aGrUM
3.2.0
a C++ library for (probabilistic) graphical models
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importanceSampling.h
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/****************************************************************************
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* This file is part of the aGrUM/pyAgrum library. *
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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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* The aGrUM/pyAgrum library is free software; you can redistribute it *
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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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****************************************************************************/
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#ifndef GUM_IMPORTANCE_INFERENCE_H
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#define GUM_IMPORTANCE_INFERENCE_H
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#include <
agrum/BN/inference/tools/samplingInference.h
>
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namespace
gum
{
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template
< GUM_Numeric GUM_SCALAR >
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class
ImportanceSampling
:
public
SamplingInference
< GUM_SCALAR > {
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public
:
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explicit
ImportanceSampling
(
const
IBayesNet< GUM_SCALAR >
* bn);
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~ImportanceSampling
()
override
;
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protected
:
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Instantiation
burnIn_
()
override
;
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Instantiation
draw_
(GUM_SCALAR* w,
Instantiation
prev)
override
;
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void
unsharpenBN_
(
BayesNetFragment< GUM_SCALAR >
* bn,
float
epsilon
);
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void
onContextualize_
(
BayesNetFragment< GUM_SCALAR >
* bn)
override
;
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};
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#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
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extern
template
class
GUM_PUBLIC_BN
ImportanceSampling< double >
;
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#endif
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}
// namespace gum
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#include <
agrum/BN/inference/importanceSampling_tpl.h
>
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#endif
gum::ApproximationScheme::epsilon
double epsilon() const override
Returns the value of epsilon.
Definition
approximationScheme_inl.h:72
gum::BayesNetFragment
Portion of a BN identified by the list of nodes and a BayesNet.
Definition
BayesNetFragment.h:90
gum::IBayesNet
Class representing the minimal interface for Bayesian network with no numerical data.
Definition
IBayesNet.h:75
gum::ImportanceSampling::onContextualize_
void onContextualize_(BayesNetFragment< GUM_SCALAR > *bn) override
fired when Bayesian network is contextualized
Definition
importanceSampling_tpl.h:120
gum::ImportanceSampling::burnIn_
Instantiation burnIn_() override
draws a defined number of samples without updating the estimators
Definition
importanceSampling_tpl.h:71
gum::ImportanceSampling::unsharpenBN_
void unsharpenBN_(BayesNetFragment< GUM_SCALAR > *bn, float epsilon)
modifies the cpts of a BN in order to tend to uniform distributions
Definition
importanceSampling_tpl.h:110
gum::ImportanceSampling::ImportanceSampling
ImportanceSampling(const IBayesNet< GUM_SCALAR > *bn)
Default constructor.
Definition
importanceSampling_tpl.h:58
gum::ImportanceSampling::draw_
Instantiation draw_(GUM_SCALAR *w, Instantiation prev) override
draws a sample according to Importance sampling
Definition
importanceSampling_tpl.h:77
gum::Instantiation
Class for assigning/browsing values to tuples of discrete variables.
Definition
instantiation.h:102
gum::SamplingInference::SamplingInference
SamplingInference(const IBayesNet< GUM_SCALAR > *bn)
default constructor
Definition
samplingInference_tpl.h:68
importanceSampling_tpl.h
Implementation of Importance Sampling for inference in Bayesian networks.
gum
gum is the global namespace for all aGrUM entities
Definition
agrum.h:46
gum::ImportanceSampling< double >
template class GUM_PUBLIC_BN ImportanceSampling< double >
Definition
importanceSampling.cpp:46
samplingInference.h
This file contains general methods for simulation-oriented approximate inference.
aGrUM
3.2.0
© PHW&CG&others - 2022
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