[136] | 1 | //=====================================================
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| 2 | // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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| 3 | //=====================================================
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| 4 | //
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| 5 | // This program is free software; you can redistribute it and/or
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| 6 | // modify it under the terms of the GNU General Public License
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| 7 | // as published by the Free Software Foundation; either version 2
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| 8 | // of the License, or (at your option) any later version.
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| 9 | //
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| 10 | // This program is distributed in the hope that it will be useful,
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| 11 | // but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 12 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 13 | // GNU General Public License for more details.
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| 14 | // You should have received a copy of the GNU General Public License
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| 15 | // along with this program; if not, write to the Free Software
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| 16 | // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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| 17 | //
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| 18 | #ifndef EIGEN2_INTERFACE_HH
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| 19 | #define EIGEN2_INTERFACE_HH
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| 20 | // #include <cblas.h>
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| 21 | #include <Eigen/Core>
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| 22 | #include <Eigen/Cholesky>
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| 23 | #include <Eigen/LU>
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| 24 | #include <Eigen/QR>
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| 25 | #include <vector>
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| 26 | #include "btl.hh"
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| 27 |
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| 28 | using namespace Eigen;
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| 29 |
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| 30 | template<class real, int SIZE=Dynamic>
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| 31 | class eigen2_interface
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| 32 | {
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| 33 |
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| 34 | public :
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| 35 |
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| 36 | enum {IsFixedSize = (SIZE!=Dynamic)};
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| 37 |
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| 38 | typedef real real_type;
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| 39 |
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| 40 | typedef std::vector<real> stl_vector;
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| 41 | typedef std::vector<stl_vector> stl_matrix;
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| 42 |
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| 43 | typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
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| 44 | typedef Eigen::Matrix<real,SIZE,1> gene_vector;
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| 45 |
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| 46 | static inline std::string name( void )
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| 47 | {
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| 48 | #if defined(EIGEN_VECTORIZE_SSE)
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| 49 | if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
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| 50 | #elif defined(EIGEN_VECTORIZE_ALTIVEC)
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| 51 | if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2";
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| 52 | #else
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| 53 | if (SIZE==Dynamic) return "eigen2_novec"; else return "tiny_eigen2_novec";
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| 54 | #endif
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| 55 | }
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| 56 |
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| 57 | static void free_matrix(gene_matrix & A, int N) {}
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| 58 |
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| 59 | static void free_vector(gene_vector & B) {}
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| 60 |
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| 61 | static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
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| 62 | A.resize(A_stl[0].size(), A_stl.size());
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| 63 |
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| 64 | for (int j=0; j<A_stl.size() ; j++){
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| 65 | for (int i=0; i<A_stl[j].size() ; i++){
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| 66 | A.coeffRef(i,j) = A_stl[j][i];
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| 67 | }
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| 68 | }
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| 69 | }
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| 70 |
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| 71 | static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
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| 72 | B.resize(B_stl.size(),1);
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| 73 |
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| 74 | for (int i=0; i<B_stl.size() ; i++){
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| 75 | B.coeffRef(i) = B_stl[i];
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| 76 | }
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| 77 | }
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| 78 |
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| 79 | static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
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| 80 | for (int i=0; i<B_stl.size() ; i++){
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| 81 | B_stl[i] = B.coeff(i);
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| 82 | }
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| 83 | }
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| 84 |
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| 85 | static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
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| 86 | int N=A_stl.size();
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| 87 |
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| 88 | for (int j=0;j<N;j++){
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| 89 | A_stl[j].resize(N);
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| 90 | for (int i=0;i<N;i++){
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| 91 | A_stl[j][i] = A.coeff(i,j);
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| 92 | }
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| 93 | }
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| 94 | }
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| 95 |
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| 96 | static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
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| 97 | X = (A*B).lazy();
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| 98 | }
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| 99 |
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| 100 | static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
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| 101 | X = (A.transpose()*B.transpose()).lazy();
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| 102 | }
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| 103 |
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| 104 | static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
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| 105 | X = (A.transpose()*A).lazy();
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| 106 | }
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| 107 |
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| 108 | static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
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| 109 | X = (A*A.transpose()).lazy();
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| 110 | }
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| 111 |
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| 112 | static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
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| 113 | X = (A*B)/*.lazy()*/;
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| 114 | }
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| 115 |
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| 116 | static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
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| 117 | X = (A.transpose()*B)/*.lazy()*/;
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| 118 | }
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| 119 |
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| 120 | static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
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| 121 | Y += coef * X;
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| 122 | }
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| 123 |
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| 124 | static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
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| 125 | Y = a*X + b*Y;
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| 126 | }
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| 127 |
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| 128 | static inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
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| 129 | cible = source;
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| 130 | }
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| 131 |
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| 132 | static inline void copy_vector(const gene_vector & source, gene_vector & cible, int N){
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| 133 | cible = source;
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| 134 | }
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| 135 |
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| 136 | static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
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| 137 | X = L.template marked<LowerTriangular>().solveTriangular(B);
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| 138 | }
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| 139 |
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| 140 | static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
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| 141 | X = L.template marked<LowerTriangular>().solveTriangular(B);
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| 142 | }
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| 143 |
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| 144 | static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
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| 145 | C = X.llt().matrixL();
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| 146 | // C = X;
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| 147 | // Cholesky<gene_matrix>::computeInPlace(C);
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| 148 | // Cholesky<gene_matrix>::computeInPlaceBlock(C);
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| 149 | }
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| 150 |
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| 151 | static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
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| 152 | C = X.lu().matrixLU();
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| 153 | // C = X.inverse();
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| 154 | }
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| 155 |
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| 156 | static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
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| 157 | C = Tridiagonalization<gene_matrix>(X).packedMatrix();
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| 158 | }
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| 159 |
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| 160 | static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
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| 161 | C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
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| 162 | }
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| 163 |
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| 164 |
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| 165 |
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| 166 | };
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| 167 |
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| 168 | #endif
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