/****************************************************************************
 *   This file is part of the aGrUM/pyAgrum library.                        *
 *                                                                          *
 *   Copyright (c) 2005-2026 by                                             *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *                                                                          *
 *   The aGrUM/pyAgrum library is free software; you can redistribute it    *
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 *    - the MIT license (MIT),                                              *
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 *   (see https://agrum.gitlab.io/articles/dual-licenses-lgplv3mit.html)    *
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 *   SPDX-FileCopyrightText: Copyright 2005-2026                            *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *   SPDX-License-Identifier: LGPL-3.0-or-later OR MIT                      *
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 *   Contact  : info_at_agrum_dot_org                                       *
 *   homepage : http://agrum.gitlab.io                                      *
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 *                                                                          *
 ****************************************************************************/

#pragma once


/**
 * @file
 * @brief Implements approximate inference algorithms from Loopy Belief
 * Propagation.
 *
 * @author Paul ALAM & Pierre-Henri WUILLEMIN(_at_LIP6)
 *
 */


#include <agrum/BN/inference/loopySamplingInference.h>

#define DEFAULT_VIRTUAL_LBP_SIZE 5000

namespace gum {


  template < GUM_Numeric GUM_SCALAR, template < typename > class APPROX >
  LoopySamplingInference< GUM_SCALAR, APPROX >::LoopySamplingInference(
      const IBayesNet< GUM_SCALAR >* BN) :
      APPROX< GUM_SCALAR >(BN), virtualLBPSize_(DEFAULT_VIRTUAL_LBP_SIZE) {
    GUM_CONSTRUCTOR(LoopySamplingInference);
  }

  template < GUM_Numeric GUM_SCALAR, template < typename > class APPROX >
  LoopySamplingInference< GUM_SCALAR, APPROX >::~LoopySamplingInference() {
    GUM_DESTRUCTOR(LoopySamplingInference);
  }

  template < GUM_Numeric GUM_SCALAR, template < typename > class APPROX >
  void LoopySamplingInference< GUM_SCALAR, APPROX >::makeInference_() {
    LoopyBeliefPropagation< GUM_SCALAR > lbp(&this->BN());
    for (const auto& x: this->hardEvidence()) {
      lbp.addEvidence(x.first, x.second);
    }
    lbp.makeInference();

    if (!this->isSetEstimator) { this->setEstimatorFromLBP_(&lbp, virtualLBPSize_); }

    this->loopApproxInference_();
  }

  template < GUM_Numeric GUM_SCALAR, template < typename > class APPROX >
  void LoopySamplingInference< GUM_SCALAR, APPROX >::setVirtualLBPSize(GUM_SCALAR vlbpsize) {
    if (vlbpsize > 0) virtualLBPSize_ = vlbpsize;
  }

}   // namespace gum
