📄 symgshft.cc
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/* ARPACK++ v1.0 8/1/1997 c++ interface to ARPACK code. MODULE SymGShft.cc. Example program that illustrates how to solve a real symmetric generalized eigenvalue problem in shift and invert mode using the ARSymGenEig class. 1) Problem description: In this example we try to solve A*x = B*x*lambda in shift and invert 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: When using ARSymGenEig, the user is required to provide some classes that contain as member functions the matrix-vector products w = OP*Bv = inv(A-sigma*B)*B*v and w = B*v. In this example, SymGenProblemB is a class that contains two member functions, MultOPv and MultBv. The first takes a vector v and returns the product OPv. The second performs the product Bv. 3) Included header files: File Contents ----------- ------------------------------------------- sgenprbb.h The SymGenProblemB class definition. argsym.h The ARSymGenEig class definition. symgsol.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 "sgenprbb.h"#include "symgsol.h"#include "argsym.h"template<class T>void Test(T type){ // Creating a symmetric generalized problem with n = 100. SymGenProblemB<T> P(100, 0.0); // Defining what we need: the four eigenvectors nearest to 0.0. // P.MultOPv is the function that performs the product w <- OPv. // P.MultBv is the function that performs the product w <- Bv. // 'S' is passed as a parameter to indicate that we will use the // shift and invert mode. ARSymGenEig<T, SymGenProblemB<T>, SymGenProblemB<T> > dprob('S', P.A.ncols(), 4L, &P, &SymGenProblemB<T>::MultOPv, &P, &SymGenProblemB<T>::MultBv, 0.0); // Finding eigenvalues and eigenvectors. dprob.FindEigenvectors(); // Printing solution. Solution(P.A, P.B, 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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