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/*
ARPACK++ v1.2 2/18/2000
c++ interface to ARPACK code.
MODULE RCompReg.cc.
Example program that illustrates how to solve a complex
standard eigenvalue problem in regular mode using the
ARrcCompStdEig class.
1) Problem description:
In this example we try to solve A*x = x*lambda in regular mode,
where A is obtained from the standard central difference
discretization of the convection-diffusion operator
(Laplacian u) + rho*(du / dx)
on the unit squre [0,1]x[0,1] with zero Dirichlet boundary
conditions.
2) Data structure used to represent matrix A:
ARrcCompStdEig is a class thar requires the user to provide
a way to perform the matrix-vector product w = Av. In this
example a class called CompMatrixA was created with this
purpose. CompMatrixA contains a member function, MultMv(v,w),
that takes a vector v and returns the product Av in w.
3) The reverse communication interface:
This example uses the reverse communication interface, which
means that the desired eigenvalues cannot be obtained directly
from an ARPACK++ class.
Here, the overall process of finding eigenvalues by using the
Arnoldi method is splitted into two parts. In the first, a
sequence of calls to a function called TakeStep is combined
with matrix-vector products in order to find an Arnoldi basis.
In the second part, an ARPACK++ function like FindEigenvectors
(or EigenValVectors) is used to extract eigenvalues and
eigenvectors.
4) Included header files:
File Contents
----------- -------------------------------------------
cmatrixa.h The CompMatrixA class definition.
arrscomp.h The ARrcCompStdEig class definition.
rcompsol.h The Solution function.
arcomp.h The "arcomplex" (complex) type definition.
5) ARPACK Authors:
Richard Lehoucq
Kristyn Maschhoff
Danny Sorensen
Chao Yang
Dept. of Computational & Applied Mathematics
Rice University
Houston, Texas
*/
#include "arcomp.h"
#include "arrscomp.h"
#include "cmatrixa.h"
#include "rcompsol.h"
template<class T>
void Test(T type)
{
// Defining a complex matrix.
CompMatrixA<T> A(10); // n = 10*10.
// Creating a complex eigenvalue problem and defining what we need:
// the four eigenvectors of A with largest magnitude.
ARrcCompStdEig<T> prob(A.ncols(), 4L);
// Finding an Arnoldi basis.
while (!prob.ArnoldiBasisFound()) {
// Calling ARPACK FORTRAN code. Almost all work needed to
// find an Arnoldi basis is performed by TakeStep.
prob.TakeStep();
if ((prob.GetIdo() == 1)||(prob.GetIdo() == -1)) {
// Performing matrix-vector multiplication.
// In regular mode, w = Av must be performed whenever
// GetIdo is equal to 1 or -1. GetVector supplies a pointer
// to the input vector, v, and PutVector a pointer to the
// output vector, w.
A.MultMv(prob.GetVector(), prob.PutVector());
}
}
// Finding eigenvalues and eigenvectors.
prob.FindEigenvectors();
// Printing solution.
Solution(prob);
} // Test.
int main()
{
// Solving a single precision problem with n = 100.
#ifndef __SUNPRO_CC
Test((float)0.0);
#endif
// Solving a double precision problem with n = 100.
Test((double)0.0);
} // main
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