSE
            CALL dcopy( n-1, work( inde ), 1, work( indee ), 1 )
            CALL dcopy( n, work( indd ), 1, work( inddd ), 1 )
*
            IF (abstol .LE. two*n*eps) THEN
               tryrac = .true.
            ELSE
               tryrac = .false.
            END IF
            CALL dstemr( jobz, 'A', n, work( inddd ), work( indee ),
     $                   vl, vu, il, iu, m, w, z, ldz, n, isuppz,
     $                   tryrac, work( indwk ), lwork, iwork, liwork,
     $                   info )
*
*
*
*        Apply orthogonal matrix used in reduction to tridiagonal
*        form to eigenvectors returned by DSTEMR.
*
            IF( wantz .AND. info.EQ.0 ) THEN
               indwkn = inde
               llwrkn = lwork - indwkn + 1
               CALL dormtr( 'L', uplo, 'N', n, m, a, lda,
     $                      work( indtau ), z, ldz, work( indwkn ),
     $                      llwrkn, iinfo )
            END IF
         END IF
*
*
         IF( info.EQ.0 ) THEN
*           Everything worked.  Skip DSTEBZ/DSTEIN.  IWORK(:) are
*           undefined.
            m = n
            GO TO 30
         END IF
         info = 0
      END IF
*
*     Otherwise, call DSTEBZ and, if eigenvectors are desired, DSTEIN.
*     Also call DSTEBZ and DSTEIN if DSTEMR fails.
*
      IF( wantz ) THEN
         order = 'B'
      ELSE
         order = 'E'
      END IF
 
      CALL dstebz( range, order, n, vll, vuu, il, iu, abstll,
     $             work( indd ), work( inde ), m, nsplit, w,
     $             iwork( indibl ), iwork( indisp ), work( indwk ),
     $             iwork( indiwo ), info )
*
      IF( wantz ) THEN
         CALL dstein( n, work( indd ), work( inde ), m, w,
     $                iwork( indibl ), iwork( indisp ), z, ldz,
     $                work( indwk ), iwork( indiwo ), iwork( indifl ),
     $                info )
*
*        Apply orthogonal matrix used in reduction to tridiagonal
*        form to eigenvectors returned by DSTEIN.
*
         indwkn = inde
         llwrkn = lwork - indwkn + 1
         CALL dormtr( 'L', uplo, 'N', n, m, a, lda, work( indtau ),
     $                z,
     $                ldz, work( indwkn ), llwrkn, iinfo )
      END IF
*
*     If matrix was scaled, then rescale eigenvalues appropriately.
*
*  Jump here if DSTEMR/DSTEIN succeeded.
   30 CONTINUE
      IF( iscale.EQ.1 ) THEN
         IF( info.EQ.0 ) THEN
            imax = m
         ELSE
            imax = info - 1
         END IF
         CALL dscal( imax, one / sigma, w, 1 )
      END IF
*
*     If eigenvalues are not in order, then sort them, along with
*     eigenvectors.  Note: We do not sort the IFAIL portion of IWORK.
*     It may not be initialized (if DSTEMR/DSTEIN succeeded), and we do
*     not return this detailed information to the user.
*
      IF( wantz ) THEN
         DO 50 j = 1, m - 1
            i = 0
            tmp1 = w( j )
            DO 40 jj = j + 1, m
               IF( w( jj ).LT.tmp1 ) THEN
                  i = jj
                  tmp1 = w( jj )
               END IF
   40       CONTINUE
*
            IF( i.NE.0 ) THEN
               w( i ) = w( j )
               w( j ) = tmp1
               CALL dswap( n, z( 1, i ), 1, z( 1, j ), 1 )
            END IF
   50    CONTINUE
      END IF
*
*     Set WORK(1) to optimal workspace size.
*
      work( 1 ) = lwkopt
      iwork( 1 ) = liwmin
*
      RETURN
*
*     End of DSYEVR
*
      END