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/*
ARPACK++ v1.2 2/18/2000
c++ interface to ARPACK code.
MODULE RSymGBkl.cc.
Example program that illustrates how to solve a real symmetric
generalized eigenvalue problem in buckling mode using the
ARrcSymGenEig class.
1) Problem description:
In this example we try to solve A*x = B*x*lambda in buckling
mode, where A and B are obtained from the finite element
discretrization of the 1-dimensional discrete Laplacian
d^2u / dx^2
on the interval [0,1] with zero Dirichlet boundary conditions
using piecewise linear elements.
2) Data structure used to represent matrices A and B:
ARrcSymGenEig is a class that requires the user to provide a
way to perform the matrix-vector products w = OP*Av =
inv(A-sigma*B)*A*v and w = A*v, where sigma is the adopted shift.
In this example a class called SymGenProblemB was created with
this purpose. SymGenProblemB contains a member function,
MultOPv(v,w), that takes a vector v and returns the product OPv
in w. It also contains an object, A, that stores matrix A data.
The product Av is performed by MultMv, a member function of A.
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
----------- -------------------------------------------
sgenprbb.h The SymGenProblemB class definition.
arrgsym.h The ARrcSymGenEig class definition.
rsymgsol.h The Solution function.
5) ARPACK Authors:
Richard Lehoucq
Kristyn Maschhoff
Danny Sorensen
Chao Yang
Dept. of Computational & Applied Mathematics
Rice University
Houston, Texas
*/
#include "sgenprbb.h"
#include "rsymgsol.h"
#include "arrgsym.h"
template<class T>
void Test(T type)
{
// Defining a temporary vector.
T temp[101];
// Creating a pencil.
SymGenProblemB<T> P(100, 1.0);
// Creating a symmetric eigenvalue problem. 'B' indicates that
// we will use the buckling mode. P.A.ncols() furnishes the
// dimension of the problem. 4 is the number of eigenvalues
// sought and 1.0 is the shift.
ARrcSymGenEig<T> prob('B', P.A.ncols(), 4L, 1.0);
// 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();
switch (prob.GetIdo()) {
case -1:
// Performing w <- OP*A*v for the first time.
// This product must be performed only if GetIdo is equal to
// -1. GetVector supplies a pointer to the input vector, v,
// and PutVector a pointer to the output vector, w.
P.A.MultMv(prob.GetVector(), temp);
P.MultOPv(temp, prob.PutVector());
break;
case 1:
// Performing w <- OP*A*v.
// This product must be performed whenever GetIdo is equal to
// 1. GetProd supplies a pointer to the previously calculated
// product Av and PutVector a pointer to the output vector w.
P.MultOPv(prob.GetProd(), prob.PutVector());
break;
case 2:
// Performing w <- A*v.
P.A.MultMv(prob.GetVector(), prob.PutVector());
}
}
// Finding eigenvalues and eigenvectors.
prob.FindEigenvectors();
// Printing solution.
Solution(prob);
} // Test.
int main()
{
// Solving a double precision problem with n = 100.
Test((double)0.0);
// Solving a single precision problem with n = 100.
Test((float)0.0);
} // main
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