/****************************************************************************
 *   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 GNU Lesser General Public License as published by               *
 *      the Free Software Foundation, either version 3 of the License,      *
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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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 *   See LICENCES for more details.                                         *
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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                      *
 *                                                                          *
 *   Contact  : info_at_agrum_dot_org                                       *
 *   homepage : http://agrum.gitlab.io                                      *
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 *                                                                          *
 ****************************************************************************/

#pragma once


/** @file
 * @brief the smooth a priori: adds a weight w to all the counts
 *
 * @author Christophe GONZALES(_at_AMU) and Pierre-Henri WUILLEMIN(_at_LIP6)
 */
#include <agrum/BN/learning/priors/smoothingPrior.h>   // to ease IDE parser
#ifndef DOXYGEN_SHOULD_SKIP_THIS

namespace gum {

  namespace learning {

    /// default constructor
    INLINE
    SmoothingPrior::SmoothingPrior(const DatabaseTable&                    database,
                                   const Bijection< NodeId, std::size_t >& nodeId2columns) :
        Prior(database, nodeId2columns) {
      GUM_CONSTRUCTOR(SmoothingPrior);
    }

    /// copy constructor
    INLINE SmoothingPrior::SmoothingPrior(const SmoothingPrior& from) : Prior(from) {
      GUM_CONS_CPY(SmoothingPrior);
    }

    /// move constructor
    INLINE SmoothingPrior::SmoothingPrior(SmoothingPrior&& from) noexcept : Prior(std::move(from)) {
      GUM_CONS_MOV(SmoothingPrior);
    }

    /// virtual copy constructor
    INLINE SmoothingPrior* SmoothingPrior::clone() const { return new SmoothingPrior(*this); }

    /// destructor
    INLINE SmoothingPrior::~SmoothingPrior() { GUM_DESTRUCTOR(SmoothingPrior); }

    /// copy operator
    INLINE SmoothingPrior& SmoothingPrior::operator=(const SmoothingPrior& from) = default;

    /// move operator
    INLINE SmoothingPrior& SmoothingPrior::operator=(SmoothingPrior&& from) {
      Prior::operator=(std::move(from));
      return *this;
    }

    /// returns the type of the prior
    INLINE PriorType SmoothingPrior::getType() const { return PriorType::SmoothingPriorType; }

    /// indicates whether the prior is potentially informative
    INLINE bool SmoothingPrior::isInformative() const { return this->weight_ != 0.0; }

    /// returns the prior vector all the variables in the idset
    INLINE void SmoothingPrior::addJointPseudoCount(const IdCondSet&       idset,
                                                    std::vector< double >& counts) {
      // if the idset is empty or the weight is zero, the prior is also empty
      if (idset.empty() || (this->weight_ == 0.0)) return;

      // otherwise, add the weight to all the cells in the counting vector
      for (auto& count: counts)
        count += this->weight_;
    }

  } /* namespace learning */

} /* namespace gum */

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
