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224 lines
7.1 KiB
C++
224 lines
7.1 KiB
C++
//=====================================================
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// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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//=====================================================
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//
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// This program is free software; you can redistribute it and/or
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// modify it under the terms of the GNU General Public License
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// as published by the Free Software Foundation; either version 2
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// of the License, or (at your option) any later version.
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//
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// This program is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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// You should have received a copy of the GNU General Public License
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// along with this program; if not, write to the Free Software
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// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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//
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#ifndef EIGEN2_INTERFACE_HH
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#define EIGEN2_INTERFACE_HH
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// #include <cblas.h>
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#include <Eigen/Array>
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#include <Eigen/Cholesky>
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#include <Eigen/LU>
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#include <Eigen/QR>
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#include <vector>
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#include "btl.hh"
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using namespace Eigen;
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template<class real, int SIZE=Dynamic>
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class eigen2_interface
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{
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public :
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enum {IsFixedSize = (SIZE!=Dynamic)};
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typedef real real_type;
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typedef std::vector<real> stl_vector;
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typedef std::vector<stl_vector> stl_matrix;
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typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
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typedef Eigen::Matrix<real,SIZE,1> gene_vector;
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static inline std::string name( void )
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{
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return EIGEN_MAKESTRING(BTL_PREFIX);
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}
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static void free_matrix(gene_matrix & A, int N) {}
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static void free_vector(gene_vector & B) {}
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static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
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A.resize(A_stl[0].size(), A_stl.size());
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for (int j=0; j<A_stl.size() ; j++){
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for (int i=0; i<A_stl[j].size() ; i++){
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A.coeffRef(i,j) = A_stl[j][i];
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}
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}
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}
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static BTL_DONT_INLINE void vector_from_stl(gene_vector & B, stl_vector & B_stl){
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B.resize(B_stl.size(),1);
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for (int i=0; i<B_stl.size() ; i++){
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B.coeffRef(i) = B_stl[i];
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}
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}
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static BTL_DONT_INLINE void vector_to_stl(gene_vector & B, stl_vector & B_stl){
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for (int i=0; i<B_stl.size() ; i++){
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B_stl[i] = B.coeff(i);
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}
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}
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static BTL_DONT_INLINE void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
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int N=A_stl.size();
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for (int j=0;j<N;j++){
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A_stl[j].resize(N);
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for (int i=0;i<N;i++){
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A_stl[j][i] = A.coeff(i,j);
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}
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}
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}
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static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
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X = (A*B).lazy();
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}
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static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
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X = (A.transpose()*B.transpose()).lazy();
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}
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static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
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X = (A.transpose()*A).lazy();
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}
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static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
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X = (A*A.transpose()).lazy();
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}
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static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
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X = (A*B)/*.lazy()*/;
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}
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static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
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//X = (A.template marked<SelfAdjoint|LowerTriangular>() * B)/*.lazy()*/;
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ei_product_selfadjoint_vector<real,0,LowerTriangularBit>(N,A.data(),N, B.data(), X.data());
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}
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template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src)
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{
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typedef typename Dest::Scalar Scalar;
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typedef typename ei_packet_traits<Scalar>::type Packet;
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const int PacketSize = sizeof(Packet)/sizeof(Scalar);
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int size = dst.cols();
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for(int j=0; j<size; j+=1)
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{
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// const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
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Scalar* A0 = dst.data() + j*dst.stride();
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int starti = j;
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int alignedEnd = starti;
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int alignedStart = (starti) + ei_alignmentOffset(&A0[starti], size-starti);
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alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2);
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// do the non-vectorizable part of the assignment
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for (int index = starti; index<alignedStart ; ++index)
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{
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if(Dest::Flags&RowMajorBit)
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dst.copyCoeff(j, index, src);
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else
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dst.copyCoeff(index, j, src);
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}
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// do the vectorizable part of the assignment
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for (int index = alignedStart; index<alignedEnd; index+=PacketSize)
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{
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if(Dest::Flags&RowMajorBit)
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dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src);
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else
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dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src);
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}
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// do the non-vectorizable part of the assignment
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for (int index = alignedEnd; index<size; ++index)
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{
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if(Dest::Flags&RowMajorBit)
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dst.copyCoeff(j, index, src);
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else
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dst.copyCoeff(index, j, src);
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}
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//dst.col(j).end(N-j) = src.col(j).end(N-j);
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}
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}
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static EIGEN_DONT_INLINE void syr2(gene_matrix & A, gene_vector & X, gene_vector & Y, int N){
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// ei_product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1);
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for(int j=0; j<N; ++j)
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A.col(j).end(N-j) += X[j] * Y.end(N-j) + Y[j] * X.end(N-j);
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}
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static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
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X = (A.transpose()*B)/*.lazy()*/;
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}
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static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
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Y += coef * X;
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}
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static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
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asm("#begin axpby");
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Y = a*X + b*Y;
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asm("#end axpby");
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}
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static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
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cible = source;
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}
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static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int N){
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cible = source;
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}
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static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
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X = L.template marked<LowerTriangular>().solveTriangular(B);
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}
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static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
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X = L.template marked<LowerTriangular>().solveTriangular(B);
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}
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static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
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C = X.llt().matrixL();
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// C = X;
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// Cholesky<gene_matrix>::computeInPlace(C);
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// Cholesky<gene_matrix>::computeInPlaceBlock(C);
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}
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static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
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C = X.lu().matrixLU();
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// C = X.inverse();
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}
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static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
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typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1);
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C = X;
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Tridiagonalization<gene_matrix>::_compute(C, aux);
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// C = Tridiagonalization<gene_matrix>(X).packedMatrix();
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}
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static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
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C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
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}
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};
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#endif
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