MarkovNet.h

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#ifndef GUM_MARKOV_NET_H
#define GUM_MARKOV_NET_H

#include <utility>

#include <agrum/agrum.h>

#include <agrum/tools/core/hashTable.h>

#include <agrum/MN/IMarkovNet.h>
#include <agrum/tools/multidim/potential.h>

namespace gum {

  template < typename GUM_SCALAR >
  class MarkovNet: public IMarkovNet< GUM_SCALAR > {
    public:
    static MarkovNet< GUM_SCALAR > fastPrototype(const std::string& dotlike,
                                                 Size domainSize = 2);

    // ===========================================================================
    // ===========================================================================

    MarkovNet();

    explicit MarkovNet(std::string name);

    virtual ~MarkovNet() final;

    MarkovNet(const MarkovNet< GUM_SCALAR >& source);

    // ===========================================================================
    // ===========================================================================

    MarkovNet< GUM_SCALAR >& operator=(const MarkovNet< GUM_SCALAR >& source);

    // ===========================================================================
    // ===========================================================================

    virtual const Potential< GUM_SCALAR >&
       factor(const NodeSet& varIds) const final;

    virtual const FactorTable<GUM_SCALAR>& factors() const final;

    virtual const VariableNodeMap& variableNodeMap() const final;

    NodeId add(const DiscreteVariable& var);

    NodeId add(const std::string& name, unsigned int nbrmod);

    NodeId add(const DiscreteVariable& var, NodeId id);

    NodeId add(const DiscreteVariable&               var,
               MultiDimImplementation< GUM_SCALAR >* aContent,
               NodeId                                id);

    void clear();

    void erase(NodeId varId);

    void erase(const std::string& name) { erase(idFromName(name)); };

    void erase(const DiscreteVariable& var);

    const DiscreteVariable& variable(NodeId id) const final;

    const DiscreteVariable& variable(const std::string& name) const {
      return variable(idFromName(name));
    };

    void changeVariableName(NodeId id, const std::string& new_name);

    void changeVariableName(const std::string& name, const std::string& new_name) {
      changeVariableName(idFromName(name), new_name);
    }

    void changeVariableLabel(NodeId             id,
                             const std::string& old_label,
                             const std::string& new_label);

    void changeVariableLabel(const std::string& name,
                             const std::string& old_label,
                             const std::string& new_label) {
      changeVariableLabel(idFromName(name), old_label, new_label);
    }

    NodeId nodeId(const DiscreteVariable& var) const final;

    NodeId idFromName(const std::string& name) const final;

    const DiscreteVariable& variableFromName(const std::string& name) const final;

    // ===========================================================================
    // ===========================================================================

    const Potential< GUM_SCALAR >& addFactor(const NodeSet& vars);
    const Potential< GUM_SCALAR >&
       addFactor(const std::vector< std::string >& varnames);
    const Potential< GUM_SCALAR >&
       addFactor(const Potential<GUM_SCALAR>& factor);

    void eraseFactor(const NodeSet& vars);


    void generateFactors() const;

    void generateFactor(const NodeSet& vars) const;

    void changeFactor(const NodeSet& vars, Potential< GUM_SCALAR >* newPot);

    private:
    void __clearFactors();

    void __copyFactors(const MarkovNet< GUM_SCALAR >& source);

    VariableNodeMap __varMap;

    FactorTable<GUM_SCALAR> __factors;

    // HashTable< const NodeSet,Potential< GUM_SCALAR >* > __factorMap;

    void _unsafeChangePotential(const NodeSet&           vars,
                                Potential< GUM_SCALAR >* newPot);

    public:
    using IMarkovNet< GUM_SCALAR >::graph;
    using IMarkovNet< GUM_SCALAR >::size;
    using IMarkovNet< GUM_SCALAR >::nodes;
    using IMarkovNet< GUM_SCALAR >::log10DomainSize;
  };

  template < typename GUM_SCALAR >
  std::ostream& operator<<(std::ostream&                  output,
                           const MarkovNet< GUM_SCALAR >& bn);


#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
  extern template class MarkovNet< double >;
#endif

} /* namespace gum */

#include <agrum/MN/MarkovNet_tpl.h>

#endif /* GUM_MARKOV_NET_H */