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      1 // Small bench routine for Eigen available in Eigen
      2 // (C) Desire NUENTSA WAKAM, INRIA
      3 
      4 #include <iostream>
      5 #include <fstream>
      6 #include <iomanip>
      7 #include <unsupported/Eigen/SparseExtra>
      8 #include <Eigen/SparseLU>
      9 #include <bench/BenchTimer.h>
     10 #ifdef EIGEN_METIS_SUPPORT
     11 #include <Eigen/MetisSupport>
     12 #endif
     13 
     14 using namespace std;
     15 using namespace Eigen;
     16 
     17 int main(int argc, char **args)
     18 {
     19 //   typedef complex<double> scalar;
     20   typedef double scalar;
     21   SparseMatrix<scalar, ColMajor> A;
     22   typedef SparseMatrix<scalar, ColMajor>::Index Index;
     23   typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;
     24   typedef Matrix<scalar, Dynamic, 1> DenseRhs;
     25   Matrix<scalar, Dynamic, 1> b, x, tmp;
     26 //   SparseLU<SparseMatrix<scalar, ColMajor>, AMDOrdering<int> >   solver;
     27 // #ifdef EIGEN_METIS_SUPPORT
     28 //   SparseLU<SparseMatrix<scalar, ColMajor>, MetisOrdering<int> > solver;
     29 //   std::cout<< "ORDERING : METIS\n";
     30 // #else
     31   SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> >  solver;
     32   std::cout<< "ORDERING : COLAMD\n";
     33 // #endif
     34 
     35   ifstream matrix_file;
     36   string line;
     37   int  n;
     38   BenchTimer timer;
     39 
     40   // Set parameters
     41   /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
     42   if (argc < 2) assert(false && "please, give the matrix market file ");
     43   loadMarket(A, args[1]);
     44   cout << "End charging matrix " << endl;
     45   bool iscomplex=false, isvector=false;
     46   int sym;
     47   getMarketHeader(args[1], sym, iscomplex, isvector);
     48 //   if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
     49   if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
     50   if (sym != 0) { // symmetric matrices, only the lower part is stored
     51     SparseMatrix<scalar, ColMajor> temp;
     52     temp = A;
     53     A = temp.selfadjointView<Lower>();
     54   }
     55   n = A.cols();
     56   /* Fill the right hand side */
     57 
     58   if (argc > 2)
     59     loadMarketVector(b, args[2]);
     60   else
     61   {
     62     b.resize(n);
     63     tmp.resize(n);
     64 //       tmp.setRandom();
     65     for (int i = 0; i < n; i++) tmp(i) = i;
     66     b = A * tmp ;
     67   }
     68 
     69   /* Compute the factorization */
     70 //   solver.isSymmetric(true);
     71   timer.start();
     72 //   solver.compute(A);
     73   solver.analyzePattern(A);
     74   timer.stop();
     75   cout << "Time to analyze " << timer.value() << std::endl;
     76   timer.reset();
     77   timer.start();
     78   solver.factorize(A);
     79   timer.stop();
     80   cout << "Factorize Time " << timer.value() << std::endl;
     81   timer.reset();
     82   timer.start();
     83   x = solver.solve(b);
     84   timer.stop();
     85   cout << "solve time " << timer.value() << std::endl;
     86   /* Check the accuracy */
     87   Matrix<scalar, Dynamic, 1> tmp2 = b - A*x;
     88   scalar tempNorm = tmp2.norm()/b.norm();
     89   cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
     90   cout << "Number of nonzeros in the factor : " << solver.nnzL() + solver.nnzU() << std::endl;
     91 
     92   return 0;
     93 }