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authorGravatar Desire NUENTSA <desire.nuentsa_wakam@inria.fr>2012-06-14 18:45:04 +0200
committerGravatar Desire NUENTSA <desire.nuentsa_wakam@inria.fr>2012-06-14 18:45:04 +0200
commit0c9b08e46e7507d9f13200f0702bc57ed6aae52c (patch)
treebc319fe32b4bdfa8dd601082e25c508606f53853 /bench/spbench
parentf8a0745cb0426eb3095dbea24288a64eddab04f0 (diff)
build complete... almost
Diffstat (limited to 'bench/spbench')
-rw-r--r--bench/spbench/test_sparseLU.cpp64
1 files changed, 64 insertions, 0 deletions
diff --git a/bench/spbench/test_sparseLU.cpp b/bench/spbench/test_sparseLU.cpp
new file mode 100644
index 000000000..0bbbb0627
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+++ 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