don't index Eigen

1 files changed, 0 insertions, 323 deletions

diff --git a/eigen/bench/sparse_product.cpp b/eigen/bench/sparse_product.cpp
deleted file mode 100644
index d2fc44f..0000000
--- a/eigen/bench/sparse_product.cpp
+++ /dev/null
@@ -1,323 +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 -DCSPARSE
-// -I /home/gael/Coding/LinearAlgebra/CSparse/Include/ /home/gael/Coding/LinearAlgebra/CSparse/Lib/libcsparse.a
-
-#include <typeinfo>
-
-#ifndef SIZE
-#define SIZE 1000000
-#endif
-
-#ifndef NNZPERCOL
-#define NNZPERCOL 6
-#endif
-
-#ifndef REPEAT
-#define REPEAT 1
-#endif
-
-#include <algorithm>
-#include "BenchTimer.h"
-#include "BenchUtil.h"
-#include "BenchSparseUtil.h"
-
-#ifndef NBTRIES
-#define NBTRIES 1
-#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(); }
-
-// #ifdef MKL
-//
-// #include "mkl_types.h"
-// #include "mkl_spblas.h"
-//
-// template<typename Lhs,typename Rhs,typename Res>
-// void mkl_multiply(const Lhs& lhs, const Rhs& rhs, Res& res)
-// {
-//   char n = 'N';
-//   float alpha = 1;
-//   char matdescra[6];
-//   matdescra[0] = 'G';
-//   matdescra[1] = 0;
-//   matdescra[2] = 0;
-//   matdescra[3] = 'C';
-//   mkl_scscmm(&n, lhs.rows(), rhs.cols(), lhs.cols(), &alpha, matdescra,
-//              lhs._valuePtr(), lhs._innerIndexPtr(), lhs.outerIndexPtr(),
-//              pntre, b, &ldb, &beta, c, &ldc);
-// //   mkl_somatcopy('C', 'T', lhs.rows(), lhs.cols(), 1,
-// //                 lhs._valuePtr(), lhs.rows(), DST, dst_stride);
-// }
-//
-// #endif
-
-
-#ifdef CSPARSE
-cs* cs_sorted_multiply(const cs* a, const cs* b)
-{
-//   return cs_multiply(a,b);
-
-  cs* A = cs_transpose(a, 1);
-  cs* B = cs_transpose(b, 1);
-  cs* D = cs_multiply(B,A);   /* D = B'*A' */
-  cs_spfree (A) ;
-  cs_spfree (B) ;
-  cs_dropzeros (D) ;      /* drop zeros from D */
-  cs* C = cs_transpose (D, 1) ;   /* C = D', so that C is sorted */
-  cs_spfree (D) ;
-  return C;
-
-//   cs* A = cs_transpose(a, 1);
-//   cs* C = cs_transpose(A, 1);
-//   return C;
-}
-
-cs* cs_sorted_multiply2(const cs* a, const cs* b)
-{
-  cs* D = cs_multiply(a,b);
-  cs* E = cs_transpose(D,1);
-  cs_spfree(D);
-  cs* C = cs_transpose(E,1);
-  cs_spfree(E);
-  return C;
-}
-#endif
-
-void bench_sort();
-
-int main(int argc, char *argv[])
-{
-//   bench_sort();
-
-  int rows = SIZE;
-  int cols = SIZE;
-  float density = DENSITY;
-
-  EigenSparseMatrix sm1(rows,cols), sm2(rows,cols), sm3(rows,cols), sm4(rows,cols);
-
-  BenchTimer timer;
-  for (int nnzPerCol = NNZPERCOL; nnzPerCol>1; nnzPerCol/=1.1)
-  {
-    sm1.setZero();
-    sm2.setZero();
-    fillMatrix2(nnzPerCol, rows, cols, sm1);
-    fillMatrix2(nnzPerCol, rows, cols, sm2);
-//     std::cerr << "filling OK\n";
-
-    // dense matrices
-    #ifdef DENSEMATRIX
-    {
-      std::cout << "Eigen Dense\t" << nnzPerCol << "%\n";
-      DenseMatrix m1(rows,cols), m2(rows,cols), m3(rows,cols);
-      eiToDense(sm1, m1);
-      eiToDense(sm2, m2);
-
-      timer.reset();
-      timer.start();
-      for (int k=0; k<REPEAT; ++k)
-        m3 = m1 * m2;
-      timer.stop();
-      std::cout << "   a * b:\t" << timer.value() << endl;
-
-      timer.reset();
-      timer.start();
-      for (int k=0; k<REPEAT; ++k)
-        m3 = m1.transpose() * m2;
-      timer.stop();
-      std::cout << "   a' * b:\t" << timer.value() << endl;
-
-      timer.reset();
-      timer.start();
-      for (int k=0; k<REPEAT; ++k)
-        m3 = m1.transpose() * m2.transpose();
-      timer.stop();
-      std::cout << "   a' * b':\t" << timer.value() << endl;
-
-      timer.reset();
-      timer.start();
-      for (int k=0; k<REPEAT; ++k)
-        m3 = m1 * m2.transpose();
-      timer.stop();
-      std::cout << "   a * b':\t" << timer.value() << endl;
-    }
-    #endif
-
-    // eigen sparse matrices
-    {
-      std::cout << "Eigen sparse\t" << sm1.nonZeros()/(float(sm1.rows())*float(sm1.cols()))*100 << "% * "
-                << sm2.nonZeros()/(float(sm2.rows())*float(sm2.cols()))*100 << "%\n";
-
-      BENCH(sm3 = sm1 * sm2; )
-      std::cout << "   a * b:\t" << timer.value() << endl;
-
-//       BENCH(sm3 = sm1.transpose() * sm2; )
-//       std::cout << "   a' * b:\t" << timer.value() << endl;
-// //
-//       BENCH(sm3 = sm1.transpose() * sm2.transpose(); )
-//       std::cout << "   a' * b':\t" << timer.value() << endl;
-// //
-//       BENCH(sm3 = sm1 * sm2.transpose(); )
-//       std::cout << "   a * b' :\t" << timer.value() << endl;
-
-
-//       std::cout << "\n";
-//
-//       BENCH( sm3._experimentalNewProduct(sm1, sm2); )
-//       std::cout << "   a * b:\t" << timer.value() << endl;
-//
-//       BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2); )
-//       std::cout << "   a' * b:\t" << timer.value() << endl;
-// //
-//       BENCH(sm3._experimentalNewProduct(sm1.transpose(),sm2.transpose()); )
-//       std::cout << "   a' * b':\t" << timer.value() << endl;
-// //
-//       BENCH(sm3._experimentalNewProduct(sm1, sm2.transpose());)
-//       std::cout << "   a * b' :\t" << timer.value() << endl;
-    }
-
-    // eigen dyn-sparse matrices
-    /*{
-      DynamicSparseMatrix<Scalar> m1(sm1), m2(sm2), m3(sm3);
-      std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/(float(m1.rows())*float(m1.cols()))*100 << "% * "
-                << m2.nonZeros()/(float(m2.rows())*float(m2.cols()))*100 << "%\n";
-
-//       timer.reset();
-//       timer.start();
-      BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1 * m2;)
-//       timer.stop();
-      std::cout << "   a * b:\t" << timer.value() << endl;
-//       std::cout << sm3 << "\n";
-
-      timer.reset();
-      timer.start();
-//       std::cerr << "transpose...\n";
-//       EigenSparseMatrix sm4 = sm1.transpose();
-//       std::cout << sm4.nonZeros() << " == " << sm1.nonZeros() << "\n";
-//       exit(1);
-//       std::cerr << "transpose OK\n";
-//       std::cout << sm1 << "\n\n" << sm1.transpose() << "\n\n" << sm4.transpose() << "\n\n";
-      BENCH(for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2;)
-//       timer.stop();
-      std::cout << "   a' * b:\t" << timer.value() << endl;
-
-//       timer.reset();
-//       timer.start();
-      BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1.transpose() * m2.transpose(); )
-//       timer.stop();
-      std::cout << "   a' * b':\t" << timer.value() << endl;
-
-//       timer.reset();
-//       timer.start();
-      BENCH( for (int k=0; k<REPEAT; ++k) m3 = m1 * m2.transpose(); )
-//       timer.stop();
-      std::cout << "   a * b' :\t" << timer.value() << endl;
-    }*/
-
-    // CSparse
-    #ifdef CSPARSE
-    {
-      std::cout << "CSparse \t" << nnzPerCol << "%\n";
-      cs *m1, *m2, *m3;
-      eiToCSparse(sm1, m1);
-      eiToCSparse(sm2, m2);
-
-      BENCH(
-      {
-        m3 = cs_sorted_multiply(m1, m2);
-        if (!m3)
-        {
-          std::cerr << "cs_multiply failed\n";
-        }
-//         cs_print(m3, 0);
-        cs_spfree(m3);
-      }
-      );
-//       timer.stop();
-      std::cout << "   a * b:\t" << timer.value() << endl;
-
-//       BENCH( { m3 = cs_sorted_multiply2(m1, m2); cs_spfree(m3); } );
-//       std::cout << "   a * b:\t" << timer.value() << endl;
-    }
-    #endif
-
-    #ifndef NOUBLAS
-    {
-      std::cout << "ublas\t" << nnzPerCol << "%\n";
-      UBlasSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
-      eiToUblas(sm1, m1);
-      eiToUblas(sm2, m2);
-
-      BENCH(boost::numeric::ublas::prod(m1, m2, m3););
-      std::cout << "   a * b:\t" << timer.value() << endl;
-    }
-    #endif
-
-    // GMM++
-    #ifndef NOGMM
-    {
-      std::cout << "GMM++ sparse\t" << nnzPerCol << "%\n";
-      GmmDynSparse  gmmT3(rows,cols);
-      GmmSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
-      eiToGmm(sm1, m1);
-      eiToGmm(sm2, m2);
-
-      BENCH(gmm::mult(m1, m2, gmmT3););
-      std::cout << "   a * b:\t" << timer.value() << endl;
-
-//       BENCH(gmm::mult(gmm::transposed(m1), m2, gmmT3););
-//       std::cout << "   a' * b:\t" << timer.value() << endl;
-//
-//       if (rows<500)
-//       {
-//         BENCH(gmm::mult(gmm::transposed(m1), gmm::transposed(m2), gmmT3););
-//         std::cout << "   a' * b':\t" << timer.value() << endl;
-//
-//         BENCH(gmm::mult(m1, gmm::transposed(m2), gmmT3););
-//         std::cout << "   a * b':\t" << timer.value() << endl;
-//       }
-//       else
-//       {
-//         std::cout << "   a' * b':\t" << "forever" << endl;
-//         std::cout << "   a * b':\t" << "forever" << endl;
-//       }
-    }
-    #endif
-
-    // MTL4
-    #ifndef NOMTL
-    {
-      std::cout << "MTL4\t" << nnzPerCol << "%\n";
-      MtlSparse m1(rows,cols), m2(rows,cols), m3(rows,cols);
-      eiToMtl(sm1, m1);
-      eiToMtl(sm2, m2);
-
-      BENCH(m3 = m1 * m2;);
-      std::cout << "   a * b:\t" << timer.value() << endl;
-
-//       BENCH(m3 = trans(m1) * m2;);
-//       std::cout << "   a' * b:\t" << timer.value() << endl;
-//
-//       BENCH(m3 = trans(m1) * trans(m2););
-//       std::cout << "  a' * b':\t" << timer.value() << endl;
-//
-//       BENCH(m3 = m1 * trans(m2););
-//       std::cout << "   a * b' :\t" << timer.value() << endl;
-    }
-    #endif
-
-    std::cout << "\n\n";
-  }
-
-  return 0;
-}
-
-
-