aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
scoreBD.h
Go to the documentation of this file.
1/****************************************************************************
2 * This file is part of the aGrUM/pyAgrum library. *
3 * *
4 * Copyright (c) 2005-2025 by *
5 * - Pierre-Henri WUILLEMIN(_at_LIP6) *
6 * - Christophe GONZALES(_at_AMU) *
7 * *
8 * The aGrUM/pyAgrum library is free software; you can redistribute it *
9 * and/or modify it under the terms of either : *
10 * *
11 * - the GNU Lesser General Public License as published by *
12 * the Free Software Foundation, either version 3 of the License, *
13 * or (at your option) any later version, *
14 * - the MIT license (MIT), *
15 * - or both in dual license, as here. *
16 * *
17 * (see https://agrum.gitlab.io/articles/dual-licenses-lgplv3mit.html) *
18 * *
19 * This aGrUM/pyAgrum library is distributed in the hope that it will be *
20 * useful, but WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, *
21 * INCLUDING BUT NOT LIMITED TO THE WARRANTIES MERCHANTABILITY or FITNESS *
22 * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE *
23 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER *
24 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, *
25 * ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR *
26 * OTHER DEALINGS IN THE SOFTWARE. *
27 * *
28 * See LICENCES for more details. *
29 * *
30 * SPDX-FileCopyrightText: Copyright 2005-2025 *
31 * - Pierre-Henri WUILLEMIN(_at_LIP6) *
32 * - Christophe GONZALES(_at_AMU) *
33 * SPDX-License-Identifier: LGPL-3.0-or-later OR MIT *
34 * *
35 * Contact : info_at_agrum_dot_org *
36 * homepage : http://agrum.gitlab.io *
37 * gitlab : https://gitlab.com/agrumery/agrum *
38 * *
39 ****************************************************************************/
40
41
50
51#ifndef GUM_LEARNING_SCORE_BD_H
52#define GUM_LEARNING_SCORE_BD_H
53
54#include <string>
55
56#include <agrum/agrum.h>
57
60
62
63namespace gum {
64
65 namespace learning {
66
84 class ScoreBD: public Score {
85 public:
86 // ##########################################################################
88 // ##########################################################################
90
92
111 const Prior& prior,
112 const std::vector< std::pair< std::size_t, std::size_t > >& ranges,
113 const Bijection< NodeId, std::size_t >& nodeId2columns
115
116
118
131 const Prior& prior,
132 const Bijection< NodeId, std::size_t >& nodeId2columns
134
136 ScoreBD(const ScoreBD& from);
137
140
142 virtual ScoreBD* clone() const;
143
145 virtual ~ScoreBD();
146
148
149
150 // ##########################################################################
152 // ##########################################################################
153
155
157 ScoreBD& operator=(const ScoreBD& from);
158
161
163
164
165 // ##########################################################################
167 // ##########################################################################
169
171
180 virtual std::string isPriorCompatible() const final;
181
183
193 virtual const Prior& internalPrior() const final;
194
196
197
199
201 static std::string isPriorCompatible(PriorType prior_type, double weight = 1.0f);
202
204
205 static std::string isPriorCompatible(const Prior& prior);
206
207
208 protected:
210
213 virtual double score_(const IdCondSet& idset) final;
214
215
216#ifndef DOXYGEN_SHOULD_SKIP_THIS
217
218 private:
220 NoPrior _internal_prior_;
221
223 GammaLog2 _gammalog2_;
224
225#endif /* DOXYGEN_SHOULD_SKIP_THIS */
226 };
227
228 } /* namespace learning */
229
230} /* namespace gum */
231
232// include the inlined functions if necessary
233#ifndef GUM_NO_INLINE
235#endif /* GUM_NO_INLINE */
236
237#endif /* GUM_LEARNING_SCORE_BD_H */
The class for computing Log2 (Gamma(x)).
Definition gammaLog2.h:68
the class used to read a row in the database and to transform it into a set of DBRow instances that c...
A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set.
Definition idCondSet.h:214
the no a priorclass: corresponds to 0 weight-sample
Definition noPrior.h:65
the base class for all a priori
Definition prior.h:83
ScoreBD(const DBRowGeneratorParser &parser, const Prior &prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
ScoreBD & operator=(ScoreBD &&from)
move operator
virtual double score_(const IdCondSet &idset) final
returns the score for a given IdCondSet
virtual std::string isPriorCompatible() const final
indicates whether the prior is compatible (meaningful) with the score
virtual ScoreBD * clone() const
virtual copy constructor
virtual ~ScoreBD()
destructor
ScoreBD(const DBRowGeneratorParser &parser, const Prior &prior, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
virtual const Prior & internalPrior() const final
returns the internal prior of the score
ScoreBD(ScoreBD &&from)
move constructor
ScoreBD & operator=(const ScoreBD &from)
copy operator
ScoreBD(const ScoreBD &from)
copy constructor
const std::vector< std::pair< std::size_t, std::size_t > > & ranges() const
returns the current ranges
Score(const DBRowGeneratorParser &parser, const Prior &external_prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
The class for computing Log2 (Gamma(x)).
include the inlined functions if necessary
Definition CSVParser.h:54
gum is the global namespace for all aGrUM entities
Definition agrum.h:46
STL namespace.
the no a priorclass: corresponds to 0 weight-sample
the class for computing BD scores
the base class for all the scores used for learning (BIC, BDeu, etc)