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CHEEVR(1)	      LAPACK driver routine (version 3.2)	     CHEEVR(1)

NAME
       CHEEVR - computes selected eigenvalues and, optionally, eigenvectors of
       a complex Hermitian matrix A

SYNOPSIS
       SUBROUTINE CHEEVR( JOBZ, RANGE, UPLO,  N,  A,  LDA,  VL,	 VU,  IL,  IU,
			  ABSTOL,  M,  W,  Z, LDZ, ISUPPZ, WORK, LWORK, RWORK,
			  LRWORK, IWORK, LIWORK, INFO )

	   CHARACTER	  JOBZ, RANGE, UPLO

	   INTEGER	  IL, INFO, IU, LDA, LDZ, LIWORK, LRWORK, LWORK, M, N

	   REAL		  ABSTOL, VL, VU

	   INTEGER	  ISUPPZ( * ), IWORK( * )

	   REAL		  RWORK( * ), W( * )

	   COMPLEX	  A( LDA, * ), WORK( * ), Z( LDZ, * )

PURPOSE
       CHEEVR computes selected eigenvalues and, optionally, eigenvectors of a
       complex	Hermitian  matrix  A.	Eigenvalues  and  eigenvectors	can be
       selected by specifying either a range of values or a range  of  indices
       for the desired eigenvalues.
       CHEEVR  first reduces the matrix A to tridiagonal form T with a call to
       CHETRD.	Then, whenever possible, CHEEVR calls CSTEMR  to  compute  the
       eigenspectrum using Relatively Robust Representations.  CSTEMR 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 com‐
       pute
	      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 representa‐
       tions
	 to compute orthogonal eigenvectors of	symmetric  tridiagonal	matri‐
       ces,"
	 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	:  CHEEVR  calls CSTEMR when the full spectrum is requested on
       machines which conform to the ieee-754 floating point standard.	CHEEVR
       calls SSTEBZ and CSTEIN on non-ieee machines and
       when partial spectrum requests are made.
       Normal execution of CSTEMR 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.

ARGUMENTS
       JOBZ    (input) CHARACTER*1
	       = 'N':  Compute eigenvalues only;
	       = 'V':  Compute eigenvalues and eigenvectors.

       RANGE   (input) 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.

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

       N       (input) INTEGER
	       The order of the matrix A.  N >= 0.

       A       (input/output) COMPLEX array, dimension (LDA, N)
	       On  entry,  the Hermitian 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     (input) INTEGER
	       The leading dimension of the array A.  LDA >= max(1,N).

       VL      (input) REAL
	       VU	(input)	 REAL 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      (input) INTEGER
	       IU      (input) 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  (input) REAL
	       The absolute error tolerance for the eigenvalues.  An  approxi‐
	       mate  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 pre‐
	       cision.	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 impor‐
	       tant, set ABSTOL to SLAMCH( 'Safe minimum' ).   Doing  so  will
	       guarantee  that eigenvalues are computed to high relative accu‐
	       racy when possible in future releases.  The current  code  does
	       not  make  any  guarantees  about  high	relative accuracy, but
	       furutre 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       (output) INTEGER
	       The  total number of eigenvalues found.	0 <= M <= N.  If RANGE
	       = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.

       W       (output) REAL array, dimension (N)
	       The first  M  elements  contain	the  selected  eigenvalues  in
	       ascending order.

       Z       (output) COMPLEX array, dimension (LDZ, max(1,M))
	       If  JOBZ = 'V', then if INFO = 0, the first M columns of Z con‐
	       tain 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.

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

       ISUPPZ  (output) INTEGER array, dimension ( 2*max(1,M) )
	       The  support  of the eigenvectors in Z, i.e., the indices indi‐
	       cating the nonzero elements  in	Z.  The	 i-th  eigenvector  is
	       nonzero only in elements ISUPPZ( 2*i-1 ) through ISUPPZ( 2*i ).

       WORK    (workspace/output) COMPLEX array, dimension (MAX(1,LWORK))
	       On exit, if INFO = 0, WORK(1) returns the optimal LWORK.

       LWORK   (input) INTEGER
	       The  length of the array WORK.  LWORK >= max(1,2*N).  For opti‐
	       mal efficiency, LWORK >= (NB+1)*N, where NB is the max  of  the
	       blocksize  for CHETRD and for CUNMTR as returned by ILAENV.  If
	       LWORK = -1, then a workspace query is assumed; the routine only
	       calculates  the	optimal	 sizes	of  the	 WORK, RWORK and IWORK
	       arrays, returns these values as the first entries of the	 WORK,
	       RWORK  and  IWORK arrays, and no error message related to LWORK
	       or LRWORK or LIWORK is issued by XERBLA.

       RWORK   (workspace/output) REAL array, dimension (MAX(1,LRWORK))
	       On exit, if INFO = 0, RWORK(1) returns the optimal  (and	 mini‐
	       mal)  LRWORK.   The  length  of	the  array  RWORK.   LRWORK >=
	       max(1,24*N).  If	 LRWORK	 =  -1,	 then  a  workspace  query  is
	       assumed;	 the  routine only calculates the optimal sizes of the
	       WORK, RWORK and IWORK arrays, returns these values as the first
	       entries	of the WORK, RWORK and IWORK arrays, and no error mes‐
	       sage related to LWORK or LRWORK or LIWORK is issued by XERBLA.

       IWORK   (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
	       On exit, if INFO = 0, IWORK(1) returns the optimal  (and	 mini‐
	       mal)  LIWORK.   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 sizes of the
	       WORK, RWORK and IWORK arrays, returns these values as the first
	       entries	of the WORK, RWORK and IWORK arrays, and no error mes‐
	       sage related to LWORK or LRWORK or LIWORK is issued by XERBLA.

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

FURTHER DETAILS
       Based on contributions by
	  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

 LAPACK driver routine (version 3November 2008			     CHEEVR(1)
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