NAG CL Interface
f12asc (complex_​monit)

Note: this function 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 function f12arc need not be called. If, however, you wish to reset some or all of the settings please refer to Section 11 in f12arc for a detailed description of the specification of the optional parameters.
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1 Purpose

f12asc can be used to return additional monitoring information during computation. It is in a suite of functions consisting of f12anc, f12apc, f12aqc, f12arc and f12asc.

2 Specification

#include <nag.h>
void  f12asc (Integer *niter, Integer *nconv, Complex ritz[], Complex rzest[], const Integer icomm[], const Complex comm[])
The function may be called by the names: f12asc, nag_sparseig_complex_monit or nag_complex_sparse_eigensystem_monit.

3 Description

The suite of functions is designed to calculate some of the eigenvalues, λ , (and optionally the corresponding eigenvectors, x ) of a standard complex eigenvalue problem Ax = λx , or of a generalized complex eigenvalue problem Ax = λBx of order n , where n is large and the coefficient matrices A and B are sparse and complex. The suite can also be used to find selected eigenvalues/eigenvectors of smaller scale dense complex problems.
On an intermediate exit from f12apc with irevcm = 4 , f12asc may be called to return monitoring information on the progress of the Arnoldi iterative process. The information returned by f12asc is:
f12asc does not have an equivalent function from the ARPACK package which prints various levels of detail of monitoring information through an output channel controlled via an argument value (see Lehoucq et al. (1998) for details of ARPACK routines). f12asc should not be called at any time other than immediately following an irevcm = 4 return from f12apc.

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, Philadelphia

5 Arguments

1: niter Integer * Output
On exit: the number of the current Arnoldi iteration.
2: nconv Integer * Output
On exit: the number of converged eigenvalues so far.
3: ritz[dim] Complex Output
Note: the dimension, dim, of the array ritz must be at least ncv (see f12anc).
On exit: the first nconv locations of the array ritz contain the converged approximate eigenvalues.
4: rzest[dim] Complex Output
Note: the dimension, dim, of the array rzest must be at least ncv (see f12anc).
On exit: the first nconv locations of the array rzest contain the complex Ritz estimates on the converged approximate eigenvalues.
5: icomm[dim] const Integer Communication Array
Note: the dimension, dim, of the array icomm must be at least max(1,licomm), where licomm is passed to the setup function  (see f12anc).
On entry: the array icomm output by the preceding call to f12apc.
6: comm[dim] const Complex Communication Array
Note: the dimension, dim, of the array comm must be at least max(1,lcomm), where lcomm is passed to the setup function  (see f12anc).
On entry: the array comm output by the preceding call to f12apc.

6 Error Indicators and Warnings

None.

7 Accuracy

A Ritz value, λ , is deemed to have converged if the magnitude of its Ritz estimate Tolerance × |λ| . The default Tolerance used is the machine precision given by X02AJC.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f12asc is not threaded in any implementation.

9 Further Comments

None.

10 Example

This example solves Ax = λBx in shifted-inverse mode, where A and B are obtained from the standard central difference discretization of the one-dimensional convection-diffusion operator d2u dx2 + ρ du dx on [0,1] , with zero Dirichlet boundary conditions. The shift, σ , is a complex number, and the operator used in the shifted-inverse iterative process is op = inv(A-σB) × B .

10.1 Program Text

Program Text (f12asce.c)

10.2 Program Data

Program Data (f12asce.d)

10.3 Program Results

Program Results (f12asce.r)