1 files changed, 0 insertions, 220 deletions
diff --git a/eigen/bench/sparse_trisolver.cpp b/eigen/bench/sparse_trisolver.cpp
deleted file mode 100644
index 13f4f0a..0000000
--- a/eigen/bench/sparse_trisolver.cpp
+++ /dev/null
@@ -1,220 +0,0 @@
-
-//g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.005 -DSIZE=10000 && ./a.out
-//g++ -O3 -g0 -DNDEBUG  sparse_product.cpp -I.. -I/home/gael/Coding/LinearAlgebra/mtl4/ -DDENSITY=0.05 -DSIZE=2000 && ./a.out
-// -DNOGMM -DNOMTL
-// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
-
-#ifndef SIZE
-#define SIZE 10000
-#endif
-
-#ifndef DENSITY
-#define DENSITY 0.01
-#endif
-
-#ifndef REPEAT
-#define REPEAT 1
-#endif
-
-#include "BenchSparseUtil.h"
-
-#ifndef MINDENSITY
-#define MINDENSITY 0.0004
-#endif
-
-#ifndef NBTRIES
-#define NBTRIES 10
-#endif
-
-#define BENCH(X) \
-  timer.reset(); \
-  for (int _j=0; _j<NBTRIES; ++_j) { \
-    timer.start(); \
-    for (int _k=0; _k<REPEAT; ++_k) { \
-        X  \
-  } timer.stop(); }
-
-typedef SparseMatrix<Scalar,UpperTriangular> EigenSparseTriMatrix;
-typedef SparseMatrix<Scalar,RowMajorBit|UpperTriangular> EigenSparseTriMatrixRow;
-
-void fillMatrix(float density, int rows, int cols,  EigenSparseTriMatrix& dst)
-{
-  dst.startFill(rows*cols*density);
-  for(int j = 0; j < cols; j++)
-  {
-    for(int i = 0; i < j; i++)
-    {
-      Scalar v = (internal::random<float>(0,1) < density) ? internal::random<Scalar>() : 0;
-      if (v!=0)
-        dst.fill(i,j) = v;
-    }
-    dst.fill(j,j) = internal::random<Scalar>();
-  }
-  dst.endFill();
-}
-
-int main(int argc, char *argv[])
-{
-  int rows = SIZE;
-  int cols = SIZE;
-  float density = DENSITY;
-  BenchTimer timer;
-  #if 1
-  EigenSparseTriMatrix sm1(rows,cols);
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  DenseVector b = DenseVector::Random(cols);
-  DenseVector x = DenseVector::Random(cols);
-
-  bool densedone = false;
-
-  for (float density = DENSITY; density>=MINDENSITY; density*=0.5)
-  {
-    EigenSparseTriMatrix sm1(rows, cols);
-    fillMatrix(density, rows, cols, sm1);
-
-    // dense matrices
-    #ifdef DENSEMATRIX
-    if (!densedone)
-    {
-      densedone = true;
-      std::cout << "Eigen Dense\t" << density*100 << "%\n";
-      DenseMatrix m1(rows,cols);
-      Matrix<Scalar,Dynamic,Dynamic,Dynamic,Dynamic,RowMajorBit> m2(rows,cols);
-      eiToDense(sm1, m1);
-      m2 = m1;
-
-      BENCH(x = m1.marked<UpperTriangular>().solveTriangular(b);)
-      std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x.transpose() << "\n";
-
-      BENCH(x = m2.marked<UpperTriangular>().solveTriangular(b);)
-      std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x.transpose() << "\n";
-    }
-    #endif
-
-    // eigen sparse matrices
-    {
-      std::cout << "Eigen sparse\t" << density*100 << "%\n";
-      EigenSparseTriMatrixRow sm2 = sm1;
-
-      BENCH(x = sm1.solveTriangular(b);)
-      std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x.transpose() << "\n";
-
-      BENCH(x = sm2.solveTriangular(b);)
-      std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x.transpose() << "\n";
-
-//       x = b;
-//       BENCH(sm1.inverseProductInPlace(x);)
-//       std::cout << "   colmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
-//       std::cerr << x.transpose() << "\n";
-//
-//       x = b;
-//       BENCH(sm2.inverseProductInPlace(x);)
-//       std::cout << "   rowmajor^-1 * b:\t" << timer.value() << " (inplace)" << endl;
-//       std::cerr << x.transpose() << "\n";
-    }
-
-
-
-    // CSparse
-    #ifdef CSPARSE
-    {
-      std::cout << "CSparse \t" << density*100 << "%\n";
-      cs *m1;
-      eiToCSparse(sm1, m1);
-
-      BENCH(x = b; if (!cs_lsolve (m1, x.data())){std::cerr << "cs_lsolve failed\n"; break;}; )
-      std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
-    }
-    #endif
-
-    // GMM++
-    #ifndef NOGMM
-    {
-      std::cout << "GMM++ sparse\t" << density*100 << "%\n";
-      GmmSparse m1(rows,cols);
-      gmm::csr_matrix<Scalar> m2;
-      eiToGmm(sm1, m1);
-      gmm::copy(m1,m2);
-      std::vector<Scalar> gmmX(cols), gmmB(cols);
-      Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols) = x;
-      Map<Matrix<Scalar,Dynamic,1> >(&gmmB[0], cols) = b;
-
-      gmmX = gmmB;
-      BENCH(gmm::upper_tri_solve(m1, gmmX, false);)
-      std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
-
-      gmmX = gmmB;
-      BENCH(gmm::upper_tri_solve(m2, gmmX, false);)
-      timer.stop();
-      std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << Map<Matrix<Scalar,Dynamic,1> >(&gmmX[0], cols).transpose() << "\n";
-    }
-    #endif
-
-    // MTL4
-    #ifndef NOMTL
-    {
-      std::cout << "MTL4\t" << density*100 << "%\n";
-      MtlSparse m1(rows,cols);
-      MtlSparseRowMajor m2(rows,cols);
-      eiToMtl(sm1, m1);
-      m2 = m1;
-      mtl::dense_vector<Scalar> x(rows, 1.0);
-      mtl::dense_vector<Scalar> b(rows, 1.0);
-
-      BENCH(x = mtl::upper_trisolve(m1,b);)
-      std::cout << "   colmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x << "\n";
-
-      BENCH(x = mtl::upper_trisolve(m2,b);)
-      std::cout << "   rowmajor^-1 * b:\t" << timer.value() << endl;
-//       std::cerr << x << "\n";
-    }
-    #endif
-
-
-    std::cout << "\n\n";
-  }
-  #endif
-
-  #if 0
-    // bench small matrices (in-place versus return bye value)
-    {
-      timer.reset();
-      for (int _j=0; _j<10; ++_j) {
-        Matrix4f m = Matrix4f::Random();
-        Vector4f b = Vector4f::Random();
-        Vector4f x = Vector4f::Random();
-        timer.start();
-        for (int _k=0; _k<1000000; ++_k) {
-          b = m.inverseProduct(b);
-        }
-        timer.stop();
-      }
-      std::cout << "4x4 :\t" << timer.value() << endl;
-    }
-
-    {
-      timer.reset();
-      for (int _j=0; _j<10; ++_j) {
-        Matrix4f m = Matrix4f::Random();
-        Vector4f b = Vector4f::Random();
-        Vector4f x = Vector4f::Random();
-        timer.start();
-        for (int _k=0; _k<1000000; ++_k) {
-          m.inverseProductInPlace(x);
-        }
-        timer.stop();
-      }
-      std::cout << "4x4 IP :\t" << timer.value() << endl;
-    }
-  #endif
-
-  return 0;
-}
-