ifstream matrix_file;
string line; int n;
BenchTimer timer;
// Set parameters /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */ if (argc < 2) assert(false && "please, give the matrix market file ");
loadMarket(A, args[1]);
cout << "End charging matrix " << endl; bool iscomplex=false, isvector=false; int sym;
getMarketHeader(args[1], sym, iscomplex, isvector); // if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; } if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;} if (sym != 0) { // symmetric matrices, only the lower part is stored
SparseMatrix<scalar, ColMajor> temp;
temp = A;
A = temp.selfadjointView<Lower>();
}
n = A.cols(); /* Fill the right hand side */
if (argc > 2)
loadMarketVector(b, args[2]); else
{
b.resize(n);
tmp.resize(n); // tmp.setRandom(); for (int i = 0; i < n; i++) tmp(i) = i;
b = A * tmp ;
}
/* Compute the factorization */ // solver.isSymmetric(true);
timer.start(); // solver.compute(A);
solver.analyzePattern(A);
timer.stop();
cout << "Time to analyze " << timer.value() << std::endl;
timer.reset();
timer.start();
solver.factorize(A);
timer.stop();
cout << "Factorize Time " << timer.value() << std::endl;
timer.reset();
timer.start();
x = solver.solve(b);
timer.stop();
cout << "solve time " << timer.value() << std::endl; /* Check the accuracy */
Matrix<scalar, Dynamic, 1> tmp2 = b - A*x;
scalar tempNorm = tmp2.norm()/b.norm();
cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
cout << "Number of nonzeros in the factor : " << solver.nnzL() + solver.nnzU() << std::endl;
return 0;
}
¤ Dauer der Verarbeitung: 0.19 Sekunden
(vorverarbeitet)
¤
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