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Chapter Introduction
NAG Toolbox

NAG Toolbox: nag_lapack_dsyev (f08fa)

 Contents

    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example

Purpose

nag_lapack_dsyev (f08fa) computes all the eigenvalues and, optionally, all the eigenvectors of a real n by n symmetric matrix A.

Syntax

[a, w, info] = f08fa(jobz, uplo, a, 'n', n)
[a, w, info] = nag_lapack_dsyev(jobz, uplo, a, 'n', n)

Description

The symmetric matrix A is first reduced to tridiagonal form, using orthogonal similarity transformations, and then the QR algorithm is applied to the tridiagonal matrix to compute the eigenvalues and (optionally) the eigenvectors.

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
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

Parameters

Compulsory Input Parameters

1:     jobz – string (length ≥ 1)
Indicates whether eigenvectors are computed.
jobz='N'
Only eigenvalues are computed.
jobz='V'
Eigenvalues and eigenvectors are computed.
Constraint: jobz='N' or 'V'.
2:     uplo – string (length ≥ 1)
If uplo='U', the upper triangular part of A is stored.
If uplo='L', the lower triangular part of A is stored.
Constraint: uplo='U' or 'L'.
3:     alda: – double array
The first dimension of the array a must be at least max1,n.
The second dimension of the array a must be at least max1,n.
The n by n symmetric matrix A.
  • If uplo='U', the upper triangular part of a must be stored and the elements of the array below the diagonal are not referenced.
  • If uplo='L', the lower triangular part of a must be stored and the elements of the array above the diagonal are not referenced.

Optional Input Parameters

1:     n int64int32nag_int scalar
Default: the first dimension of the array a and the second dimension of the array a. (An error is raised if these dimensions are not equal.)
n, the order of the matrix A.
Constraint: n0.

Output Parameters

1:     alda: – double array
The first dimension of the array a will be max1,n.
The second dimension of the array a will be max1,n.
If jobz='V', then a contains the orthonormal eigenvectors of the matrix A.
If jobz='N', then on exit the lower triangle (if uplo='L') or the upper triangle (if uplo='U') of a, including the diagonal, is overwritten.
2:     wn – double array
The eigenvalues in ascending order.
3:     info int64int32nag_int scalar
info=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

   info=-i
If info=-i, parameter i had an illegal value on entry. The parameters are numbered as follows:
1: jobz, 2: uplo, 3: n, 4: a, 5: lda, 6: w, 7: work, 8: lwork, 9: info.
It is possible that info refers to a parameter that is omitted from the MATLAB interface. This usually indicates that an error in one of the other input parameters has caused an incorrect value to be inferred.
   info>0
If info=i, the algorithm failed to converge; i off-diagonal elements of an intermediate tridiagonal form did not converge to zero.

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.

Further Comments

The total number of floating-point operations is proportional to n3.
The complex analogue of this function is nag_lapack_zheev (f08fn).

Example

This example finds all the eigenvalues and eigenvectors of the symmetric matrix
A = 1 2 3 4 2 2 3 4 3 3 3 4 4 4 4 4 ,  
together with approximate error bounds for the computed eigenvalues and eigenvectors.
function f08fa_example


fprintf('f08fa example results\n\n');

a = [1, 2, 3, 4;
     0, 2, 3, 4;
     0, 0, 3, 4;
     0, 0, 0, 4];
n = int64(size(a,1));

% Eigenvalues and eogenvectors of upper triangular A
jobz = 'Vectors';
uplo = 'Upper';
[v, w, info] = f08fa( ...
		      jobz, uplo, a);

disp('Eigenvectors');
disp(v);

% Eigenvalue error bound
errbnd = x02aj*max(abs(w(1)),abs(w(end)));
% Eigenvector condition numbers
[rcondz, info] = f08fl( ...
		        'Eigenvectors', n, n, w);

% Eigenvector error bounds
zerrbd = errbnd./rcondz;

disp('Error estimate for the eigenvalues');
fprintf('%12.1e\n',errbnd);
disp('Error estimates for the eigenvectors');
fprintf('%12.1e',zerrbd);
fprintf('\n');


f08fa example results

Eigenvectors
    0.7003   -0.5144    0.2767    0.4103
    0.3592    0.4851   -0.6634    0.4422
   -0.1569    0.5420    0.6504    0.5085
   -0.5965   -0.4543   -0.2457    0.6144

Error estimate for the eigenvalues
     1.4e-15
Error estimates for the eigenvectors
     9.3e-16     6.5e-15     6.5e-15     1.1e-16

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