From 0c9b08e46e7507d9f13200f0702bc57ed6aae52c Mon Sep 17 00:00:00 2001
From: Desire NUENTSA <desire.nuentsa_wakam@inria.fr>
Date: Thu, 14 Jun 2012 18:45:04 +0200
Subject: build complete... almost

---
 bench/spbench/test_sparseLU.cpp | 64 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 64 insertions(+)
 create mode 100644 bench/spbench/test_sparseLU.cpp

(limited to 'bench/spbench')

diff --git a/bench/spbench/test_sparseLU.cpp b/bench/spbench/test_sparseLU.cpp
new file mode 100644
index 000000000..0bbbb0627
--- /dev/null
+++ b/bench/spbench/test_sparseLU.cpp
@@ -0,0 +1,64 @@
+// 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>
+
+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;
+  SparseLU<SparseMatrix<double, ColMajor>, AMDOrdering<double, int> >   solver;
+  ifstream matrix_file; 
+  string line;
+  int  n;
+  
+  // 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<double, 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.compute(A);
+  
+  solver._solve(b, x);
+  /* Check the accuracy */
+  VectorXd tmp2 = b - A*x;
+  double tempNorm = tmp2.norm()/b.norm();
+  cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+  
+  return 0;
+}
\ No newline at end of file
-- 
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