175 lines
5.7 KiB
C++
175 lines
5.7 KiB
C++
/**
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* @file BayesTree.cpp
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* @brief Bayes Tree is a tree of cliques of a Bayes Chain
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* @author Frank Dellaert
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*/
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#include <boost/foreach.hpp>
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#include "BayesTree.h"
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#include "FactorGraph-inl.h"
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namespace gtsam {
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using namespace std;
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/* ************************************************************************* */
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template<class Conditional>
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BayesTree<Conditional>::Node::Node(const boost::shared_ptr<Conditional>& conditional) {
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separator_ = conditional->parents();
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this->push_back(conditional);
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}
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/* ************************************************************************* */
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template<class Conditional>
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void BayesTree<Conditional>::Node::print(const string& s) const {
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cout << s;
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BOOST_REVERSE_FOREACH(const conditional_ptr& conditional, this->conditionals_)
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cout << " " << conditional->key();
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if (!separator_.empty()) {
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cout << " :";
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BOOST_FOREACH(string key, separator_)
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cout << " " << key;
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}
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cout << endl;
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}
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/* ************************************************************************* */
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template<class Conditional>
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void BayesTree<Conditional>::Node::printTree(const string& indent) const {
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print(indent);
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BOOST_FOREACH(shared_ptr child, children_)
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child->printTree(indent+" ");
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}
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/* ************************************************************************* */
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template<class Conditional>
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BayesTree<Conditional>::BayesTree() {
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}
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/* ************************************************************************* */
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// TODO: traversal is O(n*log(n)) but could be O(n) with better bayesNet
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template<class Conditional>
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BayesTree<Conditional>::BayesTree(const BayesNet<Conditional>& bayesNet) {
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typename BayesNet<Conditional>::const_reverse_iterator rit;
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for ( rit=bayesNet.rbegin(); rit != bayesNet.rend(); ++rit )
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insert(*rit);
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}
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/* ************************************************************************* */
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template<class Conditional>
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void BayesTree<Conditional>::print(const string& s) const {
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cout << s << ": size == " << nodes_.size() << endl;
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if (nodes_.empty()) return;
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root_->printTree("");
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}
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/* ************************************************************************* */
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template<class Conditional>
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bool BayesTree<Conditional>::equals(const BayesTree<Conditional>& other,
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double tol) const {
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return size()==other.size();
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//&& equal(nodes_.begin(),nodes_.end(),other.nodes_.begin(),equals_star<Node>(tol));
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}
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/* ************************************************************************* */
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template<class Conditional>
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boost::shared_ptr<typename BayesTree<Conditional>::Node> BayesTree<Conditional>::addClique
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(const boost::shared_ptr<Conditional>& conditional, node_ptr parent_clique)
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{
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node_ptr new_clique(new Node(conditional));
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nodes_.insert(make_pair(conditional->key(), new_clique));
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if (parent_clique!=NULL) {
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new_clique->parent_ = parent_clique;
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parent_clique->children_.push_back(new_clique);
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}
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return new_clique;
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}
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/* ************************************************************************* */
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template<class Conditional>
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void BayesTree<Conditional>::insert
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(const boost::shared_ptr<Conditional>& conditional)
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{
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// get key and parents
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string key = conditional->key();
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list<string> parents = conditional->parents();
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// if no parents, start a new root clique
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if (parents.empty()) {
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root_ = addClique(conditional);
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return;
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}
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// otherwise, find the parent clique
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string parent = parents.front();
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typename Nodes::const_iterator it = nodes_.find(parent);
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if (it == nodes_.end()) throw(invalid_argument(
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"BayesTree::insert('"+key+"'): parent '" + parent + "' not yet inserted"));
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node_ptr parent_clique = it->second;
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// if the parents and parent clique have the same size, add to parent clique
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if (parent_clique->size() == parents.size()) {
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nodes_.insert(make_pair(key, parent_clique));
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parent_clique->push_front(conditional);
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return;
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}
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// otherwise, start a new clique and add it to the tree
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addClique(conditional,parent_clique);
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}
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/* ************************************************************************* */
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template<class Conditional>
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template<class Factor>
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boost::shared_ptr<Conditional> BayesTree<Conditional>::marginal(const string& key) const {
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// find the clique to which key belongs
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typename Nodes::const_iterator it = nodes_.find(key);
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if (it == nodes_.end()) throw(invalid_argument(
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"BayesTree::marginal('"+key+"'): key not found"));
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// get clique containing key, and remove all factors below key
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node_ptr clique = it->second;
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Ordering ordering = clique->ordering();
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FactorGraph<Factor> graph(*clique);
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while(ordering.front()!=key) {
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graph.findAndRemoveFactors(ordering.front());
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ordering.pop_front();
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}
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// find all cliques on the path to the root and turn into factor graph
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while (clique->parent_!=NULL) {
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// move up the tree
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clique = clique->parent_;
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// extend ordering
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Ordering cliqueOrdering = clique->ordering();
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ordering.splice (ordering.end(), cliqueOrdering);
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// extend factor graph
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FactorGraph<Factor> cliqueGraph(*clique);
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typename FactorGraph<Factor>::const_iterator factor=cliqueGraph.begin();
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for(; factor!=cliqueGraph.end(); factor++)
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graph.push_back(*factor);
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}
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//graph.print();
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ordering.reverse();
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//ordering.print();
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// eliminate to get marginal
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boost::shared_ptr<BayesNet<Conditional> > bayesNet;
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typename boost::shared_ptr<BayesNet<Conditional> > chordalBayesNet =
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graph.eliminate(bayesNet,ordering);
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//chordalBayesNet->print("chordalBayesNet");
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boost::shared_ptr<Conditional> marginal = chordalBayesNet->back();
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return marginal;
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}
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/* ************************************************************************* */
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}
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/// namespace gtsam
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