eigen/bench/btl/libs/eigen2/eigen2_interface.hh

//=====================================================
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
//=====================================================
//
// This program is free software; you can redistribute it and/or
// modify it under the terms of the GNU General Public License
// as published by the Free Software Foundation; either version 2
// of the License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU General Public License for more details.
// You should have received a copy of the GNU General Public License
// along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
//
#ifndef EIGEN2_INTERFACE_HH
#define EIGEN2_INTERFACE_HH
// #include <cblas.h>
#include <Eigen/Core>
#include <Eigen/Cholesky>
#include <Eigen/LU>
#include <Eigen/QR>
#include <vector>
#include "btl.hh"

using namespace Eigen;

template <class real, int SIZE = Dynamic>
class eigen2_interface {
 public:
  enum { IsFixedSize = (SIZE != Dynamic) };

  typedef real real_type;

  typedef std::vector<real> stl_vector;
  typedef std::vector<stl_vector> stl_matrix;

  typedef Eigen::Matrix<real, SIZE, SIZE> gene_matrix;
  typedef Eigen::Matrix<real, SIZE, 1> gene_vector;

  static inline std::string name(void) {
#if defined(EIGEN_VECTORIZE_SSE)
    if (SIZE == Dynamic)
      return "eigen2";
    else
      return "tiny_eigen2";
#elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
    if (SIZE == Dynamic)
      return "eigen2";
    else
      return "tiny_eigen2";
#else
    if (SIZE == Dynamic)
      return "eigen2_novec";
    else
      return "tiny_eigen2_novec";
#endif
  }

  static void free_matrix(gene_matrix& A, int N) {}

  static void free_vector(gene_vector& B) {}

  static BTL_DONT_INLINE void matrix_from_stl(gene_matrix& A, stl_matrix& A_stl) {
    A.resize(A_stl[0].size(), A_stl.size());

    for (int j = 0; j < A_stl.size(); j++) {
      for (int i = 0; i < A_stl[j].size(); i++) {
        A.coeffRef(i, j) = A_stl[j][i];
      }
    }
  }

  static BTL_DONT_INLINE void vector_from_stl(gene_vector& B, stl_vector& B_stl) {
    B.resize(B_stl.size(), 1);

    for (int i = 0; i < B_stl.size(); i++) {
      B.coeffRef(i) = B_stl[i];
    }
  }

  static BTL_DONT_INLINE void vector_to_stl(gene_vector& B, stl_vector& B_stl) {
    for (int i = 0; i < B_stl.size(); i++) {
      B_stl[i] = B.coeff(i);
    }
  }

  static BTL_DONT_INLINE void matrix_to_stl(gene_matrix& A, stl_matrix& A_stl) {
    int N = A_stl.size();

    for (int j = 0; j < N; j++) {
      A_stl[j].resize(N);
      for (int i = 0; i < N; i++) {
        A_stl[j][i] = A.coeff(i, j);
      }
    }
  }

  static inline void matrix_matrix_product(const gene_matrix& A, const gene_matrix& B, gene_matrix& X, int N) {
    X = (A * B).lazy();
  }

  static inline void transposed_matrix_matrix_product(const gene_matrix& A, const gene_matrix& B, gene_matrix& X,
                                                      int N) {
    X = (A.transpose() * B.transpose()).lazy();
  }

  static inline void ata_product(const gene_matrix& A, gene_matrix& X, int N) { X = (A.transpose() * A).lazy(); }

  static inline void aat_product(const gene_matrix& A, gene_matrix& X, int N) { X = (A * A.transpose()).lazy(); }

  static inline void matrix_vector_product(const gene_matrix& A, const gene_vector& B, gene_vector& X, int N) {
    X = (A * B) /*.lazy()*/;
  }

  static inline void atv_product(gene_matrix& A, gene_vector& B, gene_vector& X, int N) {
    X = (A.transpose() * B) /*.lazy()*/;
  }

  static inline void axpy(real coef, const gene_vector& X, gene_vector& Y, int N) { Y += coef * X; }

  static inline void axpby(real a, const gene_vector& X, real b, gene_vector& Y, int N) { Y = a * X + b * Y; }

  static inline void copy_matrix(const gene_matrix& source, gene_matrix& cible, int N) { cible = source; }

  static inline void copy_vector(const gene_vector& source, gene_vector& cible, int N) { cible = source; }

  static inline void trisolve_lower(const gene_matrix& L, const gene_vector& B, gene_vector& X, int N) {
    X = L.template marked<LowerTriangular>().solveTriangular(B);
  }

  static inline void trisolve_lower_matrix(const gene_matrix& L, const gene_matrix& B, gene_matrix& X, int N) {
    X = L.template marked<LowerTriangular>().solveTriangular(B);
  }

  static inline void cholesky(const gene_matrix& X, gene_matrix& C, int N) {
    C = X.llt().matrixL();
    //     C = X;
    //     Cholesky<gene_matrix>::computeInPlace(C);
    //     Cholesky<gene_matrix>::computeInPlaceBlock(C);
  }

  static inline void lu_decomp(const gene_matrix& X, gene_matrix& C, int N) {
    C = X.lu().matrixLU();
    //     C = X.inverse();
  }

  static inline void tridiagonalization(const gene_matrix& X, gene_matrix& C, int N) {
    C = Tridiagonalization<gene_matrix>(X).packedMatrix();
  }

  static inline void hessenberg(const gene_matrix& X, gene_matrix& C, int N) {
    C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
  }
};

#endif