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📄 lcompsol.h

📁 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 LCompSol.h   Template functions that exemplify how to print information   about complex standard and generalized eigenvalue problems.   ARPACK Authors      Richard Lehoucq      Danny Sorensen      Chao Yang      Dept. of Computational & Applied Mathematics      Rice University      Houston, Texas*/#ifndef LCOMPSOL_H#define LCOMPSOL_H#include <math.h>#include "arcomp.h"#include "blas1c.h"#include "lapackc.h"#ifdef ARLNSMAT_H#include "arlscomp.h"#include "arlgcomp.h"#elif defined ARUNSMAT_H#include "aruscomp.h"#include "arugcomp.h"#elif defined ARDNSMAT_H#include "ardscomp.h"#include "ardgcomp.h"#else#include "arbscomp.h"#include "arbgcomp.h"#endiftemplate<class MATRIX, class FLOAT>void Solution(MATRIX &A, ARluCompStdEig<FLOAT> &Prob)/*  Prints eigenvalues and eigenvectors of complex eigen-problems  on standard "cout" stream.*/{  int              i, n, nconv, mode;  arcomplex<FLOAT> *Ax;  FLOAT            *ResNorm;  n     = Prob.GetN();  nconv = Prob.ConvergedEigenvalues();  mode  = Prob.GetMode();  cout << endl << endl << "Testing ARPACK++ class ARluCompStdEig \n";  cout << "Complex eigenvalue problem: A*x - lambda*x" << endl;  switch (mode) {  case 1:    cout << "Regular mode" << endl << endl;    break;  case 3:    cout << "Shift and invert mode" << endl << endl;  }  cout << "Dimension of the system            : " << n              << endl;  cout << "Number of 'requested' eigenvalues  : " << Prob.GetNev()  << endl;  cout << "Number of 'converged' eigenvalues  : " << nconv          << endl;  cout << "Number of Arnoldi vectors generated: " << Prob.GetNcv()  << endl;  cout << "Number of iterations taken         : " << Prob.GetIter() << endl;  cout << endl;  if (Prob.EigenvaluesFound()) {    // Printing eigenvalues.    cout << "Eigenvalues:" << endl;    for (i=0; i<nconv; i++) {      cout << "  lambda[" << (i+1) << "]: " << Prob.Eigenvalue(i) << endl;    }    cout << endl;  }  if (Prob.EigenvectorsFound()) {    // Printing the residual norm || A*x - lambda*x ||    // for the nconv accurately computed eigenvectors.    Ax      = new arcomplex<FLOAT>[n];    ResNorm = new FLOAT[nconv+1];    for (i=0; i<nconv; i++) {      A.MultMv(Prob.RawEigenvector(i),Ax);      axpy(n, -Prob.Eigenvalue(i), Prob.RawEigenvector(i), 1, Ax, 1);      ResNorm[i] = nrm2(n, Ax, 1)/                   lapy2(real(Prob.Eigenvalue(i)),imag(Prob.Eigenvalue(i)));    }    for (i=0; i<nconv; i++) {      cout << "||A*x(" << (i+1) << ") - lambda(" << (i+1);      cout << ")*x(" << (i+1) << ")||: " << ResNorm[i] << endl;    }    cout << "\n";    delete[] Ax;    delete[] ResNorm;  }} // Solutiontemplate<class MATRA, class MATRB, class FLOAT>void Solution(MATRA &A, MATRB &B, ARluCompGenEig<FLOAT> &Prob)/*  Prints eigenvalues and eigenvectors of complex generalized  eigen-problems on standard "cout" stream.*/{  int              i, n, nconv, mode;  FLOAT            *ResNorm;  arcomplex<FLOAT> *Ax, *Bx;  n     = Prob.GetN();  nconv = Prob.ConvergedEigenvalues();  mode  = Prob.GetMode();  cout << endl << endl;   cout << "Testing ARPACK++ class ARluCompGenEig \n" << endl;  cout << "Complex generalized eigenvalue problem: A*x - lambda*B*x" << endl;  switch (mode) {  case 2:    cout << "Regular mode" << endl << endl;    break;  case 3:    cout << "Shift and invert mode" << endl << endl;  }  cout << "Dimension of the system            : " << n              << endl;  cout << "Number of 'requested' eigenvalues  : " << Prob.GetNev()  << endl;  cout << "Number of 'converged' eigenvalues  : " << nconv          << endl;  cout << "Number of Arnoldi vectors generated: " << Prob.GetNcv()  << endl;  cout << "Number of iterations taken         : " << Prob.GetIter() << endl;  cout << endl;  if (Prob.EigenvaluesFound()) {    // Printing eigenvalues.    cout << "Eigenvalues:" << endl;    for (i=0; i<nconv; i++) {      cout << "  lambda[" << (i+1) << "]: " << Prob.Eigenvalue(i) << endl;    }    cout << endl;  }  if (Prob.EigenvectorsFound()) {    // Printing the residual norm || A*x - lambda*B*x ||    // for the nconv accurately computed eigenvectors.    Ax      = new arcomplex<FLOAT>[n];    Bx      = new arcomplex<FLOAT>[n];    ResNorm = new FLOAT[nconv+1];    for (i=0; i<nconv; i++) {      A.MultMv(Prob.RawEigenvector(i),Ax);      B.MultMv(Prob.RawEigenvector(i),Bx);      axpy(n, -Prob.Eigenvalue(i), Bx, 1, Ax, 1);      ResNorm[i] = nrm2(n, Ax, 1)/                   lapy2(real(Prob.Eigenvalue(i)),imag(Prob.Eigenvalue(i)));    }    for (i=0; i<nconv; i++) {      cout << "||A*x(" << (i+1) << ") - lambda(" << (i+1);      cout << ")*B*x(" << (i+1) << ")||: " << ResNorm[i] << "\n";    }    cout << endl;    delete[] Ax;    delete[] Bx;    delete[] ResNorm;  }} // Solution#endif // LCOMPSOL_H

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