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📄 bnsymgsc.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 BNSymGSC.cc.   Example program that illustrates how to solve a real nonsymmetric   generalized eigenvalue problem in complex 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 is a block tridiagonal matrix and B is      a tridiagonal matrix. Each diagonal block of A is a tridiagonal      matrix with 4 on the main diagonal, -1-rho*h/2 on the subdiagonal      and -1+rho*h/2 on the superdiagonal. Each subdiagonal block of A      is an identity matrix. B has 4 on the main diagonal and 1 on      the other two diagonals.      The shift sigma is a complex number.   2) Data structure used to represent matrices A and B:      {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.       {ndiagL, ndiagU, B}: matrix B in band format.   3) Library called by this example:      The LAPACK 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      -----------      -------------------------------------------      bnmatrxd.h       BandMatrixD, a function that generates                       matrix A in band format.      bnmatrxe.h       BandMatrixE, a function that generates                        matrix B in band format.      arbnsmat.h       The ARbdNonSymMatrix class definition.      arbgnsym.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 "bnmatrxd.h"#include "bnmatrxe.h"#include "arbnsmat.h"#include "arbgnsym.h"#include "lnsymsol.h"main(){  // Defining variables;  int     nx;  int     n;       // Dimension of the problem.  int     ndiagL;  // Lower bandwidth of A and B.  int     ndiagU;  // Upper bandwidth of A and B.  double  rho;     // Parameter used to define A.  double* valA;    // pointer to an array that stores the elements of A.  double* valB;    // pointer to an array that stores the elements of B.  // Creating matrices A and B.  nx  = 10;  rho = 100.0;  BandMatrixD(nx, rho, n, ndiagL, ndiagU, valA);  ARbdNonSymMatrix<double> A(n, ndiagL, ndiagU, valA);  BandMatrixE(n, ndiagL, ndiagU, valB);  ARbdNonSymMatrix<double> B(n, ndiagL, ndiagU, valB);  // Defining what we need: the four eigenvectors nearest to 0.4+0.6I.  ARluNonSymGenEig<double> dprob(4L, A, B, 'I', 0.4, 0.6);  // Finding eigenvalues and eigenvectors.  dprob.FindEigenvectors();  // Printing solution.  Solution(A, B, dprob);} // main.

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