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📄 dsymreg.cc

📁 ARPACK is a collection of Fortran77 subroutines designed to solve large scale eigenvalue problems.
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/*   ARPACK++ v1.0 8/1/1997   c++ interface to ARPACK code.   MODULE DSymReg.cc.   Example program that illustrates how to solve a real   symmetric dense standard eigenvalue problem in regular    mode using the ARluSymStdEig class.   1) Problem description:      In this example we try to solve A*x = x*lambda in regular       mode, where A is derived from the standard central difference      discretization of the 2-dimensional Laplacian on the unit       square with zero Dirichlet boundary conditions.   2) Data structure used to represent matrix A:      Although A is very sparse in this example, it is stored      here as a dense symmetric matrix. The lower triangular part      of A is stored, by columns, in the vector A.   3) Included header files:      File             Contents      -----------      -------------------------------------------      dsmatrxa.h       DenseMatrixA, a function that generates                       matrix A.      ardsmat.h        The ARdsSymMatrix class definition.      ardssym.h        The ARluSymStdEig class definition.      lsymsol.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 "dsmatrxa.h"#include "ardsmat.h"#include "ardssym.h"#include "lsymsol.h"main(){  // Defining variables;  int     nx;  int     n;   // Dimension of the problem.  double* A;   // Pointer to an array that stores the lower triangular               // elements of A.  // Creating a 100x100 matrix.  nx  = 10;  DenseMatrixA(nx, n, A);  ARdsSymMatrix<double> matrix(n, A);  // Defining what we need: the four eigenvectors of A with largest magnitude.  ARluSymStdEig<double> dprob(4, matrix);  // Finding eigenvalues and eigenvectors.  dprob.FindEigenvectors();  // Printing solution.  Solution(matrix, dprob);} // main.

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