Disabled external gits

cs440-acg/ext/eigen/bench/spbench/sp_solver.cpp

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+// Small bench routine for Eigen available in Eigen
+// (C) Desire NUENTSA WAKAM, INRIA
+
+#include <iostream>
+#include <fstream>
+#include <iomanip>
+#include <Eigen/Jacobi>
+#include <Eigen/Householder>
+#include <Eigen/IterativeLinearSolvers>
+#include <Eigen/LU>
+#include <unsupported/Eigen/SparseExtra>
+//#include <Eigen/SparseLU>
+#include <Eigen/SuperLUSupport>
+// #include <unsupported/Eigen/src/IterativeSolvers/Scaling.h>
+#include <bench/BenchTimer.h>
+#include <unsupported/Eigen/IterativeSolvers>
+using namespace std;
+using namespace Eigen;
+
+int main(int argc, char **args)
+{
+  SparseMatrix<double, ColMajor> A; 
+  typedef SparseMatrix<double, ColMajor>::Index Index;
+  typedef Matrix<double, Dynamic, Dynamic> DenseMatrix;
+  typedef Matrix<double, Dynamic, 1> DenseRhs;
+  VectorXd b, x, tmp;
+  BenchTimer timer,totaltime; 
+  //SparseLU<SparseMatrix<double, ColMajor> >   solver;
+//   SuperLU<SparseMatrix<double, ColMajor> >   solver;
+  ConjugateGradient<SparseMatrix<double, ColMajor>, Lower,IncompleteCholesky<double,Lower> > solver; 
+  ifstream matrix_file; 
+  string line;
+  int  n;
+  // Set parameters
+//   solver.iparm(IPARM_THREAD_NBR) = 4;
+  /* 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 ");
+  
+  timer.start();
+  totaltime.start();
+  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<double, ColMajor> temp; 
+    temp = A;
+    A = temp.selfadjointView<Lower>();
+  }
+  timer.stop();
+  
+  n = A.cols();
+  // ====== TESTS FOR SPARSE TUTORIAL ======
+//   cout<< "OuterSize " << A.outerSize() << " inner " << A.innerSize() << endl; 
+//   SparseMatrix<double, RowMajor> mat1(A); 
+//   SparseMatrix<double, RowMajor> mat2;
+//   cout << " norm of A " << mat1.norm() << endl; ;
+//   PermutationMatrix<Dynamic, Dynamic, int> perm(n);
+//   perm.resize(n,1);
+//   perm.indices().setLinSpaced(n, 0, n-1);
+//   mat2 = perm * mat1;
+//   mat.subrows();
+//   mat2.resize(n,n); 
+//   mat2.reserve(10);
+//   mat2.setConstant();
+//   std::cout<< "NORM " << mat1.squaredNorm()<< endl;  
+
+  cout<< "Time to load the matrix " << timer.value() <<endl;
+  /* Fill the right hand side */
+
+//   solver.set_restart(374);
+  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 ;
+  }
+//   Scaling<SparseMatrix<double> > scal; 
+//   scal.computeRef(A);
+//   b = scal.LeftScaling().cwiseProduct(b);
+
+  /* Compute the factorization */
+  cout<< "Starting the factorization "<< endl; 
+  timer.reset();
+  timer.start(); 
+  cout<< "Size of Input Matrix "<< b.size()<<"\n\n";
+  cout<< "Rows and columns "<< A.rows() <<" " <<A.cols() <<"\n";
+  solver.compute(A);
+//   solver.analyzePattern(A);
+//   solver.factorize(A);
+  if (solver.info() != Success) {
+    std::cout<< "The solver failed \n";
+    return -1; 
+  }
+  timer.stop(); 
+  float time_comp = timer.value(); 
+  cout <<" Compute Time " << time_comp<< endl; 
+  
+  timer.reset();
+  timer.start();
+  x = solver.solve(b);
+//   x = scal.RightScaling().cwiseProduct(x);
+  timer.stop();
+  float time_solve = timer.value(); 
+  cout<< " Time to solve " << time_solve << endl; 
+ 
+  /* Check the accuracy */
+  VectorXd tmp2 = b - A*x;
+  double tempNorm = tmp2.norm()/b.norm();
+  cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+//   cout << "Iterations : " << solver.iterations() << "\n"; 
+  
+  totaltime.stop();
+  cout << "Total time " << totaltime.value() << "\n";
+//  std::cout<<x.transpose()<<"\n";
+  
+  return 0;
+}