94 lines
2.8 KiB
C++
94 lines
2.8 KiB
C++
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// Small bench routine for Eigen available in Eigen
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// (C) Desire NUENTSA WAKAM, INRIA
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#include <iostream>
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#include <fstream>
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#include <iomanip>
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#include <unsupported/Eigen/SparseExtra>
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#include <Eigen/SparseLU>
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#include <bench/BenchTimer.h>
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#ifdef EIGEN_METIS_SUPPORT
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#include <Eigen/MetisSupport>
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#endif
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using namespace std;
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using namespace Eigen;
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int main(int argc, char **args)
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{
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// typedef complex<double> scalar;
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typedef double scalar;
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SparseMatrix<scalar, ColMajor> A;
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typedef SparseMatrix<scalar, ColMajor>::Index Index;
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typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;
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typedef Matrix<scalar, Dynamic, 1> DenseRhs;
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Matrix<scalar, Dynamic, 1> b, x, tmp;
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// SparseLU<SparseMatrix<scalar, ColMajor>, AMDOrdering<int> > solver;
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// #ifdef EIGEN_METIS_SUPPORT
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// SparseLU<SparseMatrix<scalar, ColMajor>, MetisOrdering<int> > solver;
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// std::cout<< "ORDERING : METIS\n";
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// #else
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SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> > solver;
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std::cout<< "ORDERING : COLAMD\n";
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// #endif
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ifstream matrix_file;
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string line;
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int n;
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BenchTimer timer;
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// Set parameters
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/* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
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if (argc < 2) assert(false && "please, give the matrix market file ");
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loadMarket(A, args[1]);
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cout << "End charging matrix " << endl;
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bool iscomplex=false, isvector=false;
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int sym;
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getMarketHeader(args[1], sym, iscomplex, isvector);
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// if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
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if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
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if (sym != 0) { // symmetric matrices, only the lower part is stored
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SparseMatrix<scalar, ColMajor> temp;
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temp = A;
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A = temp.selfadjointView<Lower>();
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}
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n = A.cols();
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/* Fill the right hand side */
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if (argc > 2)
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loadMarketVector(b, args[2]);
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else
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{
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b.resize(n);
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tmp.resize(n);
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// tmp.setRandom();
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for (int i = 0; i < n; i++) tmp(i) = i;
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b = A * tmp ;
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}
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/* Compute the factorization */
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// solver.isSymmetric(true);
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timer.start();
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// solver.compute(A);
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solver.analyzePattern(A);
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timer.stop();
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cout << "Time to analyze " << timer.value() << std::endl;
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timer.reset();
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timer.start();
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solver.factorize(A);
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timer.stop();
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cout << "Factorize Time " << timer.value() << std::endl;
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timer.reset();
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timer.start();
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x = solver.solve(b);
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timer.stop();
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cout << "solve time " << timer.value() << std::endl;
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/* Check the accuracy */
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Matrix<scalar, Dynamic, 1> tmp2 = b - A*x;
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scalar tempNorm = tmp2.norm()/b.norm();
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cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
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cout << "Number of nonzeros in the factor : " << solver.nnzL() + solver.nnzU() << std::endl;
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return 0;
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}
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