MarkovRandomField.h

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#ifndef GUM_MARKOV_RANDOM_FIELD_H
#define GUM_MARKOV_RANDOM_FIELD_H
 
#include <utility>
 
#include <agrum/agrum.h>
 
#include <agrum/BN/BayesNet.h>
#include <agrum/MRF/IMarkovRandomField.h>
 
namespace gum {

  template < GUM_Numeric GUM_SCALAR >
  class MarkovRandomField: public IMarkovRandomField< GUM_SCALAR > {
    public:
    static MarkovRandomField< GUM_SCALAR > fastPrototype(std::string_view dotlike, Size domainSize);
    static MarkovRandomField< GUM_SCALAR > fastPrototype(std::string_view dotlike,
                                                         std::string_view domain = "[2]");

    static MarkovRandomField< GUM_SCALAR > fromBN(const BayesNet< GUM_SCALAR >& bn);
 
    // ===========================================================================
    // ===========================================================================

    MarkovRandomField();

    explicit MarkovRandomField(std::string_view name);

    ~MarkovRandomField() override;

    MarkovRandomField(const MarkovRandomField< GUM_SCALAR >& source);

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

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

    MarkovRandomField< GUM_SCALAR >& operator=(MarkovRandomField< GUM_SCALAR >&& source) noexcept;

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

    const Tensor< GUM_SCALAR >& factor(const NodeSet& varIds) const final;
 
    virtual const Tensor< GUM_SCALAR >&
        factor(const std::vector< std::string >& varnames) const final;

    const NodeSet& smallestFactorFromNode(NodeId node) const final;

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

    NodeId add(const DiscreteVariable& var);

    NodeId add(std::string_view fast_description, unsigned int default_nbrmod = 2);

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

    void clear();

    void erase(NodeId varId);

    void erase(std::string_view name);

    void erase(const DiscreteVariable& var);


    const DiscreteVariable& variable(std::string_view name) const;

    void changeVariableName(NodeId id, std::string_view new_name);

    void changeVariableName(std::string_view name, std::string_view new_name);

    void changeVariableLabel(NodeId id, std::string_view old_label, std::string_view new_label);

    void changeVariableLabel(std::string_view name,
                             std::string_view old_label,
                             std::string_view new_label);

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

    const Tensor< GUM_SCALAR >& addFactor(const std::vector< std::string >& varnames);

    const Tensor< GUM_SCALAR >& addFactor(const NodeSet& vars);

    const Tensor< GUM_SCALAR >& addFactor(const Tensor< GUM_SCALAR >& factor);

    void eraseFactor(const NodeSet& vars);
 
    void eraseFactor(const std::vector< std::string >& varnames);
 

    void generateFactors() const;

    void generateFactor(const NodeSet& vars) const;

    void beginTopologyTransformation();
 
    void endTopologyTransformation();
 
    private:
    bool _topologyTransformationInProgress_;

    void _clearFactors_();

    void _copyFactors_(const MarkovRandomField< GUM_SCALAR >& source);

    void _rebuildGraph_();

    FactorTable< GUM_SCALAR > _factors_;
 
    Tensor< GUM_SCALAR >& _addFactor_(const std::vector< NodeId >& ordered_nodes);
 
    void _eraseFactor_(const NodeSet& vars);
 
    public:
    using IMarkovRandomField< GUM_SCALAR >::graph;
    using IMarkovRandomField< GUM_SCALAR >::size;
    using IMarkovRandomField< GUM_SCALAR >::nodes;
    using IMarkovRandomField< GUM_SCALAR >::log10DomainSize;
    using DiscreteGraphicalModel::idFromName;
    using DiscreteGraphicalModel::variableNodeMap;
    using DiscreteGraphicalModel::variable;
    using DiscreteGraphicalModel::nodeId;
    using DiscreteGraphicalModel::variableFromName;
  };

  template < GUM_Numeric GUM_SCALAR >
  std::ostream& operator<<(std::ostream& output, const MarkovRandomField< GUM_SCALAR >& bn);
 
 
#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
 
  extern template class MarkovRandomField< double >;
 
#endif
 
} /* namespace gum */
 
#include <agrum/MRF/MarkovRandomField_tpl.h>
 
#endif /* GUM_MARKOV_RANDOM_FIELD_H */