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00018 #ifndef EIGEN3_INTERFACE_HH
00019 #define EIGEN3_INTERFACE_HH
00020
00021 #include <Eigen/Eigen>
00022 #include <vector>
00023 #include "btl.hh"
00024
00025 using namespace Eigen;
00026
00027 template<class real, int SIZE=Dynamic>
00028 class eigen3_interface
00029 {
00030
00031 public :
00032
00033 enum {IsFixedSize = (SIZE!=Dynamic)};
00034
00035 typedef real real_type;
00036
00037 typedef std::vector<real> stl_vector;
00038 typedef std::vector<stl_vector> stl_matrix;
00039
00040 typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
00041 typedef Eigen::Matrix<real,SIZE,1> gene_vector;
00042
00043 static inline std::string name( void )
00044 {
00045 return EIGEN_MAKESTRING(BTL_PREFIX);
00046 }
00047
00048 static void free_matrix(gene_matrix & A, int N) {}
00049
00050 static void free_vector(gene_vector & B) {}
00051
00052 static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
00053 A.resize(A_stl[0].size(), A_stl.size());
00054
00055 for (int j=0; j<A_stl.size() ; j++){
00056 for (int i=0; i<A_stl[j].size() ; i++){
00057 A.coeffRef(i,j) = A_stl[j][i];
00058 }
00059 }
00060 }
00061
00062 static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
00063 B.resize(B_stl.size(),1);
00064
00065 for (int i=0; i<B_stl.size() ; i++){
00066 B.coeffRef(i) = B_stl[i];
00067 }
00068 }
00069
00070 static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
00071 for (int i=0; i<B_stl.size() ; i++){
00072 B_stl[i] = B.coeff(i);
00073 }
00074 }
00075
00076 static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
00077 int N=A_stl.size();
00078
00079 for (int j=0;j<N;j++){
00080 A_stl[j].resize(N);
00081 for (int i=0;i<N;i++){
00082 A_stl[j][i] = A.coeff(i,j);
00083 }
00084 }
00085 }
00086
00087 static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
00088 X.noalias() = A*B;
00089 }
00090
00091 static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
00092 X.noalias() = A.transpose()*B.transpose();
00093 }
00094
00095 static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
00096 X.noalias() = A.transpose()*A;
00097 }
00098
00099 static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
00100 X.noalias() = A*A.transpose();
00101 }
00102
00103 static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
00104 X.noalias() = A*B;
00105 }
00106
00107 static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
00108 X.noalias() = (A.template selfadjointView<Lower>() * B);
00109
00110 }
00111
00112 template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src)
00113 {
00114 typedef typename Dest::Scalar Scalar;
00115 typedef typename internal::packet_traits<Scalar>::type Packet;
00116 const int PacketSize = sizeof(Packet)/sizeof(Scalar);
00117 int size = dst.cols();
00118 for(int j=0; j<size; j+=1)
00119 {
00120
00121 Scalar* A0 = dst.data() + j*dst.stride();
00122 int starti = j;
00123 int alignedEnd = starti;
00124 int alignedStart = (starti) + internal::first_aligned(&A0[starti], size-starti);
00125 alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2);
00126
00127
00128 for (int index = starti; index<alignedStart ; ++index)
00129 {
00130 if(Dest::Flags&RowMajorBit)
00131 dst.copyCoeff(j, index, src);
00132 else
00133 dst.copyCoeff(index, j, src);
00134 }
00135
00136
00137 for (int index = alignedStart; index<alignedEnd; index+=PacketSize)
00138 {
00139 if(Dest::Flags&RowMajorBit)
00140 dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src);
00141 else
00142 dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src);
00143 }
00144
00145
00146 for (int index = alignedEnd; index<size; ++index)
00147 {
00148 if(Dest::Flags&RowMajorBit)
00149 dst.copyCoeff(j, index, src);
00150 else
00151 dst.copyCoeff(index, j, src);
00152 }
00153
00154 }
00155 }
00156
00157 static EIGEN_DONT_INLINE void syr2(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
00158
00159 for(int j=0; j<N; ++j)
00160 A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j);
00161 }
00162
00163 static EIGEN_DONT_INLINE void ger(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
00164 for(int j=0; j<N; ++j)
00165 A.col(j) += X * Y[j];
00166 }
00167
00168 static EIGEN_DONT_INLINE void rot(gene_vector & A, gene_vector & B, real c, real s, int N){
00169 internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s));
00170 }
00171
00172 static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
00173 X.noalias() = (A.transpose()*B);
00174 }
00175
00176 static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
00177 Y += coef * X;
00178 }
00179
00180 static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
00181 Y = a*X + b*Y;
00182 }
00183
00184 static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
00185 cible = source;
00186 }
00187
00188 static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int N){
00189 cible = source;
00190 }
00191
00192 static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
00193 X = L.template triangularView<Lower>().solve(B);
00194 }
00195
00196 static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
00197 X = L.template triangularView<Lower>().solve(B);
00198 }
00199
00200 static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
00201 X = L.template triangularView<Lower>() * B;
00202 }
00203
00204 static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
00205 C = X;
00206 internal::llt_inplace<Lower>::blocked(C);
00207
00208
00209
00210
00211 }
00212
00213 static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
00214 C = X.fullPivLu().matrixLU();
00215 }
00216
00217 static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
00218 Matrix<DenseIndex,1,Dynamic> piv(N);
00219 DenseIndex nb;
00220 C = X;
00221 internal::partial_lu_inplace(C,piv,nb);
00222
00223 }
00224
00225 static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
00226 typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1);
00227 C = X;
00228 internal::tridiagonalization_inplace(C, aux);
00229 }
00230
00231 static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
00232 C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
00233 }
00234
00235
00236
00237 };
00238
00239 #endif