Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame^] | 1 | //===================================================== |
| 2 | // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> |
| 3 | //===================================================== |
| 4 | // |
| 5 | // This program is free software; you can redistribute it and/or |
| 6 | // modify it under the terms of the GNU General Public License |
| 7 | // as published by the Free Software Foundation; either version 2 |
| 8 | // of the License, or (at your option) any later version. |
| 9 | // |
| 10 | // This program is distributed in the hope that it will be useful, |
| 11 | // but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 12 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| 13 | // GNU General Public License for more details. |
| 14 | // You should have received a copy of the GNU General Public License |
| 15 | // along with this program; if not, write to the Free Software |
| 16 | // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. |
| 17 | // |
| 18 | #ifndef EIGEN3_INTERFACE_HH |
| 19 | #define EIGEN3_INTERFACE_HH |
| 20 | |
| 21 | #include <Eigen/Eigen> |
| 22 | #include <vector> |
| 23 | #include "btl.hh" |
| 24 | |
| 25 | using namespace Eigen; |
| 26 | |
| 27 | template<class real, int SIZE=Dynamic> |
| 28 | class eigen3_interface |
| 29 | { |
| 30 | |
| 31 | public : |
| 32 | |
| 33 | enum {IsFixedSize = (SIZE!=Dynamic)}; |
| 34 | |
| 35 | typedef real real_type; |
| 36 | |
| 37 | typedef std::vector<real> stl_vector; |
| 38 | typedef std::vector<stl_vector> stl_matrix; |
| 39 | |
| 40 | typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix; |
| 41 | typedef Eigen::Matrix<real,SIZE,1> gene_vector; |
| 42 | |
| 43 | static inline std::string name( void ) |
| 44 | { |
| 45 | return EIGEN_MAKESTRING(BTL_PREFIX); |
| 46 | } |
| 47 | |
| 48 | static void free_matrix(gene_matrix & A, int N) {} |
| 49 | |
| 50 | static void free_vector(gene_vector & B) {} |
| 51 | |
| 52 | static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){ |
| 53 | A.resize(A_stl[0].size(), A_stl.size()); |
| 54 | |
| 55 | for (int j=0; j<A_stl.size() ; j++){ |
| 56 | for (int i=0; i<A_stl[j].size() ; i++){ |
| 57 | A.coeffRef(i,j) = A_stl[j][i]; |
| 58 | } |
| 59 | } |
| 60 | } |
| 61 | |
| 62 | static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){ |
| 63 | B.resize(B_stl.size(),1); |
| 64 | |
| 65 | for (int i=0; i<B_stl.size() ; i++){ |
| 66 | B.coeffRef(i) = B_stl[i]; |
| 67 | } |
| 68 | } |
| 69 | |
| 70 | static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){ |
| 71 | for (int i=0; i<B_stl.size() ; i++){ |
| 72 | B_stl[i] = B.coeff(i); |
| 73 | } |
| 74 | } |
| 75 | |
| 76 | static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){ |
| 77 | int N=A_stl.size(); |
| 78 | |
| 79 | for (int j=0;j<N;j++){ |
| 80 | A_stl[j].resize(N); |
| 81 | for (int i=0;i<N;i++){ |
| 82 | A_stl[j][i] = A.coeff(i,j); |
| 83 | } |
| 84 | } |
| 85 | } |
| 86 | |
| 87 | static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){ |
| 88 | X.noalias() = A*B; |
| 89 | } |
| 90 | |
| 91 | static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){ |
| 92 | X.noalias() = A.transpose()*B.transpose(); |
| 93 | } |
| 94 | |
| 95 | // static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ |
| 96 | // X.noalias() = A.transpose()*A; |
| 97 | // } |
| 98 | |
| 99 | static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){ |
| 100 | X.template triangularView<Lower>().setZero(); |
| 101 | X.template selfadjointView<Lower>().rankUpdate(A); |
| 102 | } |
| 103 | |
| 104 | static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ |
| 105 | X.noalias() = A*B; |
| 106 | } |
| 107 | |
| 108 | static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ |
| 109 | X.noalias() = (A.template selfadjointView<Lower>() * B); |
| 110 | // internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1, X.data(), 1); |
| 111 | } |
| 112 | |
| 113 | template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src) |
| 114 | { |
| 115 | typedef typename Dest::Scalar Scalar; |
| 116 | typedef typename internal::packet_traits<Scalar>::type Packet; |
| 117 | const int PacketSize = sizeof(Packet)/sizeof(Scalar); |
| 118 | int size = dst.cols(); |
| 119 | for(int j=0; j<size; j+=1) |
| 120 | { |
| 121 | // const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask); |
| 122 | Scalar* A0 = dst.data() + j*dst.stride(); |
| 123 | int starti = j; |
| 124 | int alignedEnd = starti; |
| 125 | int alignedStart = (starti) + internal::first_aligned(&A0[starti], size-starti); |
| 126 | alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2); |
| 127 | |
| 128 | // do the non-vectorizable part of the assignment |
| 129 | for (int index = starti; index<alignedStart ; ++index) |
| 130 | { |
| 131 | if(Dest::Flags&RowMajorBit) |
| 132 | dst.copyCoeff(j, index, src); |
| 133 | else |
| 134 | dst.copyCoeff(index, j, src); |
| 135 | } |
| 136 | |
| 137 | // do the vectorizable part of the assignment |
| 138 | for (int index = alignedStart; index<alignedEnd; index+=PacketSize) |
| 139 | { |
| 140 | if(Dest::Flags&RowMajorBit) |
| 141 | dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src); |
| 142 | else |
| 143 | dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src); |
| 144 | } |
| 145 | |
| 146 | // do the non-vectorizable part of the assignment |
| 147 | for (int index = alignedEnd; index<size; ++index) |
| 148 | { |
| 149 | if(Dest::Flags&RowMajorBit) |
| 150 | dst.copyCoeff(j, index, src); |
| 151 | else |
| 152 | dst.copyCoeff(index, j, src); |
| 153 | } |
| 154 | //dst.col(j).tail(N-j) = src.col(j).tail(N-j); |
| 155 | } |
| 156 | } |
| 157 | |
| 158 | static EIGEN_DONT_INLINE void syr2(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ |
| 159 | // internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1); |
| 160 | for(int j=0; j<N; ++j) |
| 161 | A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j); |
| 162 | } |
| 163 | |
| 164 | static EIGEN_DONT_INLINE void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){ |
| 165 | for(int j=0; j<N; ++j) |
| 166 | A.col(j) += X * Y[j]; |
| 167 | } |
| 168 | |
| 169 | static EIGEN_DONT_INLINE void rot(gene_vector & A, gene_vector & B, real c, real s, int N){ |
| 170 | internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s)); |
| 171 | } |
| 172 | |
| 173 | static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ |
| 174 | X.noalias() = (A.transpose()*B); |
| 175 | } |
| 176 | |
| 177 | static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){ |
| 178 | Y += coef * X; |
| 179 | } |
| 180 | |
| 181 | static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){ |
| 182 | Y = a*X + b*Y; |
| 183 | } |
| 184 | |
| 185 | static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){ |
| 186 | cible = source; |
| 187 | } |
| 188 | |
| 189 | static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int N){ |
| 190 | cible = source; |
| 191 | } |
| 192 | |
| 193 | static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){ |
| 194 | X = L.template triangularView<Lower>().solve(B); |
| 195 | } |
| 196 | |
| 197 | static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ |
| 198 | X = L.template triangularView<Upper>().solve(B); |
| 199 | } |
| 200 | |
| 201 | static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ |
| 202 | X.noalias() = L.template triangularView<Lower>() * B; |
| 203 | } |
| 204 | |
| 205 | static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ |
| 206 | C = X; |
| 207 | internal::llt_inplace<real,Lower>::blocked(C); |
| 208 | //C = X.llt().matrixL(); |
| 209 | // C = X; |
| 210 | // Cholesky<gene_matrix>::computeInPlace(C); |
| 211 | // Cholesky<gene_matrix>::computeInPlaceBlock(C); |
| 212 | } |
| 213 | |
| 214 | static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ |
| 215 | C = X.fullPivLu().matrixLU(); |
| 216 | } |
| 217 | |
| 218 | static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ |
| 219 | Matrix<DenseIndex,1,Dynamic> piv(N); |
| 220 | DenseIndex nb; |
| 221 | C = X; |
| 222 | internal::partial_lu_inplace(C,piv,nb); |
| 223 | // C = X.partialPivLu().matrixLU(); |
| 224 | } |
| 225 | |
| 226 | static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ |
| 227 | typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1); |
| 228 | C = X; |
| 229 | internal::tridiagonalization_inplace(C, aux); |
| 230 | } |
| 231 | |
| 232 | static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ |
| 233 | C = HessenbergDecomposition<gene_matrix>(X).packedMatrix(); |
| 234 | } |
| 235 | |
| 236 | |
| 237 | |
| 238 | }; |
| 239 | |
| 240 | #endif |