aGrUM
3.2.0
a C++ library for (probabilistic) graphical models
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scoringCache.h
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/****************************************************************************
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* This file is part of the aGrUM/pyAgrum library. *
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* *
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* Copyright (c) 2005-2026 by *
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* - Pierre-Henri WUILLEMIN(_at_LIP6) *
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* - Christophe GONZALES(_at_AMU) *
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* *
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* The aGrUM/pyAgrum library is free software; you can redistribute it *
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* and/or modify it under the terms of either : *
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* *
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* - the GNU Lesser General Public License as published by *
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* the Free Software Foundation, either version 3 of the License, *
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* or (at your option) any later version, *
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* - the MIT license (MIT), *
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* - or both in dual license, as here. *
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* *
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* (see https://agrum.gitlab.io/articles/dual-licenses-lgplv3mit.html) *
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* *
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* This aGrUM/pyAgrum library is distributed in the hope that it will be *
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* useful, but WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, *
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* INCLUDING BUT NOT LIMITED TO THE WARRANTIES MERCHANTABILITY or FITNESS *
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* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE *
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* OTHER DEALINGS IN THE SOFTWARE. *
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* *
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* See LICENCES for more details. *
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* *
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* SPDX-FileCopyrightText: Copyright 2005-2026 *
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* - Pierre-Henri WUILLEMIN(_at_LIP6) *
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* - Christophe GONZALES(_at_AMU) *
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* SPDX-License-Identifier: LGPL-3.0-or-later OR MIT *
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* *
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* Contact : info_at_agrum_dot_org *
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* homepage : http://agrum.gitlab.io *
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* gitlab : https://gitlab.com/agrumery/agrum *
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* *
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****************************************************************************/
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#ifndef GUM_LEARNING_SCORING_CACHE_H
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#define GUM_LEARNING_SCORING_CACHE_H
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#include <utility>
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#include <
agrum/agrum.h
>
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#include <
agrum/base/stattests/idCondSet.h
>
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namespace
gum
{
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namespace
learning
{
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class
GUM_SHARED_PUBLIC
ScoringCache
{
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public
:
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// ##########################################################################
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// ##########################################################################
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ScoringCache
();
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ScoringCache
(
const
ScoringCache
& from);
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ScoringCache
(
ScoringCache
&& from);
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[[nodiscard]]
virtual
ScoringCache
*
clone
()
const
;
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virtual
~ScoringCache
();
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// ##########################################################################
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// ##########################################################################
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ScoringCache
&
operator=
(
const
ScoringCache
& from);
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ScoringCache
&
operator=
(
ScoringCache
&& from);
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// ##########################################################################
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// ##########################################################################
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void
insert
(
const
IdCondSet
& idset,
double
score
);
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void
insert
(
IdCondSet
&& idset,
double
score
);
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void
erase
(
const
IdCondSet
& idset);
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bool
exists
(
const
IdCondSet
& idset)
const
;
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double
score
(
const
IdCondSet
& idset)
const
;
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optional_ref< double >
tryGet
(
const
IdCondSet
& idset);
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void
clear
();
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std::size_t
size
()
const
;
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#ifndef DOXYGEN_SHOULD_SKIP_THIS
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private
:
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HashTable< IdCondSet, double >
_scores_;
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#endif
/* DOXYGEN_SHOULD_SKIP_THIS */
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};
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}
/* namespace learning */
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}
/* namespace gum */
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// include the inlined functions if necessary
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#ifndef GUM_NO_INLINE
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# include <
agrum/base/stattests/scoringCache_inl.h
>
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#endif
/* GUM_NO_INLINE */
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#endif
/* GUM_LEARNING_SCORING_CACHE_H */
agrum.h
gum::HashTable
The class for generic Hash Tables.
Definition
hashTable.h:640
gum::learning::IdCondSet
A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set.
Definition
idCondSet.h:214
gum::learning::ScoringCache::operator=
ScoringCache & operator=(ScoringCache &&from)
move operator
gum::learning::ScoringCache::insert
void insert(const IdCondSet &idset, double score)
insert a new score into the cache
gum::learning::ScoringCache::operator=
ScoringCache & operator=(const ScoringCache &from)
copy operator
gum::learning::ScoringCache::erase
void erase(const IdCondSet &idset)
removes a score (if it exists)
gum::learning::ScoringCache::exists
bool exists(const IdCondSet &idset) const
indicates whether a given score exists
gum::learning::ScoringCache::insert
void insert(IdCondSet &&idset, double score)
insert a new score into the cache
gum::learning::ScoringCache::clear
void clear()
removes all the stored scores
gum::learning::ScoringCache::~ScoringCache
virtual ~ScoringCache()
destructor
gum::learning::ScoringCache::score
double score(const IdCondSet &idset) const
returns a given score
gum::learning::ScoringCache::ScoringCache
ScoringCache()
default constructor
gum::learning::ScoringCache::size
std::size_t size() const
returns the number of scores saved in the cache
gum::learning::ScoringCache::tryGet
optional_ref< double > tryGet(const IdCondSet &idset)
returns a pointer to a given score, or nullptr if not cached
gum::learning::ScoringCache::ScoringCache
ScoringCache(const ScoringCache &from)
copy constructor
gum::learning::ScoringCache::clone
virtual ScoringCache * clone() const
virtual copy constructor
gum::learning::ScoringCache::ScoringCache
ScoringCache(ScoringCache &&from)
move constructor
gum::optional_ref
A lightweight wrapper around a pointer providing an optional-like API for references (not supported b...
Definition
optional_ref.h:62
idCondSet.h
A class used by learning caches to represent uniquely sets of variables.
gum::learning
include the inlined functions if necessary
Definition
CSVParser.h:55
gum
gum is the global namespace for all aGrUM entities
Definition
agrum.h:46
scoringCache_inl.h
a cache for caching scores and independence tests results
aGrUM
3.2.0
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