📄 symreg.cc
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/* ARPACK++ v1.0 8/1/1997 c++ interface to ARPACK code. MODULE SymReg.cc. Example program that illustrates how to solve a real symmetric standard eigenvalue problem in regular mode using the ARSymStdEig class. 1) Problem description: In this example we try to solve A*x = x*lambda in regular mode, where A is derived from the central difference discretization of the 2-dimensional Laplacian on the unit square [0,1]x[0,1] with zero Dirichlet boundary conditions. 2) Data structure used to represent matrix A: When using ARSymStdEig, the user is required to provide a class that contains a member function which computes the the matrix-vector product w = Av. In this example, this class is called SymMatrixA, and MultMv is the function. 3) Included header files: File Contents ----------- ------------------------------------------- smatrixa.h The SymMatrixA class definition. arssym.h The ARSymStdEig class definition. symsol.h The Solution function. 4) ARPACK Authors: Richard Lehoucq Kristyn Maschhoff Danny Sorensen Chao Yang Dept. of Computational & Applied Mathematics Rice University Houston, Texas*/#include "arssym.h"#include "smatrixa.h"#include "symsol.h"template<class T>void Test(T type){ // Creating a symmetric matrix. SymMatrixA<T> A(10L); // n = 10*10. // Defining what we need: the four eigenvectors of A with smallest magnitude. // A.MultMv is the function that performs the product w <- A.v. ARSymStdEig<T, SymMatrixA<T> > dprob(A.ncols(), 4L, &A, &SymMatrixA<T>::MultMv, "SM"); // Finding eigenvalues and eigenvectors. dprob.FindEigenvectors(); // Printing solution. Solution(A, dprob);} // Test.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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