aGrUM 3.1.1
a C++ library for (probabilistic) graphical models
scoreLog2Likelihood_inl.h
Go to the documentation of this file.
1/****************************************************************************
2 * This file is part of the aGrUM/pyAgrum library. *
3 * *
4 * Copyright (c) 2005-2026 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 2005-2026 *
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#pragma once
42
43
49
50#include <agrum/BN/learning/scores/scoreLog2Likelihood.h> // to ease IDE parser
51#ifndef DOXYGEN_SHOULD_SKIP_THIS
52
53# include <sstream>
54
56
57namespace gum {
58
59 namespace learning {
60
63 const DBRowGeneratorParser& parser,
64 const Prior& prior,
65 const std::vector< std::pair< std::size_t, std::size_t > >& ranges,
66 const Bijection< NodeId, std::size_t >& nodeId2columns) :
67 Score(parser, prior, ranges, nodeId2columns),
68 _internal_prior_(parser.database(), nodeId2columns) {
69 GUM_CONSTRUCTOR(ScoreLog2Likelihood);
70 }
71
73 INLINE ScoreLog2Likelihood::ScoreLog2Likelihood(
74 const DBRowGeneratorParser& parser,
75 const Prior& prior,
76 const Bijection< NodeId, std::size_t >& nodeId2columns) :
77 Score(parser, prior, nodeId2columns), _internal_prior_(parser.database(), nodeId2columns) {
78 GUM_CONSTRUCTOR(ScoreLog2Likelihood);
79 }
80
82 INLINE ScoreLog2Likelihood::ScoreLog2Likelihood(const ScoreLog2Likelihood& from) :
83 Score(from), _internal_prior_(from._internal_prior_) {
84 GUM_CONS_CPY(ScoreLog2Likelihood);
85 }
86
88 INLINE ScoreLog2Likelihood::ScoreLog2Likelihood(ScoreLog2Likelihood&& from) :
89 Score(std::move(from)), _internal_prior_(std::move(from._internal_prior_)) {
90 GUM_CONS_MOV(ScoreLog2Likelihood);
91 }
92
94 INLINE ScoreLog2Likelihood* ScoreLog2Likelihood::clone() const {
95 return new ScoreLog2Likelihood(*this);
96 }
97
99 INLINE ScoreLog2Likelihood::~ScoreLog2Likelihood() { GUM_DESTRUCTOR(ScoreLog2Likelihood); }
100
102 INLINE std::string ScoreLog2Likelihood::isPriorCompatible(const Prior& prior) {
103 return isPriorCompatible(prior.getType(), prior.weight());
104 }
105
107 INLINE std::string ScoreLog2Likelihood::isPriorCompatible() const {
108 return isPriorCompatible(*(this->prior_));
109 }
110
112 INLINE const Prior& ScoreLog2Likelihood::internalPrior() const { return _internal_prior_; }
113
115 INLINE double ScoreLog2Likelihood::score(const IdCondSet& idset) { return score_(idset); }
116
117
118 } /* namespace learning */
119
120} /* namespace gum */
121
122#endif /* DOXYGEN_SHOULD_SKIP_THIS */
the class used to read a row in the database and to transform it into a set of DBRow instances that c...
the base class for all a priori
Definition prior.h:81
ScoreLog2Likelihood(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
The base class for all the scores used for learning (BIC, BDeu, etc).
Definition score.h:68
include the inlined functions if necessary
Definition CSVParser.h:55
gum is the global namespace for all aGrUM entities
Definition agrum.h:46
STL namespace.
the class for computing Log2-likelihood scores