paramEstimator_tpl.h

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/**
 *
 *   Copyright 2005-2020 Pierre-Henri WUILLEMIN(@LIP6) & Christophe GONZALES(@AMU)
 *   info_at_agrum_dot_org
 *
 *  This library is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Lesser General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This library is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU Lesser General Public License for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with this library.  If not, see <http://www.gnu.org/licenses/>.
 *
 */


/** @file
 * @brief the base class for estimating parameters of CPTs
 *
 * @author Christophe GONZALES(@AMU) and Pierre-Henri WUILLEMIN(@LIP6)
 */

#ifndef DOXYGEN_SHOULD_SKIP_THIS

namespace gum {

  namespace learning {

    /// returns the allocator used by the score
    template < template < typename > class ALLOC >
    INLINE typename ParamEstimator< ALLOC >::allocator_type
       ParamEstimator< ALLOC >::getAllocator() const {
      return counter_.getAllocator();
    }


    /// default constructor
    template < template < typename > class ALLOC >
    ParamEstimator< ALLOC >::ParamEstimator(
       const DBRowGeneratorParser< ALLOC >& parser,
       const Apriori< ALLOC >&              external_apriori,
       const Apriori< ALLOC >&              score_internal_apriori,
       const std::vector< std::pair< std::size_t, std::size_t >,
                          ALLOC< std::pair< std::size_t, std::size_t > > >& ranges,
       const Bijection< NodeId, std::size_t, ALLOC< std::size_t > >&
                                                               nodeId2columns,
       const typename ParamEstimator< ALLOC >::allocator_type& alloc) :
        counter_(parser, ranges, nodeId2columns, alloc) {
      // copy the a prioris
      external_apriori_ = external_apriori.clone(alloc);
      try {
        score_internal_apriori_ = score_internal_apriori.clone();
      } catch (...) {
        ALLOC< Apriori< ALLOC > > allocator(alloc);
        allocator.destroy(external_apriori_);
        allocator.deallocate(external_apriori_, 1);
        throw;
      }

      GUM_CONSTRUCTOR(ParamEstimator);
    }


    /// default constructor
    template < template < typename > class ALLOC >
    ParamEstimator< ALLOC >::ParamEstimator(
       const DBRowGeneratorParser< ALLOC >& parser,
       const Apriori< ALLOC >&              external_apriori,
       const Apriori< ALLOC >&              score_internal_apriori,
       const Bijection< NodeId, std::size_t, ALLOC< std::size_t > >&
                                                               nodeId2columns,
       const typename ParamEstimator< ALLOC >::allocator_type& alloc) :
        counter_(parser, nodeId2columns, alloc) {
      // copy the a prioris
      external_apriori_ = external_apriori.clone(alloc);
      try {
        score_internal_apriori_ = score_internal_apriori.clone();
      } catch (...) {
        ALLOC< Apriori< ALLOC > > allocator(alloc);
        allocator.destroy(external_apriori_);
        allocator.deallocate(external_apriori_, 1);
        throw;
      }

      GUM_CONSTRUCTOR(ParamEstimator);
    }


    /// copy constructor with a given allocator
    template < template < typename > class ALLOC >
    INLINE ParamEstimator< ALLOC >::ParamEstimator(
       const ParamEstimator< ALLOC >&                          from,
       const typename ParamEstimator< ALLOC >::allocator_type& alloc) :
        external_apriori_(from.external_apriori_->clone(alloc)),
        score_internal_apriori_(from.score_internal_apriori_->clone(alloc)),
        counter_(from.counter_, alloc) {
      GUM_CONS_CPY(ParamEstimator);
    }


    /// copy constructor
    template < template < typename > class ALLOC >
    INLINE ParamEstimator< ALLOC >::ParamEstimator(
       const ParamEstimator< ALLOC >& from) :
        ParamEstimator< ALLOC >(from, from.getAllocator()) {}


    /// move constructor with a given allocator
    template < template < typename > class ALLOC >
    INLINE ParamEstimator< ALLOC >::ParamEstimator(
       ParamEstimator< ALLOC >&&                               from,
       const typename ParamEstimator< ALLOC >::allocator_type& alloc) :
        external_apriori_(from.external_apriori_),
        score_internal_apriori_(from.score_internal_apriori_),
        counter_(std::move(from.counter_), alloc) {
      from.external_apriori_       = nullptr;
      from.score_internal_apriori_ = nullptr;
      GUM_CONS_MOV(ParamEstimator);
    }


    /// move constructor
    template < template < typename > class ALLOC >
    INLINE
       ParamEstimator< ALLOC >::ParamEstimator(ParamEstimator< ALLOC >&& from) :
        ParamEstimator< ALLOC >(std::move(from), from.getAllocator()) {}


    /// destructor
    template < template < typename > class ALLOC >
    ParamEstimator< ALLOC >::~ParamEstimator() {
      ALLOC< Apriori< ALLOC > > allocator(this->getAllocator());
      if (external_apriori_ != nullptr) {
        allocator.destroy(external_apriori_);
        allocator.deallocate(external_apriori_, 1);
      }

      if (score_internal_apriori_ != nullptr) {
        allocator.destroy(score_internal_apriori_);
        allocator.deallocate(score_internal_apriori_, 1);
      }

      GUM_DESTRUCTOR(ParamEstimator);
    }


    /// copy operator
    template < template < typename > class ALLOC >
    ParamEstimator< ALLOC >&
       ParamEstimator< ALLOC >::operator=(const ParamEstimator< ALLOC >& from) {
      if (this != &from) {
        ALLOC< Apriori< ALLOC > > allocator(this->getAllocator());
        if (external_apriori_ != nullptr) {
          allocator.destroy(external_apriori_);
          allocator.deallocate(external_apriori_, 1);
          external_apriori_ = nullptr;
        }
        external_apriori_ = from.external_apriori_->clone(this->getAllocator());

        if (score_internal_apriori_ != nullptr) {
          allocator.destroy(score_internal_apriori_);
          allocator.deallocate(score_internal_apriori_, 1);
          external_apriori_ = nullptr;
        }
        score_internal_apriori_
           = from.score_internal_apriori_->clone(this->getAllocator());

        counter_ = from.counter_;
      }
      return *this;
    }


    /// move operator
    template < template < typename > class ALLOC >
    ParamEstimator< ALLOC >&
       ParamEstimator< ALLOC >::operator=(ParamEstimator< ALLOC >&& from) {
      if (this != &from) {
        external_apriori_            = from.external_apriori_;
        score_internal_apriori_      = from.score_internal_apriori_;
        counter_                     = std::move(from.counter_);
        from.external_apriori_       = nullptr;
        from.score_internal_apriori_ = nullptr;
      }
      return *this;
    }


    /// clears all the data structures from memory
    template < template < typename > class ALLOC >
    INLINE void ParamEstimator< ALLOC >::clear() {
      counter_.clear();
    }


    /// changes the max number of threads used to parse the database
    template < template < typename > class ALLOC >
    void ParamEstimator< ALLOC >::setMaxNbThreads(std::size_t nb) const {
      counter_.setMaxNbThreads(nb);
    }


    /// returns the number of threads used to parse the database
    template < template < typename > class ALLOC >
    std::size_t ParamEstimator< ALLOC >::nbThreads() const {
      return counter_.nbThreads();
    }


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


    /// returns the minimum of rows that each thread should process
    template < template < typename > class ALLOC >
    INLINE std::size_t ParamEstimator< ALLOC >::minNbRowsPerThread() const {
      return counter_.minNbRowsPerThread();
    }


    /// sets new ranges to perform the countings used by the score
    /** @param ranges a set of pairs {(X1,Y1),...,(Xn,Yn)} of database's rows
     * indices. The countings are then performed only on the union of the
     * rows [Xi,Yi), i in {1,...,n}. This is useful, e.g, when performing
     * cross validation tasks, in which part of the database should be ignored.
     * An empty set of ranges is equivalent to an interval [X,Y) ranging over
     * the whole database. */
    template < template < typename > class ALLOC >
    template < template < typename > class XALLOC >
    void ParamEstimator< ALLOC >::setRanges(
       const std::vector< std::pair< std::size_t, std::size_t >,
                          XALLOC< std::pair< std::size_t, std::size_t > > >&
          new_ranges) {
      std::vector< std::pair< std::size_t, std::size_t >,
                   ALLOC< std::pair< std::size_t, std::size_t > > >
         old_ranges = ranges();
      counter_.setRanges(new_ranges);
      if (old_ranges != ranges()) clear();
    }


    /// reset the ranges to the one range corresponding to the whole database
    template < template < typename > class ALLOC >
    void ParamEstimator< ALLOC >::clearRanges() {
      std::vector< std::pair< std::size_t, std::size_t >,
                   ALLOC< std::pair< std::size_t, std::size_t > > >
         old_ranges = ranges();
      counter_.clearRanges();
      if (old_ranges != ranges()) clear();
    }


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


    /// returns the CPT's parameters corresponding to a given target node
    template < template < typename > class ALLOC >
    INLINE std::vector< double, ALLOC< double > >
           ParamEstimator< ALLOC >::parameters(const NodeId target_node) {
      return parameters(target_node, empty_nodevect_);
    }


    // check the coherency between the parameters passed to setParameters functions
    template < template < typename > class ALLOC >
    template < typename GUM_SCALAR >
    void ParamEstimator< ALLOC >::checkParameters__(
       const NodeId                                  target_node,
       const std::vector< NodeId, ALLOC< NodeId > >& conditioning_nodes,
       Potential< GUM_SCALAR >&                      pot) {
      // check that the nodes passed in arguments correspond to those of pot
      const Sequence< const DiscreteVariable* >& vars = pot.variablesSequence();
      if (vars.size() == 0) {
        GUM_ERROR(SizeError, "the potential contains no variable");
      }

      const auto& database  = counter_.database();
      const auto& node2cols = counter_.nodeId2Columns();
      if (node2cols.empty()) {
        if (database.domainSize(target_node) != vars[0]->domainSize()) {
          GUM_ERROR(SizeError,
                    "Variable "
                       << vars[0]->name() << "of the potential to be filled "
                       << "has a domain size of " << vars[0]->domainSize()
                       << ", which is different from that of node " << target_node
                       << " which is equal to "
                       << database.domainSize(target_node));
        }
        for (std::size_t i = 1; i < vars.size(); ++i) {
          if (database.domainSize(conditioning_nodes[i - 1])
              != vars[i]->domainSize()) {
            GUM_ERROR(SizeError,
                      "Variable "
                         << vars[i]->name() << "of the potential to be filled "
                         << "has a domain size of " << vars[i]->domainSize()
                         << ", which is different from that of node "
                         << conditioning_nodes[i - 1] << " which is equal to "
                         << database.domainSize(conditioning_nodes[i - 1]));
          }
        }
      } else {
        std::size_t col = node2cols.second(target_node);
        if (database.domainSize(col) != vars[0]->domainSize()) {
          GUM_ERROR(SizeError,
                    "Variable "
                       << vars[0]->name() << "of the potential to be filled "
                       << "has a domain size of " << vars[0]->domainSize()
                       << ", which is different from that of node " << target_node
                       << " which is equal to " << database.domainSize(col));
        }
        for (std::size_t i = 1; i < vars.size(); ++i) {
          col = node2cols.second(conditioning_nodes[i - 1]);
          if (database.domainSize(col) != vars[i]->domainSize()) {
            GUM_ERROR(SizeError,
                      "Variable "
                         << vars[i]->name() << "of the potential to be filled "
                         << "has a domain size of " << vars[i]->domainSize()
                         << ", which is different from that of node "
                         << conditioning_nodes[i - 1] << " which is equal to "
                         << database.domainSize(col));
          }
        }
      }
    }


    /// sets the CPT's parameters corresponding to a given nodeset
    template < template < typename > class ALLOC >
    template < typename GUM_SCALAR >
    INLINE typename std::enable_if< !std::is_same< GUM_SCALAR, double >::value,
                                    void >::type
       ParamEstimator< ALLOC >::setParameters__(
          const NodeId                                  target_node,
          const std::vector< NodeId, ALLOC< NodeId > >& conditioning_nodes,
          Potential< GUM_SCALAR >&                      pot) {
      checkParameters__(target_node, conditioning_nodes, pot);

      const std::vector< double, ALLOC< double > > params(
         parameters(target_node, conditioning_nodes));

      // transform the vector of double into a vector of GUM_SCALAR
      const std::size_t                              size = params.size();
      std::vector< GUM_SCALAR, ALLOC< GUM_SCALAR > > xparams(size);
      for (std::size_t i = std::size_t(0); i < size; ++i)
        xparams[i] = GUM_SCALAR(params[i]);

      pot.fillWith(xparams);
    }


    /// sets the CPT's parameters corresponding to a given nodeset
    template < template < typename > class ALLOC >
    template < typename GUM_SCALAR >
    INLINE typename std::enable_if< std::is_same< GUM_SCALAR, double >::value,
                                    void >::type
       ParamEstimator< ALLOC >::setParameters__(
          const NodeId                                  target_node,
          const std::vector< NodeId, ALLOC< NodeId > >& conditioning_nodes,
          Potential< GUM_SCALAR >&                      pot) {
      checkParameters__(target_node, conditioning_nodes, pot);

      const std::vector< double, ALLOC< double > > params(
         parameters(target_node, conditioning_nodes));
      pot.fillWith(params);
    }


    /// sets the CPT's parameters corresponding to a given nodeset
    template < template < typename > class ALLOC >
    template < typename GUM_SCALAR >
    INLINE void ParamEstimator< ALLOC >::setParameters(
       const NodeId                                  target_node,
       const std::vector< NodeId, ALLOC< NodeId > >& conditioning_nodes,
       Potential< GUM_SCALAR >&                      pot) {
      setParameters__(target_node, conditioning_nodes, pot);
    }


    /// returns the mapping from ids to column positions in the database
    template < template < typename > class ALLOC >
    INLINE const Bijection< NodeId, std::size_t, ALLOC< std::size_t > >&
                 ParamEstimator< ALLOC >::nodeId2Columns() const {
      return counter_.nodeId2Columns();
    }


    /// returns the database on which we perform the counts
    template < template < typename > class ALLOC >
    INLINE const DatabaseTable< ALLOC >&
                 ParamEstimator< ALLOC >::database() const {
      return counter_.database();
    }


    /// assign a new Bayes net to all the counter's generators depending on a BN
    template < template < typename > class ALLOC >
    template < typename GUM_SCALAR >
    INLINE void
       ParamEstimator< ALLOC >::setBayesNet(const BayesNet< GUM_SCALAR >& new_bn) {
      counter_.setBayesNet(new_bn);
    }


  } /* namespace learning */

} /* namespace gum */

#endif /* DOXYGEN_SHOULD_SKIP_THIS */