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