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NAG Toolbox: nag_lapack_dsyev (f08fa)
Purpose
nag_lapack_dsyev (f08fa) computes all the eigenvalues and, optionally, all the eigenvectors of a real by symmetric matrix .
Syntax
Description
The symmetric matrix is first reduced to tridiagonal form, using orthogonal similarity transformations, and then the 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:
– string (length ≥ 1)
-
Indicates whether eigenvectors are computed.
- Only eigenvalues are computed.
- Eigenvalues and eigenvectors are computed.
Constraint:
or .
- 2:
– string (length ≥ 1)
-
If
, the upper triangular part of
is stored.
If , the lower triangular part of is stored.
Constraint:
or .
- 3:
– double array
-
The first dimension of the array
a must be at least
.
The second dimension of the array
a must be at least
.
The
by
symmetric matrix
.
- If , the upper triangular part of must be stored and the elements of the array below the diagonal are not referenced.
- If , the lower triangular part of must be stored and the elements of the array above the diagonal are not referenced.
Optional Input Parameters
- 1:
– 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.)
, the order of the matrix .
Constraint:
.
Output Parameters
- 1:
– double array
-
The first dimension of the array
a will be
.
The second dimension of the array
a will be
.
If
, then
a contains the orthonormal eigenvectors of the matrix
.
If
, then on exit the lower triangle (if
) or the upper triangle (if
) of
a, including the diagonal, is overwritten.
- 2:
– double array
-
The eigenvalues in ascending order.
- 3:
– int64int32nag_int scalar
unless the function detects an error (see
Error Indicators and Warnings).
Error Indicators and Warnings
-
If , parameter 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.
-
-
If , the algorithm failed to converge; 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
, where
and
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 .
The complex analogue of this function is
nag_lapack_zheev (f08fn).
Example
This example finds all the eigenvalues and eigenvectors of the symmetric matrix
together with approximate error bounds for the computed eigenvalues and eigenvectors.
Open in the MATLAB editor:
f08fa_example
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));
jobz = 'Vectors';
uplo = 'Upper';
[v, w, info] = f08fa( ...
jobz, uplo, a);
disp('Eigenvectors');
disp(v);
errbnd = x02aj*max(abs(w(1)),abs(w(end)));
[rcondz, info] = f08fl( ...
'Eigenvectors', n, n, w);
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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