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| #ifndef EIGEN2_INTERFACE_HH |
| #define EIGEN2_INTERFACE_HH |
| |
| #include <Eigen/Core> |
| #include <Eigen/Cholesky> |
| #include <Eigen/LU> |
| #include <Eigen/QR> |
| #include <vector> |
| #include "btl.hh" |
|
|
| using namespace Eigen; |
|
|
| template<class real, int SIZE=Dynamic> |
| class eigen2_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 ) |
| { |
| #if defined(EIGEN_VECTORIZE_SSE) |
| if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2"; |
| #elif defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX) |
| if (SIZE==Dynamic) return "eigen2"; else return "tiny_eigen2"; |
| #else |
| if (SIZE==Dynamic) return "eigen2_novec"; else return "tiny_eigen2_novec"; |
| #endif |
| } |
|
|
| 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 = (A*B).lazy(); |
| } |
|
|
| static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){ |
| X = (A.transpose()*B.transpose()).lazy(); |
| } |
|
|
| static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){ |
| X = (A.transpose()*A).lazy(); |
| } |
|
|
| static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){ |
| X = (A*A.transpose()).lazy(); |
| } |
|
|
| static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){ |
| X = (A*B); |
| } |
|
|
| static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){ |
| X = (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 inline void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){ |
| cible = source; |
| } |
|
|
| static 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 marked<LowerTriangular>().solveTriangular(B); |
| } |
|
|
| static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){ |
| X = L.template marked<LowerTriangular>().solveTriangular(B); |
| } |
|
|
| static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){ |
| C = X.llt().matrixL(); |
| |
| |
| |
| } |
|
|
| static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){ |
| C = X.lu().matrixLU(); |
| |
| } |
|
|
| static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){ |
| C = Tridiagonalization<gene_matrix>(X).packedMatrix(); |
| } |
|
|
| static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){ |
| C = HessenbergDecomposition<gene_matrix>(X).packedMatrix(); |
| } |
|
|
|
|
|
|
| }; |
|
|
| #endif |
|
|