dstemr.f(3)

NAME
dstemr.f -

SYNOPSIS

  Functions/Subroutines
subroutine dstemr (JOBZ, RANGE, N, D, E, VL, VU, IL, IU, M, W, Z, LDZ, NZC, ISUPPZ, TRYRAC, WORK, LWORK, IWORK, LIWORK, INFO)
DSTEMR

Function/Subroutine Documentation

  subroutine dstemr (characterJOBZ, characterRANGE, integerN, double precision, dimension( * )D, double precision, dimension( * )E, double precisionVL, double precisionVU, integerIL, integerIU, integerM, double precision, dimension( * )W, double precision, dimension( ldz, * )Z, integerLDZ, integerNZC, integer, dimension( * )ISUPPZ, logicalTRYRAC, double precision, dimension( * )WORK, integerLWORK, integer, dimension( * )IWORK, integerLIWORK, integerINFO)

DSTEMR

Purpose:

     DSTEMR computes selected eigenvalues and, optionally, eigenvectors
     of a real symmetric tridiagonal matrix T. Any such unreduced matrix has
     a well defined set of pairwise different real eigenvalues, the corresponding
     real eigenvectors are pairwise orthogonal.
     The spectrum may be computed either completely or partially by specifying
     either an interval (VL,VU] or a range of indices IL:IU for the desired
     eigenvalues.
     Depending on the number of desired eigenvalues, these are computed either
     by bisection or the dqds algorithm. Numerically orthogonal eigenvectors are
     computed by the use of various suitable L D L^T factorizations near clusters
     of close eigenvalues (referred to as RRRs, Relatively Robust
     Representations). An informal sketch of the algorithm 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.
     For more details, see:
     - 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.
     Further Details
     1.DSTEMR works only on machines which follow IEEE-754
     floating-point standard in their handling of infinities and NaNs.
     This permits the use of efficient inner loops avoiding a check for
     zero divisors.

Parameters:
    JOBZ

              JOBZ is CHARACTER*1
              = 'N':  Compute eigenvalues only;
              = 'V':  Compute eigenvalues and eigenvectors.

    RANGE

              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.

    N

              N is INTEGER
              The order of the matrix.  N >= 0.

    D

              D is DOUBLE PRECISION array, dimension (N)
              On entry, the N diagonal elements of the tridiagonal matrix
              T. On exit, D is overwritten.

    E

              E is DOUBLE PRECISION array, dimension (N)
              On entry, the (N-1) subdiagonal elements of the tridiagonal
              matrix T in elements 1 to N-1 of E. E(N) need not be set on
              input, but is used internally as workspace.
              On exit, E is overwritten.

    VL

              VL is DOUBLE PRECISION

    VU

              VU is DOUBLE PRECISION
              If RANGE='V', the lower and upper bounds of the interval to
              be searched for eigenvalues. VL < VU.
              Not referenced if RANGE = 'A' or 'I'.

    IL

              IL is INTEGER

    IU

              IU is INTEGER
              If RANGE='I', the indices (in ascending order) of the
              smallest and largest eigenvalues to be returned.
              1 <= IL <= IU <= N, if N > 0.
              Not referenced if RANGE = 'A' or 'V'.

    M

              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.

    W

              W is DOUBLE PRECISION array, dimension (N)
              The first M elements contain the selected eigenvalues in
              ascending order.

    Z

              Z is DOUBLE PRECISION array, dimension (LDZ, max(1,M) )
              If JOBZ = 'V', and if INFO = 0, then the first M columns of Z
              contain the orthonormal eigenvectors of the matrix T
              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 can be computed with a workspace
              query by setting NZC = -1, see below.

    LDZ

              LDZ is INTEGER
              The leading dimension of the array Z.  LDZ >= 1, and if
              JOBZ = 'V', then LDZ >= max(1,N).

    NZC

              NZC is INTEGER
              The number of eigenvectors to be held in the array Z.
              If RANGE = 'A', then NZC >= max(1,N).
              If RANGE = 'V', then NZC >= the number of eigenvalues in (VL,VU].
              If RANGE = 'I', then NZC >= IU-IL+1.
              If NZC = -1, then a workspace query is assumed; the
              routine calculates the number of columns of the array Z that
              are needed to hold the eigenvectors.
              This value is returned as the first entry of the Z array, and
              no error message related to NZC is issued by XERBLA.

    ISUPPZ

              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 computed eigenvector
              is nonzero only in elements ISUPPZ( 2*i-1 ) through
              ISUPPZ( 2*i ). This is relevant in the case when the matrix
              is split. ISUPPZ is only accessed when JOBZ is 'V' and N > 0.

    TRYRAC

              TRYRAC is LOGICAL
              If TRYRAC.EQ..TRUE., indicates that the code should check whether
              the tridiagonal matrix defines its eigenvalues to high relative
              accuracy.  If so, the code uses relative-accuracy preserving
              algorithms that might be (a bit) slower depending on the matrix.
              If the matrix does not define its eigenvalues to high relative
              accuracy, the code can uses possibly faster algorithms.
              If TRYRAC.EQ..FALSE., the code is not required to guarantee
              relatively accurate eigenvalues and can use the fastest possible
              techniques.
              On exit, a .TRUE. TRYRAC will be set to .FALSE. if the matrix
              does not define its eigenvalues to high relative accuracy.

    WORK

              WORK is DOUBLE PRECISION array, dimension (LWORK)
              On exit, if INFO = 0, WORK(1) returns the optimal
              (and minimal) LWORK.

    LWORK

              LWORK is INTEGER
              The dimension of the array WORK. LWORK >= max(1,18*N)
              if JOBZ = 'V', and LWORK >= max(1,12*N) if JOBZ = 'N'.
              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.

    IWORK

              IWORK is INTEGER array, dimension (LIWORK)
              On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.

    LIWORK

              LIWORK is INTEGER
              The dimension of the array IWORK.  LIWORK >= max(1,10*N)
              if the eigenvectors are desired, and LIWORK >= max(1,8*N)
              if only the eigenvalues are to be computed.
              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.

    INFO

              INFO is INTEGER
              On exit, INFO
              = 0:  successful exit
              < 0:  if INFO = -i, the i-th argument had an illegal value
              > 0:  if INFO = 1X, internal error in DLARRE,
                    if INFO = 2X, internal error in DLARRV.
                    Here, the digit X = ABS( IINFO ) < 10, where IINFO is
                    the nonzero error code returned by DLARRE or
                    DLARRV, respectively.

Author:
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Date:
    September 2012

Contributors:
    Beresford Parlett, University of California, Berkeley, USA
     Jim Demmel, University of California, Berkeley, USA
     Inderjit Dhillon, University of Texas, Austin, USA
     Osni Marques, LBNL/NERSC, USA
     Christof Voemel, University of California, Berkeley, USA

Definition at line 311 of file dstemr.f.

Author

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