BlockMatrix2x2.h
Go to the documentation of this file.
1 //===========================================================================
2 /*!
3  *
4  *
5  * \brief Kernel matrix for SVM regression.
6  *
7  *
8  * \par
9  *
10  *
11  *
12  * \author T. Glasmachers
13  * \date 2007-2012
14  *
15  *
16  * \par Copyright 1995-2017 Shark Development Team
17  *
18  * <BR><HR>
19  * This file is part of Shark.
20  * <http://shark-ml.org/>
21  *
22  * Shark is free software: you can redistribute it and/or modify
23  * it under the terms of the GNU Lesser General Public License as published
24  * by the Free Software Foundation, either version 3 of the License, or
25  * (at your option) any later version.
26  *
27  * Shark is distributed in the hope that it will be useful,
28  * but WITHOUT ANY WARRANTY; without even the implied warranty of
29  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
30  * GNU Lesser General Public License for more details.
31  *
32  * You should have received a copy of the GNU Lesser General Public License
33  * along with Shark. If not, see <http://www.gnu.org/licenses/>.
34  *
35  */
36 //===========================================================================
37 
38 
39 #ifndef SHARK_LINALG_BLOCKMATRIX2X2_H
40 #define SHARK_LINALG_BLOCKMATRIX2X2_H
41 
42 #include <shark/Data/Dataset.h>
43 #include <shark/LinAlg/Base.h>
44 
45 #include <vector>
46 #include <cmath>
47 
48 
49 namespace shark {
50 
51 
52 ///
53 /// \brief SVM regression matrix
54 ///
55 /// \par
56 /// The BlockMatrix2x2 class is a \f$ 2n \times 2n \f$ block matrix of the form<br>
57 /// &nbsp;&nbsp;&nbsp; \f$ \left( \begin{array}{lr} M & M \\ M & M \end{array} \right) \f$ <br>
58 /// where M is an \f$ n \times n \f$ matrix.
59 /// This matrix form is needed in SVM regression problems.
60 ///
61 template <class Matrix>
63 {
64 public:
65  typedef typename Matrix::QpFloatType QpFloatType;
66 
67  /// Constructor.
68  /// \param base underlying matrix M, see class description of BlockMatrix2x2.
69  BlockMatrix2x2(Matrix* base)
70  {
71  m_base = base;
72 
73  m_mapping.resize(size());
74 
75  std::size_t ic = m_base->size();
76  for (std::size_t i = 0; i < ic; i++)
77  {
78  m_mapping[i] = i;
79  m_mapping[i + ic] = i;
80  }
81  }
82 
83 
84  /// return a single matrix entry
85  QpFloatType operator () (std::size_t i, std::size_t j) const
86  { return entry(i, j); }
87 
88  /// return a single matrix entry
89  QpFloatType entry(std::size_t i, std::size_t j) const
90  {
91  return m_base->entry(m_mapping[i], m_mapping[j]);
92  }
93 
94  /// \brief Computes the i-th row of the kernel matrix.
95  ///
96  ///The entries start,...,end of the i-th row are computed and stored in storage.
97  ///There must be enough room for this operation preallocated.
98  void row(std::size_t i, std::size_t start,std::size_t end, QpFloatType* storage) const{
99  for(std::size_t j = start; j < end; j++){
100  storage[j-start] = m_base->entry(m_mapping[i], m_mapping[j]);
101  }
102  }
103 
104  /// \brief Computes the kernel-matrix
105  template<class M>
106  void matrix(
107  blas::matrix_expression<M, blas::cpu_tag> & storage
108  ) const{
109  for(std::size_t i = 0; i != size(); ++i){
110  for(std::size_t j = 0; j != size(); ++j){
111  storage()(i,j) = entry(i,j);
112  }
113  }
114  }
115 
116  /// swap two variables
117  void flipColumnsAndRows(std::size_t i, std::size_t j)
118  {
119  std::swap(m_mapping[i], m_mapping[j]);
120  }
121 
122  /// return the size of the quadratic matrix
123  std::size_t size() const
124  { return 2 * m_base->size(); }
125 
126 protected:
127  /// underlying KernelMatrix object
128  Matrix* m_base;
129 
130  /// coordinate permutation
131  std::vector<std::size_t> m_mapping;
132 };
133 
134 }
135 #endif