| //===================================================== |
| // 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 |