Discus.h
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1 /*!
2  *
3  *
4  * \brief Convex quadratic benchmark function.
5  *
6  *
7  * \author -
8  * \date 2010-2011
9  *
10  *
11  * \par Copyright 1995-2017 Shark Development Team
12  *
13  * <BR><HR>
14  * This file is part of Shark.
15  * <http://shark-ml.org/>
16  *
17  * Shark is free software: you can redistribute it and/or modify
18  * it under the terms of the GNU Lesser General Public License as published
19  * by the Free Software Foundation, either version 3 of the License, or
20  * (at your option) any later version.
21  *
22  * Shark is distributed in the hope that it will be useful,
23  * but WITHOUT ANY WARRANTY; without even the implied warranty of
24  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
25  * GNU Lesser General Public License for more details.
26  *
27  * You should have received a copy of the GNU Lesser General Public License
28  * along with Shark. If not, see <http://www.gnu.org/licenses/>.
29  *
30  */
31 #ifndef SHARK_OBJECTIVEFUNCTIONS_BENCHMARKS_DISCUS_H
32 #define SHARK_OBJECTIVEFUNCTIONS_BENCHMARKS_DISCUS_H
33 
35 #include <shark/Core/Random.h>
36 
37 namespace shark {
38 /**
39  * \brief Convex quadratic benchmark function.
40  */
42 
43  Discus(std::size_t numberOfVariables = 5,double alpha = 1.E-3) : m_alpha(alpha) {
46  m_numberOfVariables = numberOfVariables;
47  }
48 
49  /// \brief From INameable: return the class name.
50  std::string name() const
51  { return "Discus"; }
52 
53  std::size_t numberOfVariables()const{
54  return m_numberOfVariables;
55  }
56 
58  return true;
59  }
60 
61  /// \brief Adjusts the number of variables if the function is scalable.
62  /// \param [in] numberOfVariables The new dimension.
64  m_numberOfVariables = numberOfVariables;
65  }
66 
68  RealVector x(numberOfVariables());
69 
70  for (std::size_t i = 0; i < x.size(); i++) {
71  x(i) = random::uni(*mep_rng, 0,1);
72  }
73  return x;
74  }
75 
76  double eval(SearchPointType const& p) const {
78  double sum = sqr(p(0));
79  for (std::size_t i = 1; i < p.size(); i++)
80  sum += m_alpha * sqr(p(i));
81 
82  return sum;
83  }
84  double evalDerivative(SearchPointType const& p, FirstOrderDerivative & derivative ) const {
85  derivative.resize(p.size());
86  noalias(derivative) = (2 * m_alpha) * p;
87  derivative(0) = 2 * p(0);
88  return eval(p);
89  }
90 
91  double alpha() const {
92  return m_alpha;
93  }
94 
95  void setAlpha(double alpha) {
96  m_alpha = alpha;
97  }
98 
99 private:
100  double m_alpha;
101  std::size_t m_numberOfVariables;
102 };
103 }
104 
105 #endif