KernelMatrix.h
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1 //===========================================================================
2 /*!
3  *
4  *
5  * \brief Kernel Gram matrix
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_KERNELMATRIX_H
40 #define SHARK_LINALG_KERNELMATRIX_H
41 
42 
43 #include <shark/Data/Dataset.h>
44 #include <shark/LinAlg/Base.h>
46 
47 #include <vector>
48 #include <cmath>
49 
50 
51 namespace shark {
52 
53 ///
54 /// \brief Kernel Gram matrix
55 ///
56 /// \par
57 /// The KernelMatrix is the most prominent type of matrix
58 /// for quadratic programming. It provides the Gram matrix
59 /// of a fixed data set with respect to an inner product
60 /// implicitly defined by a kernel function.
61 ///
62 /// \par
63 /// NOTE: The KernelMatrix class stores pointers to the
64 /// data, instead of maintaining a copy of the data. Thus,
65 /// it implicitly assumes that the dataset is not altered
66 /// during the lifetime of the KernelMatrix object. This
67 /// condition is ensured as long as the class is used via
68 /// the various SVM-trainers.
69 ///
70 template <class InputType, class CacheType>
72 {
73 public:
74  typedef CacheType QpFloatType;
75 
76  /// Constructor
77  /// \param kernelfunction kernel function defining the Gram matrix
78  /// \param data data to evaluate the kernel function
80  Data<InputType> const& data)
81  : kernel(kernelfunction)
82  , m_data(data)
83  , m_accessCounter( 0 )
84  {
85  std::size_t elements = m_data.numberOfElements();
86  x.resize(elements);
88  for(std::size_t i = 0; i != elements; ++i,++iter){
89  x[i]=iter.getInnerIterator();
90  }
91  }
92 
93  /// return a single matrix entry
94  QpFloatType operator () (std::size_t i, std::size_t j) const
95  { return entry(i, j); }
96 
97  /// return a single matrix entry
98  QpFloatType entry(std::size_t i, std::size_t j) const
99  {
100  ++m_accessCounter;
101  return (QpFloatType)kernel.eval(*x[i], *x[j]);
102  }
103 
104  /// \brief Computes the i-th row of the kernel matrix.
105  ///
106  ///The entries start,...,end of the i-th row are computed and stored in storage.
107  ///There must be enough room for this operation preallocated.
108  void row(std::size_t i, std::size_t start,std::size_t end, QpFloatType* storage) const{
109  m_accessCounter += end-start;
110 
112  SHARK_PARALLEL_FOR(int j = (int)start; j < (int) end; j++)
113  {
114  storage[j-start] = QpFloatType(kernel.eval(xi, *x[j]));
115  }
116  }
117 
118  /// \brief Computes the kernel-matrix
119  template<class M>
120  void matrix(
121  blas::matrix_expression<M, blas::cpu_tag> & storage
122  ) const{
124  }
125 
126  /// swap two variables
127  void flipColumnsAndRows(std::size_t i, std::size_t j){
128  using std::swap;
129  swap(x[i],x[j]);
130  }
131 
132  /// return the size of the quadratic matrix
133  std::size_t size() const
134  { return x.size(); }
135 
136  /// query the kernel access counter
137  unsigned long long getAccessCount() const
138  { return m_accessCounter; }
139 
140  /// reset the kernel access counter
142  { m_accessCounter = 0; }
143 
144 protected:
145  /// Kernel function defining the kernel Gram matrix
147 
149 
151  /// Array of data pointers for kernel evaluations
152  std::vector<PointerType> x;
153 
154  /// counter for the kernel accesses
155  mutable unsigned long long m_accessCounter;
156 };
157 
158 }
159 #endif