BayesOpt
criteria_distance.hpp
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1 
2 /*
3 -------------------------------------------------------------------------
4  This file is part of BayesOpt, an efficient C++ library for
5  Bayesian optimization.
6 
7  Copyright (C) 2011-2015 Ruben Martinez-Cantin <rmcantin@unizar.es>
8 
9  BayesOpt is free software: you can redistribute it and/or modify it
10  under the terms of the GNU Affero General Public License as published by
11  the Free Software Foundation, either version 3 of the License, or
12  (at your option) any later version.
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14  BayesOpt is distributed in the hope that it will be useful, but
15  WITHOUT ANY WARRANTY; without even the implied warranty of
16  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17  GNU Affero General Public License for more details.
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19  You should have received a copy of the GNU Affero General Public License
20  along with BayesOpt. If not, see <http://www.gnu.org/licenses/>.
21 ------------------------------------------------------------------------
22 */
23 
24 #ifndef _CRITERIA_DISTANCE_HPP_
25 #define _CRITERIA_DISTANCE_HPP_
26 
27 #include "criteria_functors.hpp"
28 
29 namespace bayesopt
30 {
31 
34 
40  class InputDistance: public Criteria
41  {
42  public:
43  void init(NonParametricProcess* proc)
44  {
45  mProc = proc;
46  mW = 1;
47  };
48  virtual ~InputDistance(){};
49  void setParameters(const vectord &params)
50  { mW = params(0); };
51  size_t nParameters() {return 1;};
52 
53  double operator() (const vectord &x)
54  {
55  const vectord x2 = mProc->getData()->getLastSampleX();
56  return mW*norm_2(x-x2);
57  };
58  std::string name() {return "cDistance";};
59  private:
60  double mW;
61  };
62 
63 
65 
66 } //namespace bayesopt
67 
68 
69 #endif
Distance in input space.
Namespace of the library interface.
Definition: using.dox:1
Abstract class to implement Bayesian regressors.
Abstract interface for criteria functors.
Abstract and factory modules for criteria.