added comments
Kai Ni
parent
03ca6ccc93
commit
612aca96c6
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@ -96,12 +96,34 @@ namespace gtsam {
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bool equals(const Cliques& other, double tol = 1e-9) const;
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};
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/** clique statistics */
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struct CliqueStats {
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double avgConditionalSize;
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std::size_t maxConditionalSize;
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double avgSeparatorSize;
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std::size_t maxSeparatorSize;
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};
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/** store all the sizes */
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struct CliqueData {
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std::vector<std::size_t> conditionalSizes;
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std::vector<std::size_t> separatorSizes;
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CliqueStats getStats() const;
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};
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private:
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/** Map from keys to Clique */
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typedef SymbolMap<sharedClique> Nodes;
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Nodes nodes_;
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/** private helper method for saving the Tree to a text file in GraphViz format */
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void saveGraph(std::ostream &s, sharedClique clique,
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int parentnum = 0) const;
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/** Gather data on a single clique */
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void getCliqueData(CliqueData& stats, sharedClique clique) const;
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protected:
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/** Root clique */
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@ -130,15 +152,23 @@ namespace gtsam {
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virtual ~BayesTree() {
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}
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/** print */
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void print(const std::string& s = "") const;
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/**
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* Constructing Bayes trees
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*/
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/** saves the Tree 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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void saveGraph(std::ostream &s, sharedClique clique,
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int parentnum = 0) const;
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public:
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/** Insert a new conditional */
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void insert(const sharedConditional& conditional, const IndexTable<Symbol>& index);
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/** Insert a new clique corresponding to the given Bayes net.
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* It is the caller's responsibility to decide whether the given Bayes net is a valid clique,
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* i.e. all the variables (frontal and separator) are connected
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*/
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sharedClique insert(const BayesNet<Conditional>& bayesNet,
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std::list<sharedClique>& children, bool isRootClique = false);
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/**
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* Querying Bayes trees
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*/
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/** check equality */
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bool equals(const BayesTree<Conditional>& other, double tol = 1e-9) const;
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@ -149,15 +179,6 @@ namespace gtsam {
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*/
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Symbol findParentClique(const std::list<Symbol>& parents, const IndexTable<Symbol>& index) const;
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/** insert a new conditional */
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void insert(const sharedConditional& conditional, const IndexTable<Symbol>& index);
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/** insert a new clique corresponding to the given bayes net.
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* it is the caller's responsibility to decide whether the given bayes net is a valid clique,
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* i.e. all the variables (frontal and separator) are connected */
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sharedClique insert(const BayesNet<Conditional>& bayesNet,
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std::list<sharedClique>& children, bool isRootClique = false);
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/** number of cliques */
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inline size_t size() const {
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if(root_)
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@ -176,24 +197,9 @@ namespace gtsam {
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return nodes_.at(key);
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}
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/** clique statistics */
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struct CliqueStats {
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double avgConditionalSize;
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std::size_t maxConditionalSize;
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double avgSeparatorSize;
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std::size_t maxSeparatorSize;
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};
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struct CliqueData {
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std::vector<std::size_t> conditionalSizes;
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std::vector<std::size_t> separatorSizes;
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CliqueStats getStats() const;
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};
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/** Gather data on all cliques */
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CliqueData getCliqueData() const;
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private:
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void getCliqueData(CliqueData& stats, sharedClique clique) const;
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public:
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/** return marginal on any variable */
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template<class Factor>
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FactorGraph<Factor> marginal(const Symbol& key) const;
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@ -210,6 +216,20 @@ namespace gtsam {
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template<class Factor>
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BayesNet<Conditional> jointBayesNet(const Symbol& key1, const Symbol& key2) const;
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/**
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* Read only with side effects
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*/
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/** print */
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void print(const std::string& s = "") const;
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/** saves the Tree to a text file in GraphViz format */
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void saveGraph(const std::string& s) const;
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/**
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* Altering Bayes trees
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*/
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/**
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* Remove all nodes
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*/
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@ -69,19 +69,6 @@ SymbolicBayesTree createAsiaSymbolicBayesTree() {
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return bayesTree;
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}
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/* ************************************************************************* */
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TEST( BayesTree, Front )
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{
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SymbolicBayesNet f1;
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f1.push_back(B);
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f1.push_back(L);
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SymbolicBayesNet f2;
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f2.push_back(L);
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f2.push_back(B);
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CHECK(f1.equals(f1));
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CHECK(!f1.equals(f2));
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}
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/* ************************************************************************* */
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TEST( BayesTree, constructor )
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{
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@ -21,6 +21,24 @@ using namespace std;
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using namespace gtsam;
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using namespace example;
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Symbol _B_('B', 0), _L_('L', 0);
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SymbolicConditional::shared_ptr
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B(new SymbolicConditional(_B_)),
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L(new SymbolicConditional(_L_, _B_));
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/* ************************************************************************* */
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TEST( SymbolicBayesNet, equals )
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{
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SymbolicBayesNet f1;
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f1.push_back(B);
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f1.push_back(L);
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SymbolicBayesNet f2;
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f2.push_back(L);
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f2.push_back(B);
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CHECK(f1.equals(f1));
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CHECK(!f1.equals(f2));
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}
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/* ************************************************************************* */
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TEST( SymbolicBayesNet, constructor )
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{
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