PDF version (NAG web site
, 64-bit version, 64-bit version)
NAG Toolbox: nag_lapack_zhegvx (f08sp)
Purpose
nag_lapack_zhegvx (f08sp) computes selected eigenvalues and, optionally, eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form
where
and
are Hermitian and
is also positive definite. Eigenvalues and eigenvectors can be selected by specifying either a range of values or a range of indices for the desired eigenvalues.
Syntax
[
a,
b,
m,
w,
z,
jfail,
info] = f08sp(
itype,
jobz,
range,
uplo,
a,
b,
vl,
vu,
il,
iu,
abstol, 'n',
n)
[
a,
b,
m,
w,
z,
jfail,
info] = nag_lapack_zhegvx(
itype,
jobz,
range,
uplo,
a,
b,
vl,
vu,
il,
iu,
abstol, 'n',
n)
Description
nag_lapack_zhegvx (f08sp) first performs a Cholesky factorization of the matrix
as
, when
or
, when
. The generalized problem is then reduced to a standard symmetric eigenvalue problem
which is solved for the desired eigenvalues and eigenvectors; the eigenvectors are then backtransformed to give the eigenvectors of the original problem.
For the problem
, the eigenvectors are normalized so that the matrix of eigenvectors,
, satisfies
where
is the diagonal matrix whose diagonal elements are the eigenvalues. For the problem
we correspondingly have
and for
we have
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
Demmel J W and Kahan W (1990) Accurate singular values of bidiagonal matrices SIAM J. Sci. Statist. Comput. 11 873–912
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Parameters
Compulsory Input Parameters
- 1:
– int64int32nag_int scalar
-
Specifies the problem type to be solved.
- .
- .
- .
Constraint:
, or .
- 2:
– string (length ≥ 1)
-
Indicates whether eigenvectors are computed.
- Only eigenvalues are computed.
- Eigenvalues and eigenvectors are computed.
Constraint:
or .
- 3:
– string (length ≥ 1)
-
If
, all eigenvalues will be found.
If , all eigenvalues in the half-open interval will be found.
If
, the
ilth to
iuth eigenvalues will be found.
Constraint:
, or .
- 4:
– string (length ≥ 1)
-
If
, the upper triangles of
and
are stored.
If , the lower triangles of and are stored.
Constraint:
or .
- 5:
– complex 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
Hermitian 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.
- 6:
– complex array
-
The first dimension of the array
b must be at least
.
The second dimension of the array
b must be at least
.
The
by
Hermitian 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.
- 7:
– double scalar
- 8:
– double scalar
-
If
, the lower and upper bounds of the interval to be searched for eigenvalues.
If
or
,
vl and
vu are not referenced.
Constraint:
if , .
- 9:
– int64int32nag_int scalar
- 10:
– int64int32nag_int scalar
-
If
, the indices (in ascending order) of the smallest and largest eigenvalues to be returned.
If
or
,
il and
iu are not referenced.
Constraints:
- if and , and ;
- if and , .
- 11:
– double scalar
-
The absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval
of width less than or equal to
where
is the
machine precision. If
abstol is less than or equal to zero, then
will be used in its place, where
is the tridiagonal matrix obtained by reducing
to tridiagonal form. Eigenvalues will be computed most accurately when
abstol is set to twice the underflow threshold
, not zero. If this function returns with
, indicating that some eigenvectors did not converge, try setting
abstol to
. See
Demmel and Kahan (1990).
Optional Input Parameters
- 1:
– int64int32nag_int scalar
-
Default:
the first dimension of the arrays
a,
b and the second dimension of the arrays
a,
b. (An error is raised if these dimensions are not equal.)
, the order of the matrices and .
Constraint:
.
Output Parameters
- 1:
– complex array
-
The first dimension of the array
a will be
.
The second dimension of the array
a will be
.
The lower triangle (if
) or the upper triangle (if
) of
a, including the diagonal, is overwritten.
- 2:
– complex array
-
The first dimension of the array
b will be
.
The second dimension of the array
b will be
.
The triangular factor or from the Cholesky factorization or .
- 3:
– int64int32nag_int scalar
-
The total number of eigenvalues found.
.
If , .
If , .
- 4:
– double array
-
The first
m elements contain the selected eigenvalues in ascending order.
- 5:
– complex array
-
The first dimension,
, of the array
z will be
- if , ;
- otherwise .
The second dimension of the array
z will be
if
and
otherwise.
If
, then
- if , the first m columns of contain the orthonormal eigenvectors of the matrix corresponding to the selected eigenvalues, with the th column of holding the eigenvector associated with . The eigenvectors are normalized as follows:
- if or , ;
- if , ;
- if an eigenvector fails to converge (), then that column of contains the latest approximation to the eigenvector, and the index of the eigenvector is returned in jfail.
If
,
z is not referenced.
- 6:
– int64int32nag_int array
-
The dimension of the array
jfail will be
If
, then
- if , the first m elements of jfail are zero;
- if , jfail contains the indices of the eigenvectors that failed to converge.
If
,
jfail is not referenced.
- 7:
– int64int32nag_int scalar
unless the function detects an error (see
Error Indicators and Warnings).
Error Indicators and Warnings
Cases prefixed with W are classified as warnings and
do not generate an error of type NAG:error_n. See nag_issue_warnings.
-
If , parameter had an illegal value on entry. The parameters are numbered as follows:
1:
itype, 2:
jobz, 3:
range, 4:
uplo, 5:
n, 6:
a, 7:
lda, 8:
b, 9:
ldb, 10:
vl, 11:
vu, 12:
il, 13:
iu, 14:
abstol, 15:
m, 16:
w, 17:
z, 18:
ldz, 19:
work, 20:
lwork, 21:
rwork, 22:
iwork, 23:
jfail, 24:
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.
- W
-
If
,
nag_lapack_zheevx (f08fp) failed to converge;
eigenvectors failed to converge. Their indices are stored in array
jfail.
-
-
nag_lapack_zpotrf (f07fr) returned an error code; i.e., if
, for
, then the leading minor of order
of
is not positive definite. The factorization of
could not be completed and no eigenvalues or eigenvectors were computed.
Accuracy
If
is ill-conditioned with respect to inversion, then the error bounds for the computed eigenvalues and vectors may be large, although when the diagonal elements of
differ widely in magnitude the eigenvalues and eigenvectors may be less sensitive than the condition of
would suggest. See Section 4.10 of
Anderson et al. (1999) for details of the error bounds.
Further Comments
The total number of floating-point operations is proportional to .
The real analogue of this function is
nag_lapack_dsygvx (f08sb).
Example
This example finds the eigenvalues in the half-open interval
, and corresponding eigenvectors, of the generalized Hermitian eigenproblem
, where
and
The example program for
nag_lapack_zhegvd (f08sq) illustrates solving a generalized Hermitian eigenproblem of the form
.
Open in the MATLAB editor:
f08sp_example
function f08sp_example
fprintf('f08sp example results\n\n');
uplo = 'Upper';
n = 4;
a = [-7.36 + 0i, 0.77 - 0.43i, -0.64 - 0.92i, 3.01 - 6.97i;
0 + 0i, 3.49 + 0i, 2.19 + 4.45i, 1.90 + 3.73i;
0 + 0i, 0 + 0i, 0.12 + 0i, 2.88 - 3.17i;
0 + 0i, 0 + 0i, 0 + 0i, -2.54 + 0i];
b = [ 3.23 + 0i, 1.51 - 1.92i, 1.90 + 0.84i, 0.42 + 2.5i;
0 + 0i, 3.58 + 0i, -0.23 + 1.11i, -1.18 + 1.37i;
0 + 0i, 0 + 0i, 4.09 + 0i, 2.33 - 0.14i;
0 + 0i, 0 + 0i, 0 + 0i, 4.29 + 0i];
itype = int64(1);
jobz = 'Vectors';
range = 'Values in range';
uplo = 'Upper';
vl = -3; vu = 3;
il = int64(0); iu = int64(0);
abstol = 0;
[~, ~, m, w, Z, jfail, info] = ...
f08sp( ...
itype, jobz, range, uplo, a, b, vl, vu, il, iu, abstol);
for i = 1:m
[~,k] = max(abs(real(Z(:,i)))+abs(imag(Z(:,i))));
Z(:,i) = Z(:,i)*conj(Z(k,i))/abs(Z(k,i));
end
disp('Eigenvalues');
disp(w(1:m)');
disp('Eigenvectors');
disp(Z);
f08sp example results
Eigenvalues
-2.9936 0.5047
Eigenvectors
-0.6626 + 0.2258i 0.6462 + 0.0000i
-0.1164 - 0.0178i 0.1216 - 0.4788i
0.9098 + 0.0000i -0.1344 - 0.3059i
-0.6120 - 0.5348i 0.2924 + 0.5987i
PDF version (NAG web site
, 64-bit version, 64-bit version)
© The Numerical Algorithms Group Ltd, Oxford, UK. 2009–2015