NAG Library Routine Document
F12AEF
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 F12ADF need not be called.
If, however, you wish to reset some or all of the settings please refer to Section 11 in F12ADF for a detailed description of the specification of the optional parameters.
1 Purpose
F12AEF can be used to return additional monitoring information during computation. It is in a suite of routines consisting of
F12AAF,
F12ABF,
F12ACF,
F12ADF and F12AEF.
2 Specification
INTEGER |
NITER, NCONV, ICOMM(*) |
REAL (KIND=nag_wp) |
RITZR(*), RITZI(*), 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 nonsymmetric. The suite can also be used to find selected eigenvalues/eigenvectors of smaller scale dense, real and nonsymmetric problems.
On an intermediate exit from
F12ABF with
, F12AEF may be called to return monitoring information on the progress of the Arnoldi iterative process. The information returned by F12AEF 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. |
F12AEF 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). F12AEF should not be called at any time other than immediately following an
return from
F12ABF.
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
RITZR
must be at least
(see
F12AAF).
On exit: the first
NCONV locations of the array
RITZR contain the real parts of the converged approximate eigenvalues.
- 4: – REAL (KIND=nag_wp) arrayOutput
-
Note: the dimension of the array
RITZI
must be at least
(see
F12AAF).
On exit: the first
NCONV locations of the array
RITZI contain the imaginary parts of the converged approximate eigenvalues.
- 5: – REAL (KIND=nag_wp) arrayOutput
-
Note: the dimension of the array
RZEST
must be at least
(see
F12AAF).
On exit: the first
NCONV locations of the array
RZEST contain the Ritz estimates (error bounds) on the converged approximate eigenvalues.
- 6: – INTEGER arrayCommunication Array
-
Note: the dimension of the array
ICOMM
must be at least
, where
LICOMM
is passed to the setup routine
(see
F12AAF).
On entry: the array
ICOMM output by the preceding call to
F12ABF.
- 7: – 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
F12AAF).
On entry: the array
COMM output by the preceding call to
F12ABF.
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 in shifted-real mode, where is the tridiagonal matrix with on the diagonal, on the subdiagonal and on the superdiagonal. The matrix is the tridiagonal matrix with on the diagonal and on the off-diagonals. The shift sigma, , is a complex number, and the operator used in the shifted-real iterative process is .
10.1 Program Text
Program Text (f12aefe.f90)
10.2 Program Data
Program Data (f12aefe.d)
10.3 Program Results
Program Results (f12aefe.r)