dsyevr.f(3)

NAME
dsyevr.f -

SYNOPSIS

  Functions/Subroutines
subroutine dsyevr (JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO)
DSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices

Function/Subroutine Documentation

  subroutine dsyevr (characterJOBZ, characterRANGE, characterUPLO, integerN, double precision, dimension( lda, * )A, integerLDA, double precisionVL, double precisionVU, integerIL, integerIU, double precisionABSTOL, integerM, double precision, dimension( * )W, double precision, dimension( ldz, * )Z, integerLDZ, integer, dimension( * )ISUPPZ, double precision, dimension( * )WORK, integerLWORK, integer, dimension( * )IWORK, integerLIWORK, integerINFO)

DSYEVR computes the eigenvalues and, optionally, the left and/or right eigenvectors for SY matrices

Purpose:

     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.
     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 SSTEIN 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.

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.
              For RANGE = 'V' or 'I' and IU - IL < N - 1, DSTEBZ and
              DSTEIN are called

    UPLO

              UPLO is CHARACTER*1
              = 'U':  Upper triangle of A is stored;
              = 'L':  Lower triangle of A is stored.

    N

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

    A

              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.

    LDA

              LDA is INTEGER
              The leading dimension of the array A.  LDA >= max(1,N).

    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; IL = 1 and IU = 0 if N = 0.
              Not referenced if RANGE = 'A' or 'V'.

    ABSTOL

              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.

    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', 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.

    LDZ

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

    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 eigenvector
              is nonzero only in elements ISUPPZ( 2*i-1 ) through
              ISUPPZ( 2*i ).
              Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1

    WORK

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

    LWORK

              LWORK is INTEGER
              The dimension of the array WORK.  LWORK >= max(1,26*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.

    IWORK

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

    LIWORK

              LIWORK is INTEGER
              The dimension of the array IWORK.  LIWORK >= max(1,10*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.

    INFO

              INFO is INTEGER
              = 0:  successful exit
              < 0:  if INFO = -i, the i-th argument had an illegal value
              > 0:  Internal error

Author:
    Univ. of Tennessee

    Univ. of California Berkeley

    Univ. of Colorado Denver

    NAG Ltd.

Date:
    September 2012

Contributors:
    Inderjit Dhillon, IBM Almaden, USA
     Osni Marques, LBNL/NERSC, USA
     Ken Stanley, Computer Science Division, University of California at Berkeley, USA
     Jason Riedy, Computer Science Division, University of California at Berkeley, USA

Definition at line 324 of file dsyevr.f.

Author

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