nag_zheevr (f08frc) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG C Library Manual

NAG Library Function Document

nag_zheevr (f08frc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_zheevr (f08frc) computes selected eigenvalues and, optionally, eigenvectors of a complex n by n 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.

2  Specification

#include <nag.h>
#include <nagf08.h>
void  nag_zheevr (Nag_OrderType order, Nag_JobType job, Nag_RangeType range, Nag_UploType uplo, Integer n, Complex a[], Integer pda, double vl, double vu, Integer il, Integer iu, double abstol, Integer *m, double w[], Complex z[], Integer pdz, Integer isuppz[], NagError *fail)

3  Description

The Hermitian matrix is first reduced to a real tridiagonal matrix T, using unitary similarity transformations. Then whenever possible, nag_zheevr (f08frc) computes the eigenspectrum using Relatively Robust Representations. nag_zheevr (f08frc) computes eigenvalues by the dqds algorithm, while orthogonal eigenvectors are computed from various ‘good’ LDLT representations (also known as Relatively Robust Representations). Gram–Schmidt orthogonalisation is avoided as far as possible. More specifically, the various steps of the algorithm are as follows. For the ith unreduced block of T:
(a) compute T - σi I = Li Di LiT , such that Li Di LiT  is a relatively robust representation,
(b) compute the eigenvalues, λj, of Li Di LiT  to high relative accuracy by the dqds algorithm,
(c) if there is a cluster of close eigenvalues, ‘choose’ σi close to the cluster, and go to (a),
(d) given the approximate eigenvalue λj of Li Di LiT , compute the corresponding eigenvector by forming a rank-revealing twisted factorization.
The desired accuracy of the output can be specified by the argument abstol. For more details, see Dhillon (1997) and Parlett and Dhillon (2000).

4  References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug
Barlow J and Demmel J W (1990) Computing accurate eigensystems of scaled diagonally dominant matrices SIAM J. Numer. Anal. 27 762–791
Demmel J W and Kahan W (1990) Accurate singular values of bidiagonal matrices SIAM J. Sci. Statist. Comput. 11 873–912
Dhillon I (1997) A new On2 algorithm for the symmetric tridiagonal eigenvalue/eigenvector problem Computer Science Division Technical Report No. UCB//CSD-97-971 UC Berkeley
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Parlett B N and Dhillon I S (2000) Relatively robust representations of symmetric tridiagonals Linear Algebra Appl. 309 121–151

5  Arguments

1:     orderNag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by order=Nag_RowMajor. See Section 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     jobNag_JobTypeInput
On entry: indicates whether eigenvectors are computed.
job=Nag_EigVals
Only eigenvalues are computed.
job=Nag_DoBoth
Eigenvalues and eigenvectors are computed.
Constraint: job=Nag_EigVals or Nag_DoBoth.
3:     rangeNag_RangeTypeInput
On entry: if range=Nag_AllValues, all eigenvalues will be found.
If range=Nag_Interval, all eigenvalues in the half-open interval vl,vu will be found.
If range=Nag_Indices, the ilth to iuth eigenvalues will be found.
For range=Nag_Interval or Nag_Indices and iu-il<n-1, nag_dstebz (f08jjc) and nag_zstein (f08jxc) are called.
Constraint: range=Nag_AllValues, Nag_Interval or Nag_Indices.
4:     uploNag_UploTypeInput
On entry: if uplo=Nag_Upper, the upper triangular part of A is stored.
If uplo=Nag_Lower, the lower triangular part of A is stored.
Constraint: uplo=Nag_Upper or Nag_Lower.
5:     nIntegerInput
On entry: n, the order of the matrix A.
Constraint: n0.
6:     a[dim]ComplexInput/Output
Note: the dimension, dim, of the array a must be at least max1,pda×n.
On entry: the n by n Hermitian matrix A.
If order=Nag_ColMajor, Aij is stored in a[j-1×pda+i-1].
If order=Nag_RowMajor, Aij is stored in a[i-1×pda+j-1].
If uplo=Nag_Upper, the upper triangular part of A must be stored and the elements of the array below the diagonal are not referenced.
If uplo=Nag_Lower, the lower triangular part of A must be stored and the elements of the array above the diagonal are not referenced.
On exit: the lower triangle (if uplo=Nag_Lower) or the upper triangle (if uplo=Nag_Upper) of a, including the diagonal, is overwritten.
7:     pdaIntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraint: pdamax1,n.
8:     vldoubleInput
9:     vudoubleInput
On entry: if range=Nag_Interval, the lower and upper bounds of the interval to be searched for eigenvalues.
If range=Nag_AllValues or Nag_Indices, vl and vu are not referenced.
Constraint: if range=Nag_Interval, vl<vu.
10:   ilIntegerInput
11:   iuIntegerInput
On entry: if range=Nag_Indices, the indices (in ascending order) of the smallest and largest eigenvalues to be returned.
If range=Nag_AllValues or Nag_Interval, il and iu are not referenced.
Constraints:
  • if range=Nag_Indices and n=0, il=1 and iu=0;
  • if range=Nag_Indices and n>0, 1 il iu n .
12:   abstoldoubleInput
On entry: 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+ε maxa,b ,
where ε  is the machine precision. If abstol is less than or equal to zero, then ε T1  will be used in its place, where T is the real tridiagonal matrix obtained by reducing A to tridiagonal form. See Demmel and Kahan (1990).
If high relative accuracy is important, set abstol to nag_real_safe_small_number  , although doing so does not currently guarantee that eigenvalues are computed to high relative accuracy. See Barlow and Demmel (1990) for a discussion of which matrices can define their eigenvalues to high relative accuracy.
13:   mInteger *Output
On exit: the total number of eigenvalues found. 0mn.
If range=Nag_AllValues, m=n.
If range=Nag_Indices, m=iu-il+1.
14:   w[dim]doubleOutput
Note: the dimension, dim, of the array w must be at least max1,n.
On exit: the first m elements contain the selected eigenvalues in ascending order.
15:   z[dim]ComplexOutput
Note: the dimension, dim, of the array z must be at least
  • max1,pdz×n when job=Nag_DoBoth;
  • 1 otherwise.
The i,jth element of the matrix Z is stored in
  • z[j-1×pdz+i-1] when order=Nag_ColMajor;
  • z[i-1×pdz+j-1] when order=Nag_RowMajor.
On exit: if job=Nag_DoBoth, the first m columns of Z contain the orthonormal eigenvectors of the matrix A corresponding to the selected eigenvalues, with the ith column of Z holding the eigenvector associated with w[i-1].
If job=Nag_EigVals, z is not referenced.
16:   pdzIntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array z.
Constraints:
  • if job=Nag_DoBoth, pdz max1,n ;
  • otherwise pdz1.
17:   isuppz[dim]IntegerOutput
Note: the dimension, dim, of the array isuppz must be at least max1,2×m.
On exit: the support of the eigenvectors in z, i.e., the indices indicating the nonzero elements in z. The ith eigenvector is nonzero only in elements isuppz[2×i-2] through isuppz[2×i-1]. Implemented only for range=Nag_AllValues or Nag_Indices and iu-il=n-1.
18:   failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_CONVERGENCE
nag_zheevr (f08frc) failed to converge.
NE_ENUM_INT_2
On entry, job=value, pdz=value and n=value.
Constraint: if job=Nag_DoBoth, pdz max1,n ;
otherwise pdz1.
NE_ENUM_INT_3
On entry, range=value, il=value, iu=value and n=value.
Constraint: if range=Nag_Indices and n=0, il=1 and iu=0;
if range=Nag_Indices and n>0, 1 il iu n .
NE_ENUM_REAL_2
On entry, range=value, vl=value and vu=value.
Constraint: if range=Nag_Interval, vl<vu.
NE_INT
On entry, n=value.
Constraint: n0.
On entry, pda=value.
Constraint: pda>0.
On entry, pdz=value.
Constraint: pdz>0.
NE_INT_2
On entry, pda=value and n=value.
Constraint: pdamax1,n.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.

7  Accuracy

The computed eigenvalues and eigenvectors are exact for a nearby matrix A+E, where
E2 = Oε A2 ,
and ε is the machine precision. See Section 4.7 of Anderson et al. (1999) for further details.

8  Further Comments

The total number of floating point operations is proportional to n3.
The real analogue of this function is nag_dsyevr (f08fdc).

9  Example

This example finds the eigenvalues with indices in the range 2,3 , and the corresponding eigenvectors, of the Hermitian matrix
A = 1 2-i 3-i 4-i 2+i 2 3-2i 4-2i 3+i 3+2i 3 4-3i 4+i 4+2i 4+3i 4 .

9.1  Program Text

Program Text (f08frce.c)

9.2  Program Data

Program Data (f08frce.d)

9.3  Program Results

Program Results (f08frce.r)


nag_zheevr (f08frc) (PDF version)
f08 Chapter Contents
f08 Chapter Introduction
NAG C Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012