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📄 lnsymreg.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 LNSymReg.cc.   Example program that illustrates how to solve a real   nonsymmetric standard eigenvalue problem in regular mode   using the ARluNonSymStdEig 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 convection-diffusion operator                       (Laplacian u) + rho*(du/dx)      on a unit square with zero Dirichlet boundary conditions.   2) Data structure used to represent matrix A:      {nnz, irow, pcol, A}: matrix A data in CSC format.   3) Included header files:      File             Contents      -----------      -------------------------------------------      lnmatrxb.h       BlockTridMatrix, a function that generates                       matrix A in CSC format.      arlnsmat.h       The ARluNonSymMatrix class definition.      arlsnsym.h       The ARluNonSymStdEig class definition.      lnsymsol.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 "lnmatrxb.h"#include "arlnsmat.h"#include "arlsnsym.h"#include "lnsymsol.h"main(){  // Defining variables;  int     nx;  int     n;          // Dimension of the problem.  int     nnz;        // Number of nonzero elements in A.  int*    irow;       // pointer to an array that stores the row                      // indices of the nonzeros in A.  int*    pcol;       // pointer to an array of pointers to the                      // beginning of each column of A in vector A.  double* A;          // pointer to an array that stores the                      // nonzero elements of A.  // Creating a 100x100 matrix.  nx = 10;  BlockTridMatrix(nx, n, nnz, A, irow, pcol);  ARluNonSymMatrix<double> matrix(n, nnz, A, irow, pcol);  // Defining what we need: the four eigenvectors of A with largest magnitude.  ARluNonSymStdEig<double> dprob(4, matrix);  // Finding eigenvalues and eigenvectors.  dprob.FindEigenvectors();  // Printing solution.  Solution(matrix, dprob);} // main.

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