📄 lcompshf.cc
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/* ARPACK++ v1.0 8/1/1997 c++ interface to ARPACK code. MODULE LCompShf.cc. Example program that illustrates how to solve a complex standard eigenvalue problem in shift and invert mode using the ARluCompStdEig 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 central difference 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. 2) Data structure used to represent matrix A: {nnz, irow, pcol, A}: matrix A data in CSC format. 3) Library called by this example: The SuperLU package is called by ARluCompStdEig 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 ----------- --------------------------------------------- lcmatrxb.h CompMatrixB, a function that generates matrix A in CSC format. arlnsmat.h The ARluNonSymMatrix class definition. arlscomp.h The ARluCompStdEig class definition. lcompsol.h The Solution function. arcomp.h The "arcomplex" (complex) type definition. 5) ARPACK Authors: Richard Lehoucq Kristyn Maschhoff Danny Sorensen Chao Yang Dept. of Computational & Applied Mathematics Rice University Houston, Texas*/#include "arcomp.h"#include "arlnsmat.h"#include "arlscomp.h"#include "lcmatrxb.h"#include "lcompsol.h"main(){ // Defining variables; 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 valA. arcomplex<double> rho; // parameter used to define A. arcomplex<double>* valA; // pointer to an array that stores the // nonzero elements of A. // Creating a complex matrix. n = 100; rho = 10.0; CompMatrixB(n, rho, nnz, valA, irow, pcol); ARluNonSymMatrix<arcomplex<double> > A(n, nnz, valA, irow, pcol); // Defining what we need: the four eigenvectors of F nearest to 0.0. ARluCompStdEig<double> dprob(4L, A, arcomplex<double>(0.0, 0.0)); // Finding eigenvalues and eigenvectors. dprob.FindEigenvectors(); // Printing solution. Solution(A, dprob);} // main.
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