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