NAG Library Routine Document
F12FEF
Note: this routine uses optional parameters to define choices in the problem specification. If you wish to use default
settings for all of the optional parameters, then the option setting routine F12FDF need not be called.
If, however, you wish to reset some or all of the settings please refer to Section 11 in F12FDF for a detailed description of the specification of the optional parameters.
1 Purpose
F12FEF can be used to return additional monitoring information during computation. It is in a suite of routines which includes
F12FAF,
F12FBF,
F12FCF and
F12FDF.
2 Specification
INTEGER |
NITER, NCONV, ICOMM(*) |
REAL (KIND=nag_wp) |
RITZ(*), RZEST(*), COMM(*) |
|
3 Description
The suite of routines is designed to calculate some of the eigenvalues, , (and optionally the corresponding eigenvectors, ) of a standard eigenvalue problem , or of a generalized eigenvalue problem of order , where is large and the coefficient matrices and are sparse, real and symmetric. The suite can also be used to find selected eigenvalues/eigenvectors of smaller scale dense, real and symmetric problems.
On an intermediate exit from
F12FBF with
, F12FEF may be called to return monitoring information on the progress of the Arnoldi iterative process. The information returned by F12FEF is:
– |
the number of the current Arnoldi iteration; |
– |
the number of converged eigenvalues at this point; |
– |
the real and imaginary parts of the converged eigenvalues; |
– |
the error bounds on the converged eigenvalues. |
F12FEF does not have an equivalent routine from the ARPACK package which prints various levels of detail of monitoring information through an output channel controlled via a parameter value (see
Lehoucq et al. (1998) for details of ARPACK routines). F12FEF should not be called at any time other than immediately following an
return from
F12FBF.
4 References
Lehoucq R B (2001) Implicitly restarted Arnoldi methods and subspace iteration SIAM Journal on Matrix Analysis and Applications 23 551–562
Lehoucq R B and Scott J A (1996) An evaluation of software for computing eigenvalues of sparse nonsymmetric matrices Preprint MCS-P547-1195 Argonne National Laboratory
Lehoucq R B and Sorensen D C (1996) Deflation techniques for an implicitly restarted Arnoldi iteration SIAM Journal on Matrix Analysis and Applications 17 789–821
Lehoucq R B, Sorensen D C and Yang C (1998) ARPACK Users' Guide: Solution of Large-scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods SIAM, Philidelphia
5 Parameters
- 1: – INTEGEROutput
-
On exit: the number of the current Arnoldi iteration.
- 2: – INTEGEROutput
-
On exit: the number of converged eigenvalues so far.
- 3: – REAL (KIND=nag_wp) arrayOutput
-
Note: the dimension of the array
RITZ
must be at least
(see
F12FAF).
On exit: the first
NCONV locations of the array
RITZ contain the real converged approximate eigenvalues.
- 4: – REAL (KIND=nag_wp) arrayOutput
-
Note: the dimension of the array
RZEST
must be at least
(see
F12FAF).
On exit: the first
NCONV locations of the array
RZEST contain the Ritz estimates (error bounds) on the real
NCONV converged approximate eigenvalues.
- 5: – INTEGER arrayCommunication Array
-
Note: the dimension of the array
ICOMM
must be at least
, where
LICOMM
is passed to the setup routine
(see
F12FAF).
On entry: the array
ICOMM output by the preceding call to
F12FBF.
- 6: – REAL (KIND=nag_wp) arrayCommunication Array
-
Note: the dimension of the array
COMM
must be at least
, where
LCOMM
is passed to the setup routine
(see
F12FAF).
On entry: the array
COMM output by the preceding call to
F12FBF.
6 Error Indicators and Warnings
None.
7 Accuracy
A Ritz value,
, is deemed to have converged if its Ritz estimate
. The default
Tolerance used is the
machine precision given by
X02AJF.
8 Parallelism and Performance
Not applicable.
None.
10 Example
This example solves
using the
Buckling option (see
F12FDF, where
and
are obtained by the finite element method applied to the one-dimensional discrete Laplacian operator
on
, with zero Dirichlet boundary conditions using piecewise linear elements. The shift,
, is a real number, and the operator used in the Buckling iterative process is
and
.
10.1 Program Text
Program Text (f12fefe.f90)
10.2 Program Data
Program Data (f12fefe.d)
10.3 Program Results
Program Results (f12fefe.r)