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				| //===================================================== | |
| // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.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 EIGEN3_INTERFACE_HH | |
| #define EIGEN3_INTERFACE_HH | |
|  | |
| #include <Eigen/Eigen> | |
| #include <vector> | |
| #include "btl.hh" | |
|  | |
| using namespace Eigen; | |
| 
 | |
| template<class real, int SIZE=Dynamic> | |
| class eigen3_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 ) | |
|   { | |
|     return EIGEN_MAKESTRING(BTL_PREFIX); | |
|   } | |
| 
 | |
|   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.noalias() = A*B; | |
|   } | |
| 
 | |
|   static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){ | |
|     X.noalias() = A.transpose()*B.transpose(); | |
|   } | |
| 
 | |
| //   static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ | |
| //     X.noalias() = A.transpose()*A; | |
| //   } | |
|  | |
|   static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){ | |
|     X.template triangularView<Lower>().setZero(); | |
|     X.template selfadjointView<Lower>().rankUpdate(A); | |
|   } | |
| 
 | |
|   static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ | |
|     X.noalias() = A*B; | |
|   } | |
| 
 | |
|   static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ | |
|     X.noalias() = (A.template selfadjointView<Lower>() * B); | |
| //     internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1, X.data(), 1); | |
|   } | |
| 
 | |
|   template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src) | |
|   { | |
|     typedef typename Dest::Scalar Scalar; | |
|     typedef typename internal::packet_traits<Scalar>::type Packet; | |
|     const int PacketSize = sizeof(Packet)/sizeof(Scalar); | |
|     int size = dst.cols(); | |
|     for(int j=0; j<size; j+=1) | |
|     { | |
| //       const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask); | |
|       Scalar* A0 = dst.data() + j*dst.stride(); | |
|       int starti = j; | |
|       int alignedEnd = starti; | |
|       int alignedStart = (starti) + internal::first_aligned(&A0[starti], size-starti); | |
|       alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2); | |
| 
 | |
|       // do the non-vectorizable part of the assignment | |
|       for (int index = starti; index<alignedStart ; ++index) | |
|       { | |
|         if(Dest::Flags&RowMajorBit) | |
|           dst.copyCoeff(j, index, src); | |
|         else | |
|           dst.copyCoeff(index, j, src); | |
|       } | |
| 
 | |
|       // do the vectorizable part of the assignment | |
|       for (int index = alignedStart; index<alignedEnd; index+=PacketSize) | |
|       { | |
|         if(Dest::Flags&RowMajorBit) | |
|           dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src); | |
|         else | |
|           dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src); | |
|       } | |
| 
 | |
|       // do the non-vectorizable part of the assignment | |
|       for (int index = alignedEnd; index<size; ++index) | |
|       { | |
|         if(Dest::Flags&RowMajorBit) | |
|           dst.copyCoeff(j, index, src); | |
|         else | |
|           dst.copyCoeff(index, j, src); | |
|       } | |
|       //dst.col(j).tail(N-j) = src.col(j).tail(N-j); | |
|     } | |
|   } | |
| 
 | |
|   static EIGEN_DONT_INLINE void syr2(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){ | |
|     // internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1); | |
|     for(int j=0; j<N; ++j) | |
|       A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j); | |
|   } | |
| 
 | |
|   static EIGEN_DONT_INLINE void ger(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){ | |
|     for(int j=0; j<N; ++j) | |
|       A.col(j) += X * Y[j]; | |
|   } | |
| 
 | |
|   static EIGEN_DONT_INLINE void rot(gene_vector & A,  gene_vector & B, real c, real s, int N){ | |
|     internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s)); | |
|   } | |
| 
 | |
|   static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ | |
|     X.noalias() = (A.transpose()*B); | |
|   } | |
| 
 | |
|   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 EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){ | |
|     cible = source; | |
|   } | |
| 
 | |
|   static EIGEN_DONT_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 triangularView<Lower>().solve(B); | |
|   } | |
| 
 | |
|   static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ | |
|     X = L.template triangularView<Upper>().solve(B); | |
|   } | |
| 
 | |
|   static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ | |
|     X.noalias() = L.template triangularView<Lower>() * B; | |
|   } | |
| 
 | |
|   static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ | |
|     C = X; | |
|     internal::llt_inplace<real,Lower>::blocked(C); | |
|     //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.fullPivLu().matrixLU(); | |
|   } | |
| 
 | |
|   static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ | |
|     Matrix<DenseIndex,1,Dynamic> piv(N); | |
|     DenseIndex nb; | |
|     C = X; | |
|     internal::partial_lu_inplace(C,piv,nb); | |
| //     C = X.partialPivLu().matrixLU(); | |
|   } | |
| 
 | |
|   static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ | |
|     typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1); | |
|     C = X; | |
|     internal::tridiagonalization_inplace(C, aux); | |
|   } | |
| 
 | |
|   static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ | |
|     C = HessenbergDecomposition<gene_matrix>(X).packedMatrix(); | |
|   } | |
| 
 | |
| 
 | |
| 
 | |
| }; | |
| 
 | |
| #endif
 |