From f0238cfb6997c4acfc2bd200de7295f3fa36968f Mon Sep 17 00:00:00 2001
From: Stanislaw Halik <sthalik@misaki.pl>
Date: Sun, 3 Mar 2019 21:09:10 +0100
Subject: don't index Eigen

---
 eigen/bench/spbench/test_sparseLU.cpp | 93 -----------------------------------
 1 file changed, 93 deletions(-)
 delete mode 100644 eigen/bench/spbench/test_sparseLU.cpp

(limited to 'eigen/bench/spbench/test_sparseLU.cpp')

diff --git a/eigen/bench/spbench/test_sparseLU.cpp b/eigen/bench/spbench/test_sparseLU.cpp
deleted file mode 100644
index f8ecbe6..0000000
--- a/eigen/bench/spbench/test_sparseLU.cpp
+++ /dev/null
@@ -1,93 +0,0 @@
-// Small bench routine for Eigen available in Eigen
-// (C) Desire NUENTSA WAKAM, INRIA
-
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <unsupported/Eigen/SparseExtra>
-#include <Eigen/SparseLU>
-#include <bench/BenchTimer.h>
-#ifdef EIGEN_METIS_SUPPORT
-#include <Eigen/MetisSupport>
-#endif
-
-using namespace std;
-using namespace Eigen;
-
-int main(int argc, char **args)
-{
-//   typedef complex<double> scalar; 
-  typedef double scalar; 
-  SparseMatrix<scalar, ColMajor> A; 
-  typedef SparseMatrix<scalar, ColMajor>::Index Index;
-  typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;
-  typedef Matrix<scalar, Dynamic, 1> DenseRhs;
-  Matrix<scalar, Dynamic, 1> b, x, tmp;
-//   SparseLU<SparseMatrix<scalar, ColMajor>, AMDOrdering<int> >   solver;
-// #ifdef EIGEN_METIS_SUPPORT
-//   SparseLU<SparseMatrix<scalar, ColMajor>, MetisOrdering<int> > solver; 
-//   std::cout<< "ORDERING : METIS\n"; 
-// #else
-  SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> >  solver;
-  std::cout<< "ORDERING : COLAMD\n"; 
-// #endif
-  
-  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;
-}
\ No newline at end of file
-- 
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