📄 rcompreg.cc
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/* ARPACK++ v1.0 8/1/1997 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.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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