/****************************************************************************
 *   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    *
 *   and/or modify it under the terms of either :                           *
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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),                                              *
 *    - or both in dual license, as here.                                   *
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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                                      *
 *   gitlab   : https://gitlab.com/agrumery/agrum                           *
 *                                                                          *
 ****************************************************************************/

#pragma once


/** @file
 * @brief the base class for all the scores used for learning (BIC, BDeu, etc)
 *
 * @author Christophe GONZALES(_at_AMU) and Pierre-Henri WUILLEMIN(_at_LIP6)
 */
#include <agrum/BN/learning/scores/score.h>   // to ease IDE parser
#ifndef DOXYGEN_SHOULD_SKIP_THIS

namespace gum {

  namespace learning {

    /// default constructor
    INLINE Score::Score(const DBRowGeneratorParser&                                 parser,
                        const Prior&                                                prior,
                        const std::vector< std::pair< std::size_t, std::size_t > >& ranges,
                        const Bijection< NodeId, std::size_t >& nodeId2columns) :
        prior_(prior.clone()), counter_(parser, ranges, nodeId2columns) {
      GUM_CONSTRUCTOR(Score);
    }

    /// default constructor
    INLINE Score::Score(const DBRowGeneratorParser&             parser,
                        const Prior&                            prior,
                        const Bijection< NodeId, std::size_t >& nodeId2columns) :
        prior_(prior.clone()), counter_(parser, nodeId2columns) {
      GUM_CONSTRUCTOR(Score);
    }

    /// copy constructor
    INLINE Score::Score(const Score& from) :
        prior_(from.prior_->clone()), counter_(from.counter_), cache_(from.cache_),
        use_cache_(from.use_cache_) {
      GUM_CONS_CPY(Score);
    }

    /// move constructor
    INLINE Score::Score(Score&& from) :
        prior_(from.prior_), counter_(std::move(from.counter_)), cache_(std::move(from.cache_)),
        use_cache_(from.use_cache_) {
      from.prior_ = nullptr;
      GUM_CONS_MOV(Score);
    }

    /// destructor
    INLINE Score::~Score() {
      if (prior_ != nullptr) delete prior_;
      GUM_DESTRUCTOR(Score);
    }

    /// changes the max number of threads used to parse the database
    INLINE void Score::setNumberOfThreads(Size nb) { counter_.setNumberOfThreads(nb); }

    /// returns the current max number of threads of the scheduler
    INLINE Size Score::getNumberOfThreads() const { return counter_.getNumberOfThreads(); }

    /// indicates whether the user set herself the number of threads
    INLINE bool Score::isGumNumberOfThreadsOverriden() const {
      return counter_.isGumNumberOfThreadsOverriden();
    }

    /** @brief changes the number min of rows a thread should process in a
     * multithreading context */
    INLINE void Score::setMinNbRowsPerThread(const std::size_t nb) const {
      counter_.setMinNbRowsPerThread(nb);
    }

    /// returns the minimum of rows that each thread should process
    INLINE std::size_t Score::minNbRowsPerThread() const { return counter_.minNbRowsPerThread(); }

    /// returns the current ranges
    INLINE const std::vector< std::pair< std::size_t, std::size_t > >& Score::ranges() const {
      return counter_.ranges();
    }

    /// returns the score of a single node
    INLINE double Score::score(const NodeId var) {
      IdCondSet idset(var, empty_ids_, true);
      if (use_cache_) {
        if (auto ptr_score = cache_.tryGet(idset)) { return *ptr_score; }
        double the_score = score_(idset);
        cache_.insert(std::move(idset), the_score);
        return the_score;
      } else {
        return score_(std::move(idset));
      }
    }

    /// returns the score of a single node given some other nodes
    /** @param var1 the variable on the left side of the conditioning bar
     * @param rhs_ids the set of variables on the right side of the
     * conditioning bar */
    INLINE double Score::score(const NodeId var, const std::vector< NodeId >& rhs_ids) {
      IdCondSet idset(var, rhs_ids, false);
      if (use_cache_) {
        if (auto ptr_score = cache_.tryGet(idset)) { return *ptr_score; }
        const double the_score = score_(idset);
        cache_.insert(std::move(idset), the_score);
        return the_score;
      } else {
        return score_(idset);
      }
    }

    /// clears all the data structures from memory
    INLINE void Score::clear() {
      counter_.clear();
      cache_.clear();
    }

    /// clears the current cache (clear nodesets as well)
    INLINE void Score::clearCache() { cache_.clear(); }

    /// turn on/off the use of a cache of the previously computed score
    INLINE void Score::useCache(const bool on_off) { use_cache_ = on_off; }

    /// indicates whether the score uses a cache
    INLINE bool Score::isUsingCache() const { return use_cache_; }

    /// return the mapping between the columns of the database and the node ids
    INLINE const Bijection< NodeId, std::size_t >& Score::nodeId2Columns() const {
      return counter_.nodeId2Columns();
    }

    /// return the database used by the score
    INLINE const DatabaseTable& Score::database() const { return counter_.database(); }

  } /* namespace learning */

} /* namespace gum */

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
