113 lines
3.4 KiB
C++
113 lines
3.4 KiB
C++
/**
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* @file BayesNet
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* @brief Bayes network
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* @author Frank Dellaert
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*/
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// \callgraph
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#pragma once
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#include <list>
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#include <boost/shared_ptr.hpp>
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#include <boost/serialization/list.hpp>
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#include <boost/serialization/shared_ptr.hpp>
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#include <gtsam/base/Testable.h>
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#include <gtsam/inference/Key.h>
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namespace gtsam {
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class Ordering;
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/**
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* Bayes network
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* This is the base class for SymbolicBayesNet, DiscreteBayesNet, and GaussianBayesNet
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* corresponding to what is used for the "Conditional" template argument:
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* a SymbolicConditional, ConditionalProbabilityTable, or a GaussianConditional
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*/
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template<class Conditional>
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class BayesNet: public Testable<BayesNet<Conditional> > {
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public:
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/** We store shared pointers to Conditional densities */
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typedef typename boost::shared_ptr<Conditional> sharedConditional;
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typedef typename std::list<sharedConditional> Conditionals;
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typedef typename Conditionals::const_iterator const_iterator;
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typedef typename Conditionals::const_reverse_iterator const_reverse_iterator;
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protected:
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/**
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* Conditional densities are stored in reverse topological sort order (i.e., leaves first,
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* parents last), which corresponds to the elimination ordering if so obtained,
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* and is consistent with the column (block) ordering of an upper triangular matrix.
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*/
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Conditionals conditionals_;
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public:
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/** print */
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void print(const std::string& s = "") const;
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/** check equality */
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bool equals(const BayesNet& other, double tol = 1e-9) const;
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/** push_back: use reverse topological sort (i.e. parents last / elimination order) */
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inline void push_back(const sharedConditional& conditional) {
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conditionals_.push_back(conditional);
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}
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/** push_front: use topological sort (i.e. parents first / reverse elimination order) */
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inline void push_front(const sharedConditional& conditional) {
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conditionals_.push_front(conditional);
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}
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// push_back an entire Bayes net */
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void push_back(const BayesNet<Conditional> bn);
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// push_front an entire Bayes net */
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void push_front(const BayesNet<Conditional> bn);
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/**
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* pop_front: remove node at the bottom, used in marginalization
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* For example P(ABC)=P(A|BC)P(B|C)P(C) becomes P(BC)=P(B|C)P(C)
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*/
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inline void pop_front() {conditionals_.pop_front();}
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/** size is the number of nodes */
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inline size_t size() const {
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return conditionals_.size();
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}
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/** return keys in reverse topological sort order, i.e., elimination order */
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Ordering ordering() const;
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/** SLOW O(n) random access to Conditional by key */
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sharedConditional operator[](const Symbol& key) const;
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/** return last node in ordering */
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inline sharedConditional back() { return conditionals_.back(); }
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/** return iterators. FD: breaks encapsulation? */
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inline const_iterator const begin() const {return conditionals_.begin();}
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inline const_iterator const end() const {return conditionals_.end();}
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inline const_reverse_iterator const rbegin() const {return conditionals_.rbegin();}
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inline const_reverse_iterator const rend() const {return conditionals_.rend();}
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/** saves the bayes to a text file in GraphViz format */
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void saveGraph(const std::string& s) const;
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private:
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/** Serialization function */
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friend class boost::serialization::access;
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template<class Archive>
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void serialize(Archive & ar, const unsigned int version) {
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ar & BOOST_SERIALIZATION_NVP(conditionals_);
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}
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}; // BayesNet
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} /// namespace gtsam
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