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 < typename GUM_SCALAR >
  class MarkovRandomField: public IMarkovRandomField< GUM_SCALAR > {
    public:
    static MarkovRandomField< GUM_SCALAR > fastPrototype(const std::string& dotlike,
                                                         Size               domainSize);
    static MarkovRandomField< GUM_SCALAR > fastPrototype(const std::string& dotlike,
                                                         const std::string& domain = "[2]");

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

    MarkovRandomField();

    explicit MarkovRandomField(std::string name);

    virtual ~MarkovRandomField();

    MarkovRandomField(const MarkovRandomField< GUM_SCALAR >& source);

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

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

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

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

    virtual const NodeSet& smallestFactorFromNode(NodeId node) 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& fast_description, unsigned int default_nbrmod = 2);

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

    void clear();

    void erase(NodeId varId);

    void erase(const std::string& 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 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_();
    VariableNodeMap _varMap_;

    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;
  };

  template < typename 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 */