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Made JunctionTree a subclass of ClusterTree

release/4.3a0
Frank Dellaert 2010-07-14 04:32:58 +00:00
parent c3a907127f
commit d07dfac236
7 changed files with 66 additions and 247 deletions
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93
inference/ClusterTree-inl.h
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@ -20,7 +20,7 @@ namespace gtsam {
/* ************************************************************************* */
template <class FG>
bool ClusterTree<FG>::Clique::equals(const ClusterTree<FG>::Clique& other) const {
bool ClusterTree<FG>::Cluster::equals(const ClusterTree<FG>::Cluster& other) const {
if (!frontal_.equals(other.frontal_))
return false;
@ -43,7 +43,7 @@ namespace gtsam {
* ClusterTree
*/
template <class FG>
void ClusterTree<FG>::Clique::print(const string& indent) const {
void ClusterTree<FG>::Cluster::print(const string& indent) const {
// FG::print(indent);
cout << indent;
BOOST_FOREACH(const Symbol& key, frontal_)
@ -56,99 +56,12 @@ namespace gtsam {
/* ************************************************************************* */
template <class FG>
void ClusterTree<FG>::Clique::printTree(const string& indent) const {
void ClusterTree<FG>::Cluster::printTree(const string& indent) const {
print(indent);
BOOST_FOREACH(const shared_ptr& child, children_)
child->printTree(indent+" ");
}
/* ************************************************************************* */
template <class FG>
ClusterTree<FG>::ClusterTree(FG& fg, const Ordering& ordering) {
// Symbolic factorization: GaussianFactorGraph -> SymbolicFactorGraph -> SymbolicBayesNet -> SymbolicBayesTree
SymbolicFactorGraph sfg(fg);
SymbolicBayesNet sbn = sfg.eliminate(ordering);
BayesTree<SymbolicConditional> sbt(sbn);
// distribtue factors
root_ = distributeFactors(fg, sbt.root());
}
/* ************************************************************************* */
template <class FG>
typename ClusterTree<FG>::sharedClique ClusterTree<FG>::distributeFactors(FG& fg,
const BayesTree<SymbolicConditional>::sharedClique bayesClique) {
// create a new clique in the junction tree
sharedClique clique(new Clique());
clique->frontal_ = bayesClique->ordering();
clique->separator_.insert(bayesClique->separator_.begin(), bayesClique->separator_.end());
// recursively call the children
BOOST_FOREACH(const BayesTree<SymbolicConditional>::sharedClique bayesChild, bayesClique->children()) {
sharedClique child = distributeFactors(fg, bayesChild);
clique->children_.push_back(child);
child->parent_ = clique;
}
// collect the factors
typedef vector<typename FG::sharedFactor> Factors;
BOOST_FOREACH(const Symbol& frontal, clique->frontal_) {
Factors factors = fg.template findAndRemoveFactors<Factors>(frontal);
BOOST_FOREACH(const typename FG::sharedFactor& factor_, factors) {
clique->push_back(factor_);
}
}
return clique;
}
/* ************************************************************************* */
template <class FG> template <class Conditional>
pair<FG, BayesTree<Conditional> >
ClusterTree<FG>::eliminateOneClique(sharedClique current) {
// current->frontal_.print("current clique:");
typedef typename BayesTree<Conditional>::sharedClique sharedBtreeClique;
FG fg; // factor graph will be assembled from local factors and marginalized children
list<BayesTree<Conditional> > children;
fg.push_back(*current); // add the local factor graph
// BOOST_FOREACH(const typename FG::sharedFactor& factor_, fg)
// Ordering(factor_->keys()).print("local factor:");
BOOST_FOREACH(sharedClique& child, current->children_) {
// receive the factors from the child and its clique point
FG fgChild; BayesTree<Conditional> childTree;
boost::tie(fgChild, childTree) = eliminateOneClique<Conditional>(child);
// BOOST_FOREACH(const typename FG::sharedFactor& factor_, fgChild)
// Ordering(factor_->keys()).print("factor from child:");
fg.push_back(fgChild);
children.push_back(childTree);
}
// eliminate the combined factors
// warning: fg is being eliminated in-place and will contain marginal afterwards
BayesNet<Conditional> bn = fg.eliminateFrontals(current->frontal_);
// create a new clique corresponding the combined factors
BayesTree<Conditional> bayesTree(bn, children);
return make_pair(fg, bayesTree);
}
/* ************************************************************************* */
template <class FG> template <class Conditional>
BayesTree<Conditional> ClusterTree<FG>::eliminate() {
pair<FG, BayesTree<Conditional> > ret = this->eliminateOneClique<Conditional>(root_);
// ret.first.print("ret.first");
if (ret.first.nrFactors() != 0)
throw runtime_error("JuntionTree::eliminate: elimination failed because of factors left over!");
return ret.second;
}
/* ************************************************************************* */
template <class FG>
bool ClusterTree<FG>::equals(const ClusterTree<FG>& other, double tol) const {

67
inference/ClusterTree.h
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@ -10,38 +10,45 @@
#include <set>
#include <boost/shared_ptr.hpp>
#include "BayesTree.h"
#include "SymbolicConditional.h"
namespace gtsam {
/* ************************************************************************* */
/**
* A cluster-tree is associated with a factor graph and is defined as in Koller-Friedman:
* each node k represents a subset C_k \sub X, and the tree is family preserving, in that
* each factor f_i is associated with a single cluster and scope(f_i) \sub C_k.
*/
template <class FG>
class ClusterTree : public Testable<ClusterTree<FG> > {
public:
// the class for subgraphs that also include the pointers to the parents and two children
class Clique : public FG {
private:
typedef typename boost::shared_ptr<Clique> shared_ptr;
shared_ptr parent_; // the parent subgraph node
std::vector<shared_ptr> children_; // the child cliques
Ordering frontal_; // the frontal varaibles
Unordered separator_; // the separator variables
friend class ClusterTree<FG>;
public:
// the class for subgraphs that also include the pointers to the parents and two children
class Cluster : public FG {
public:
typedef typename boost::shared_ptr<Cluster> shared_ptr;
/* commented private out to make compile but needs to be addressed */
shared_ptr parent_; // the parent subgraph node
std::vector<shared_ptr> children_; // the child clusters
Ordering frontal_; // the frontal variables
Unordered separator_; // the separator variables
public:
// empty constructor
Clique() {}
Cluster() {}
// constructor with all the information
Clique(const FG& fgLocal, const Ordering& frontal, const Unordered& separator,
Cluster(const FG& fgLocal, const Ordering& frontal, const Unordered& separator,
const shared_ptr& parent)
: frontal_(frontal), separator_(separator), FG(fgLocal), parent_(parent) {}
// constructor for an empty graph
Clique(const Ordering& frontal, const Unordered& separator, const shared_ptr& parent)
Cluster(const Ordering& frontal, const Unordered& separator, const shared_ptr& parent)
: frontal_(frontal), separator_(separator), parent_(parent) {}
// return the members
@ -57,23 +64,15 @@ namespace gtsam {
void printTree(const std::string& indent) const;
// check equality
bool equals(const Clique& other) const;
bool equals(const Cluster& other) const;
};
// typedef for shared pointers to cliques
typedef typename Clique::shared_ptr sharedClique;
// typedef for shared pointers to clusters
typedef typename Cluster::shared_ptr sharedCluster;
protected:
// Root clique
sharedClique root_;
private:
// distribute the factors along the Bayes tree
sharedClique distributeFactors(FG& fg, const BayesTree<SymbolicConditional>::sharedClique clique);
// utility function called by eliminate
template <class Conditional>
std::pair<FG, BayesTree<Conditional> > eliminateOneClique(sharedClique fg_);
// Root cluster
sharedCluster root_;
public:
// constructor
@ -82,16 +81,12 @@ namespace gtsam {
// constructor given a factor graph and the elimination ordering
ClusterTree(FG& fg, const Ordering& ordering);
// return the root clique
sharedClique root() const { return root_; }
// eliminate the factors in the subgraphs
template <class Conditional>
BayesTree<Conditional> eliminate();
// return the root cluster
sharedCluster root() const { return root_; }
// print the object
void print(const std::string& str) const {
cout << str << endl;
std::cout << str << std::endl;
if (root_.get()) root_->printTree("");
}

66
inference/JunctionTree-inl.h
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@ -18,70 +18,28 @@ namespace gtsam {
using namespace std;
/* ************************************************************************* */
template <class FG>
bool JunctionTree<FG>::Clique::equals(const JunctionTree<FG>::Clique& other) const {
if (!frontal_.equals(other.frontal_))
return false;
if (!separator_.equals(other.separator_))
return false;
if (children_.size() != other.children_.size())
return false;
typename vector<shared_ptr>::const_iterator it1 = children_.begin();
typename vector<shared_ptr>::const_iterator it2 = other.children_.begin();
for(; it1!=children_.end(); it1++, it2++)
if (!(*it1)->equals(**it2)) return false;
return true;
}
/* ************************************************************************* */
/**
* JunctionTree
*/
template <class FG>
void JunctionTree<FG>::Clique::print(const string& indent) const {
// FG::print(indent);
cout << indent;
BOOST_FOREACH(const Symbol& key, frontal_)
cout << (string)key << " ";
cout << ":";
BOOST_FOREACH(const Symbol& key, separator_)
cout << (string)key << " ";
cout << endl;
}
/* ************************************************************************* */
template <class FG>
void JunctionTree<FG>::Clique::printTree(const string& indent) const {
print(indent);
BOOST_FOREACH(const shared_ptr& child, children_)
child->printTree(indent+" ");
}
/* ************************************************************************* */
template <class FG>
JunctionTree<FG>::JunctionTree(FG& fg, const Ordering& ordering) {
// Symbolic factorization: GaussianFactorGraph -> SymbolicFactorGraph -> SymbolicBayesNet -> SymbolicBayesTree
// Symbolic factorization: GaussianFactorGraph -> SymbolicFactorGraph
// -> SymbolicBayesNet -> SymbolicBayesTree
SymbolicFactorGraph sfg(fg);
SymbolicBayesNet sbn = sfg.eliminate(ordering);
BayesTree<SymbolicConditional> sbt(sbn);
// distribtue factors
root_ = distributeFactors(fg, sbt.root());
this->root_ = distributeFactors(fg, sbt.root());
}
/* ************************************************************************* */
template<class FG>
typename JunctionTree<FG>::sharedClique JunctionTree<FG>::distributeFactors(FG& fg,
const BayesTree<SymbolicConditional>::sharedClique bayesClique) {
typename JunctionTree<FG>::sharedClique JunctionTree<FG>::distributeFactors(
FG& fg, const BayesTree<SymbolicConditional>::sharedClique bayesClique) {
// create a new clique in the junction tree
sharedClique clique(new Clique());
clique->frontal_ = bayesClique->ordering();
clique->separator_.insert(bayesClique->separator_.begin(), bayesClique->separator_.end());
clique->separator_.insert(bayesClique->separator_.begin(),
bayesClique->separator_.end());
// recursively call the children
BOOST_FOREACH(const BayesTree<SymbolicConditional>::sharedClique bayesChild, bayesClique->children()) {
@ -142,18 +100,10 @@ namespace gtsam {
/* ************************************************************************* */
template <class FG> template <class Conditional>
BayesTree<Conditional> JunctionTree<FG>::eliminate() {
pair<FG, BayesTree<Conditional> > ret = this->eliminateOneClique<Conditional>(root_);
// ret.first.print("ret.first");
pair<FG, BayesTree<Conditional> > ret = this->eliminateOneClique<Conditional>(this->root());
if (ret.first.nrFactors() != 0)
throw runtime_error("JuntionTree::eliminate: elimination failed because of factors left over!");
return ret.second;
}
/* ************************************************************************* */
template <class FG>
bool JunctionTree<FG>::equals(const JunctionTree<FG>& other, double tol) const {
if (!root_ || !other.root_) return false;
return root_->equals(*other.root_);
}
} //namespace gtsam

71
inference/JunctionTree.h
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@ -11,62 +11,29 @@
#include <set>
#include <boost/shared_ptr.hpp>
#include "BayesTree.h"
#include "ClusterTree.h"
#include "SymbolicConditional.h"
namespace gtsam {
/* ************************************************************************* */
/**
* A junction tree (or clique-tree) is a cluster-tree where each node k represents a
* clique (maximal fully connected subset) of an associated chordal graph, such as a
* chordal Bayes net resulting from elimination. In GTSAM the BayesTree is used to
* represent the clique tree associated with a Bayes net, and the JunctionTree is
* used to collect the factors associated with each clique during the elimination process.
*/
template <class FG>
class JunctionTree : public Testable<JunctionTree<FG> > {
public:
// the class for subgraphs that also include the pointers to the parents and two children
class Clique : public FG {
private:
typedef typename boost::shared_ptr<Clique> shared_ptr;
shared_ptr parent_; // the parent subgraph node
std::vector<shared_ptr> children_; // the child cliques
Ordering frontal_; // the frontal varaibles
Unordered separator_; // the separator variables
friend class JunctionTree<FG>;
class JunctionTree : public ClusterTree<FG> {
public:
// empty constructor
Clique() {}
// constructor with all the information
Clique(const FG& fgLocal, const Ordering& frontal, const Unordered& separator,
const shared_ptr& parent)
: frontal_(frontal), separator_(separator), FG(fgLocal), parent_(parent) {}
// constructor for an empty graph
Clique(const Ordering& frontal, const Unordered& separator, const shared_ptr& parent)
: frontal_(frontal), separator_(separator), parent_(parent) {}
// return the members
const Ordering& frontal() const { return frontal_;}
const Unordered& separator() const { return separator_;}
const std::vector<shared_ptr>& children() { return children_; }
// add a child node
void addChild(const shared_ptr& child) { children_.push_back(child); }
// print the object
void print(const std::string& indent) const;
void printTree(const std::string& indent) const;
// check equality
bool equals(const Clique& other) const;
};
// typedef for shared pointers to cliques
/**
* In a junction tree each cluster is associated with a clique
*/
typedef typename ClusterTree<FG>::Cluster Clique;
typedef typename Clique::shared_ptr sharedClique;
protected:
// Root clique
sharedClique root_;
private:
// distribute the factors along the Bayes tree
sharedClique distributeFactors(FG& fg, const BayesTree<SymbolicConditional>::sharedClique clique);
@ -82,22 +49,10 @@ namespace gtsam {
// constructor given a factor graph and the elimination ordering
JunctionTree(FG& fg, const Ordering& ordering);
// return the root clique
sharedClique root() const { return root_; }
// eliminate the factors in the subgraphs
template <class Conditional>
BayesTree<Conditional> eliminate();
// print the object
void print(const std::string& str) const {
std::cout << str << std::endl;
if (root_.get()) root_->printTree("");
}
/** check equality */
bool equals(const JunctionTree<FG>& other, double tol = 1e-9) const;
}; // JunctionTree
} // namespace gtsam

2
inference/testClusterTree.cpp
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@ -15,6 +15,8 @@ using namespace boost::assign;
using namespace gtsam;
// explicit instantiation and typedef
template class ClusterTree<SymbolicFactorGraph>;
typedef ClusterTree<SymbolicFactorGraph> SymbolicClusterTree;
/* ************************************************************************* */

9
inference/testJunctionTree.cpp
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@ -15,18 +15,21 @@ using namespace boost::assign;
#include "Ordering.h"
#include "SymbolicFactorGraph.h"
#include "JunctionTree.h"
#include "ClusterTree-inl.h"
#include "JunctionTree-inl.h"
using namespace gtsam;
// explicit instantiation and typedef
template class JunctionTree<SymbolicFactorGraph>;
typedef JunctionTree<SymbolicFactorGraph> SymbolicJunctionTree;
/* ************************************************************************* */
/**
/* ************************************************************************* *
* x1 - x2 - x3 - x4
* x3 x4
* x2 x1 : x3
*/
****************************************************************************/
TEST( JunctionTree, constructor )
{
SymbolicFactorGraph fg;

1
linear/GaussianJunctionTree.cpp
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@ -8,6 +8,7 @@
#include <boost/foreach.hpp>
#include "ClusterTree-inl.h"
#include "JunctionTree-inl.h"
#include "GaussianJunctionTree.h"