aGrUM
3.2.0
a C++ library for (probabilistic) graphical models
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DBRowGeneratorEM.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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* - the GNU Lesser General Public License as published by *
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* - the MIT license (MIT), *
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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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* *
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****************************************************************************/
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#ifndef GUM_LEARNING_DBROW_GENERATOR_EM_H
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#define GUM_LEARNING_DBROW_GENERATOR_EM_H
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#include <vector>
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#include <
agrum/agrum.h
>
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#include <
agrum/base/database/DBRowGeneratorWithBN.h
>
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namespace
gum
{
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namespace
learning
{
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template
< GUM_Numeric GUM_SCALAR =
double
>
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class
DBRowGeneratorEM
:
public
DBRowGeneratorWithBN
< GUM_SCALAR > {
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public
:
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// ##########################################################################
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// ##########################################################################
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DBRowGeneratorEM
(
const
std::vector< DBTranslatedValueType >& column_types,
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const
BayesNet< GUM_SCALAR >& bn,
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const
Bijection< NodeId, std::size_t >
& nodeId2columns
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=
Bijection< NodeId, std::size_t >
());
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DBRowGeneratorEM
(
const
DBRowGeneratorEM< GUM_SCALAR >
& from);
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DBRowGeneratorEM
(
DBRowGeneratorEM< GUM_SCALAR >
&& from)
noexcept
;
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[[nodiscard]]
DBRowGeneratorEM< GUM_SCALAR >
*
clone
() const final;
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~
DBRowGeneratorEM
() override;
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// ##########################################################################
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// ##########################################################################
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DBRowGeneratorEM
< GUM_SCALAR >& operator=(const
DBRowGeneratorEM
< GUM_SCALAR >& from);
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DBRowGeneratorEM
< GUM_SCALAR >& operator=(
DBRowGeneratorEM
< GUM_SCALAR >&& from);
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// ##########################################################################
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// ##########################################################################
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const
DBRow
<
DBTranslatedValue
>&
generate
() final;
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void
setBayesNet
(const
BayesNet
< GUM_SCALAR >& new_bn) final;
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protected:
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std
::
size_t
computeRows_
(const
DBRow
<
DBTranslatedValue
>& row) final;
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#ifndef DOXYGEN_SHOULD_SKIP_THIS
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private
:
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const
DBRow< DBTranslatedValue >
* _input_row_{
nullptr
};
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std::vector< std::size_t > _missing_cols_;
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std::size_t _nb_miss_;
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Tensor< GUM_SCALAR > _joint_proba_;
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Instantiation
* _joint_inst_{
nullptr
};
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DBRow< DBTranslatedValue > _filled_row1_;
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DBRow< DBTranslatedValue > _filled_row2_;
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bool
_use_filled_row1_{
true
};
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double
_original_weight_;
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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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// always include the template implementation
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#include <
agrum/base/database/DBRowGeneratorEM_tpl.h
>
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#endif
/* GUM_LEARNING_DBROW_GENERATOR_EM_H */
DBRowGeneratorEM_tpl.h
A DBRowGenerator class that returns incomplete rows as EM would do.
DBRowGeneratorWithBN.h
Base class for DBRowGenerator classes that use a BN for computing their outputs.
agrum.h
gum::BayesNet
Class representing a Bayesian network.
Definition
BayesNet.h:99
gum::Bijection< NodeId, std::size_t >
gum::Instantiation
Class for assigning/browsing values to tuples of discrete variables.
Definition
instantiation.h:102
gum::learning::DBRowGeneratorEM::clone
DBRowGeneratorEM< GUM_SCALAR > * clone() const final
virtual copy constructor
gum::learning::DBRowGeneratorEM::DBRowGeneratorEM
DBRowGeneratorEM(const std::vector< DBTranslatedValueType > &column_types, const BayesNet< GUM_SCALAR > &bn, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
gum::learning::DBRowGeneratorEM::computeRows_
std::size_t computeRows_(const DBRow< DBTranslatedValue > &row) final
computes the rows it will provide as output
gum::learning::DBRowGeneratorEM::DBRowGeneratorEM
DBRowGeneratorEM(const DBRowGeneratorEM< GUM_SCALAR > &from)
copy constructor
gum::learning::DBRowGeneratorEM::setBayesNet
void setBayesNet(const BayesNet< GUM_SCALAR > &new_bn) final
assign a new Bayes net to the generator
gum::learning::DBRowGeneratorEM::DBRowGeneratorEM
DBRowGeneratorEM(DBRowGeneratorEM< GUM_SCALAR > &&from) noexcept
move constructor
gum::learning::DBRowGeneratorEM::generate
const DBRow< DBTranslatedValue > & generate() final
generates one output DBRow for each DBRow passed to method setInputRow
gum::learning::DBRowGeneratorWithBN< double >::DBRowGeneratorWithBN
DBRowGeneratorWithBN(const std::vector< DBTranslatedValueType > &column_types, const BayesNet< GUM_SCALAR > &bn, const DBRowGeneratorGoal goal, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
gum::learning::DBRow
The class for storing a record in a database.
Definition
DBRow.h:75
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
std
STL namespace.
gum::learning::DBTranslatedValue
The union class for storing the translated values in learning databases.
Definition
DBTranslatedValue.h:88
aGrUM
3.2.0
© PHW&CG&others - 2022
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