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📄 lnsymgsh.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 LNSymGSh.cc.   Example program that illustrates how to solve a real nonsymmetric   generalized eigenvalue problem in real shift and invert mode using   the ARluNonSymGenEig class.   1) Problem description:      In this example we try to solve A*x = B*x*lambda in shift and      inverse mode, where A and B are derived from the finite element      discretization of the 1-dimensional convection-diffusion operator                        (d^2u / dx^2) + rho*(du/dx)      on the interval [0,1] with zero Dirichlet boundary conditions      using linear elements.      The shift sigma is a real number.   2) Data structure used to represent matrices A and B:      {nnzA, irowA, pcolA, valA}: matrix A data in CSC format.      {nnzA, irowA, pcolA, valA}: matrix B data in CSC format.   3) Library called by this example:      The SuperLU package is called by ARluNonSymGenEig to solve      some linear systems involving (A-sigma*B). This is needed to      implement the shift and invert strategy.   4) Included header files:      File             Contents      -----------      -------------------------------------------      lnmatrxc.h       StiffnessMatrix, a function that generates                       matrix A in CSC format.      lnmatrxd.h       MassMatrix, a function tha generates matrix                       B in CSC format.      arlnsmat.h       The ARluNonSymMatrix class definition.      arlgnsym.h       The ARluNonSymGenEig 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 "lnmatrxc.h"#include "lnmatrxd.h"#include "arlnsmat.h"#include "arlgnsym.h"#include "lnsymsol.h"main(){  // Defining variables.  int     n;               // Dimension of the problem.  int     nnza,   nnzb;    // Number of nonzero elements in A and B.  int     *irowa, *irowb;  // pointers to arrays that store the row                           // indices of the nonzeros in A and B.  int     *pcola, *pcolb;  // pointers to arrays of pointers to the                           // beginning of each column of A and B in                           // valA and ValB.  double  rho;             // A parameter used in StiffnessMatrix.  double  *valA,  *valB;   // pointers to arrays that store the                           // nonzero elements of A and B.  // Creating matrices A and B.  n   = 100;  rho = 10.0;  StiffnessMatrix(n, rho, nnza, valA, irowa, pcola);  ARluNonSymMatrix<double> A(n, nnza, valA, irowa, pcola);  MassMatrix(n, nnzb, valB, irowb, pcolb);  ARluNonSymMatrix<double> B(n, nnzb, valB, irowb, pcolb);  // Defining what we need: the four eigenvectors nearest to 1.0.  ARluNonSymGenEig<double> dprob(4L, A, B, 1.0);  // Finding eigenvalues and eigenvectors.  dprob.FindEigenvectors();  // Printing solution.  Solution(A, B, dprob);} // main.

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