1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//=====================================================
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//=====================================================
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This program is free software; you can redistribute it and/or
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// modify it under the terms of the GNU General Public License
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// as published by the Free Software Foundation; either version 2
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// of the License, or (at your option) any later version.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This program is distributed in the hope that it will be useful,
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// but WITHOUT ANY WARRANTY; without even the implied warranty of
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// GNU General Public License for more details.
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// You should have received a copy of the GNU General Public License
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// along with this program; if not, write to the Free Software
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN3_INTERFACE_HH
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN3_INTERFACE_HH
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Eigen>
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <vector>
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "btl.hh"
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing namespace Eigen;
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<class real, int SIZE=Dynamic>
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathclass eigen3_interface
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathpublic :
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  enum {IsFixedSize = (SIZE!=Dynamic)};
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef real real_type;
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef std::vector<real> stl_vector;
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef std::vector<stl_vector> stl_matrix;
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Eigen::Matrix<real,SIZE,SIZE> gene_matrix;
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Eigen::Matrix<real,SIZE,1> gene_vector;
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline std::string name( void )
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    return EIGEN_MAKESTRING(BTL_PREFIX);
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void free_matrix(gene_matrix & A, int N) {}
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static void free_vector(gene_vector & B) {}
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static BTL_DONT_INLINE void matrix_from_stl(gene_matrix & A, stl_matrix & A_stl){
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    A.resize(A_stl[0].size(), A_stl.size());
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int j=0; j<A_stl.size() ; j++){
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (int i=0; i<A_stl[j].size() ; i++){
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        A.coeffRef(i,j) = A_stl[j][i];
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static BTL_DONT_INLINE  void vector_from_stl(gene_vector & B, stl_vector & B_stl){
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    B.resize(B_stl.size(),1);
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<B_stl.size() ; i++){
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      B.coeffRef(i) = B_stl[i];
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static BTL_DONT_INLINE  void vector_to_stl(gene_vector & B, stl_vector & B_stl){
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<B_stl.size() ; i++){
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      B_stl[i] = B.coeff(i);
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static BTL_DONT_INLINE  void matrix_to_stl(gene_matrix & A, stl_matrix & A_stl){
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    int N=A_stl.size();
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int j=0;j<N;j++){
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      A_stl[j].resize(N);
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (int i=0;i<N;i++){
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        A_stl[j][i] = A.coeff(i,j);
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = A*B;
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void transposed_matrix_matrix_product(const gene_matrix & A, const gene_matrix & B, gene_matrix & X, int N){
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = A.transpose()*B.transpose();
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   static inline void ata_product(const gene_matrix & A, gene_matrix & X, int N){
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     X.noalias() = A.transpose()*A;
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//   }
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void aat_product(const gene_matrix & A, gene_matrix & X, int N){
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.template triangularView<Lower>().setZero();
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.template selfadjointView<Lower>().rankUpdate(A);
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void matrix_vector_product(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = A*B;
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void symv(const gene_matrix & A, const gene_vector & B, gene_vector & X, int N){
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = (A.template selfadjointView<Lower>() * B);
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     internal::product_selfadjoint_vector<real,0,LowerTriangularBit,false,false>(N,A.data(),N, B.data(), 1, X.data(), 1);
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename Dest, typename Src> static void triassign(Dest& dst, const Src& src)
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename Dest::Scalar Scalar;
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef typename internal::packet_traits<Scalar>::type Packet;
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const int PacketSize = sizeof(Packet)/sizeof(Scalar);
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    int size = dst.cols();
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int j=0; j<size; j+=1)
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//       const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      Scalar* A0 = dst.data() + j*dst.stride();
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      int starti = j;
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      int alignedEnd = starti;
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      int alignedStart = (starti) + internal::first_aligned(&A0[starti], size-starti);
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      alignedEnd = alignedStart + ((size-alignedStart)/(2*PacketSize))*(PacketSize*2);
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // do the non-vectorizable part of the assignment
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (int index = starti; index<alignedStart ; ++index)
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if(Dest::Flags&RowMajorBit)
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.copyCoeff(j, index, src);
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.copyCoeff(index, j, src);
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // do the vectorizable part of the assignment
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (int index = alignedStart; index<alignedEnd; index+=PacketSize)
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if(Dest::Flags&RowMajorBit)
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.template copyPacket<Src, Aligned, Unaligned>(j, index, src);
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.template copyPacket<Src, Aligned, Unaligned>(index, j, src);
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      // do the non-vectorizable part of the assignment
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for (int index = alignedEnd; index<size; ++index)
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      {
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        if(Dest::Flags&RowMajorBit)
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.copyCoeff(j, index, src);
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        else
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          dst.copyCoeff(index, j, src);
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      }
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      //dst.col(j).tail(N-j) = src.col(j).tail(N-j);
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE void syr2(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    // internal::product_selfadjoint_rank2_update<real,0,LowerTriangularBit>(N,A.data(),N, X.data(), 1, Y.data(), 1, -1);
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int j=0; j<N; ++j)
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      A.col(j).tail(N-j) += X[j] * Y.tail(N-j) + Y[j] * X.tail(N-j);
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE void ger(gene_matrix & A,  gene_vector & X, gene_vector & Y, int N){
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int j=0; j<N; ++j)
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      A.col(j) += X * Y[j];
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE void rot(gene_vector & A,  gene_vector & B, real c, real s, int N){
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::apply_rotation_in_the_plane(A, B, JacobiRotation<real>(c,s));
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void atv_product(gene_matrix & A, gene_vector & B, gene_vector & X, int N){
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = (A.transpose()*B);
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void axpy(real coef, const gene_vector & X, gene_vector & Y, int N){
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Y += coef * X;
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void axpby(real a, const gene_vector & X, real b, gene_vector & Y, int N){
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Y = a*X + b*Y;
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE void copy_matrix(const gene_matrix & source, gene_matrix & cible, int N){
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    cible = source;
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static EIGEN_DONT_INLINE void copy_vector(const gene_vector & source, gene_vector & cible, int N){
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    cible = source;
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void trisolve_lower(const gene_matrix & L, const gene_vector& B, gene_vector& X, int N){
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X = L.template triangularView<Lower>().solve(B);
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void trisolve_lower_matrix(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X = L.template triangularView<Upper>().solve(B);
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void trmm(const gene_matrix & L, const gene_matrix& B, gene_matrix& X, int N){
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    X.noalias() = L.template triangularView<Lower>() * B;
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void cholesky(const gene_matrix & X, gene_matrix & C, int N){
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    C = X;
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::llt_inplace<real,Lower>::blocked(C);
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    //C = X.llt().matrixL();
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     C = X;
210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     Cholesky<gene_matrix>::computeInPlace(C);
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     Cholesky<gene_matrix>::computeInPlaceBlock(C);
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    C = X.fullPivLu().matrixLU();
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void partial_lu_decomp(const gene_matrix & X, gene_matrix & C, int N){
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Matrix<DenseIndex,1,Dynamic> piv(N);
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    DenseIndex nb;
221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    C = X;
222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::partial_lu_inplace(C,piv,nb);
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     C = X.partialPivLu().matrixLU();
224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
225c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
226c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void tridiagonalization(const gene_matrix & X, gene_matrix & C, int N){
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typename Tridiagonalization<gene_matrix>::CoeffVectorType aux(N-1);
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    C = X;
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::tridiagonalization_inplace(C, aux);
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  static inline void hessenberg(const gene_matrix & X, gene_matrix & C, int N){
233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    C = HessenbergDecomposition<gene_matrix>(X).packedMatrix();
234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
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