📄 bnsymshf.cc
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/* ARPACK++ v1.0 8/1/1997 c++ interface to ARPACK code. MODULE BNSymShf.cc. Example program that illustrates how to solve a real nonsymmetric standard eigenvalue problem in shift and invert mode using the ARluNonSymStdEig class. 1) Problem description: In this example we try to solve A*x = x*lambda in shift and invert mode, where A is derived from the standard central difference discretization of the 2-dimensional convection-diffusion operator (Laplacian u) + rho*(du/dx) on a unit square with zero Dirichlet boundary conditions. The shift is a real number. 2) Data structure used to represent matrix A: {ndiagL, ndiagU, A}: matrix A data in band format. The columns of A are stored sequentially in vector A. ndiagL and ndiagU supply the lower and upper bandwidth of A, respectively. 3) Library called by this example: The LAPACK package is called by ARluNonSymStdEig to solve some linear systems involving (A-sigma*I). This is needed to implement the shift and invert strategy. 4) Included header files: File Contents ----------- -------------------------------------------- bnmatrxa.h BandMatrixA, a function that generates matrix A in band format. arbnsmat.h The ARbdNonSymMatrix class definition. arbsnsym.h The ARluNonSymStdEig class definition. lnsymsol.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 "bnmatrxa.h"#include "arbnsmat.h"#include "arbsnsym.h"#include "lnsymsol.h"main(){ // Defining variables; int nx; int n; // Dimension of the problem. int ndiagL; // Lower bandwidth of A. int ndiagU; // Upper bandwidth of A. double rho; // Parameter used to define A. double* A; // pointer to an array that stores the elements of A. // Creating a 100x100 matrix. nx = 10; rho = 10.0; BandMatrixA(nx, rho, n, ndiagL, ndiagU, A); ARbdNonSymMatrix<double> matrix(n, ndiagL, ndiagU, A); // Defining what we need: the four eigenvectors of A nearest to 1000.0. ARluNonSymStdEig<double> dprob(4L, matrix, 1000.0, "LM", 20); // Finding eigenvalues and eigenvectors. dprob.FindEigenvectors(); // Printing solution. Solution(matrix, dprob);} // main
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