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/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file BayesTree.cpp
* @brief Bayes Tree is a tree of cliques of a Bayes Chain
* @author Frank Dellaert
* @author Michael Kaess
* @author Viorela Ila
* @author Richard Roberts
*/
#pragma once
#include <gtsam/base/FastSet.h>
#include <gtsam/base/FastVector.h>
#include <gtsam/inference/BayesTree.h>
#include <gtsam/inference/inference.h>
#include <gtsam/inference/GenericSequentialSolver-inl.h>
#include <iostream>
#include <algorithm>
#include <boost/foreach.hpp>
#include <boost/assign/std/list.hpp> // for operator +=
#include <boost/format.hpp>
#include <boost/lambda/lambda.hpp>
#include <boost/iterator/transform_iterator.hpp>
#include <fstream>
using namespace boost::assign;
namespace lam = boost::lambda;
namespace gtsam {
using namespace std;
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::Clique::assertInvariants() const {
#ifndef NDEBUG
// We rely on the keys being sorted
// FastVector<Index> sortedUniqueKeys(conditional_->begin(), conditional_->end());
// std::sort(sortedUniqueKeys.begin(), sortedUniqueKeys.end());
// std::unique(sortedUniqueKeys.begin(), sortedUniqueKeys.end());
// assert(sortedUniqueKeys.size() == conditional_->size() &&
// std::equal(sortedUniqueKeys.begin(), sortedUniqueKeys.end(), conditional_->begin()));
#endif
}
/* ************************************************************************* */
template<class CONDITIONAL>
BayesTree<CONDITIONAL>::Clique::Clique(const sharedConditional& conditional) : conditional_(conditional) {
assertInvariants();
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::Clique::print(const string& s) const {
conditional_->print(s);
}
/* ************************************************************************* */
template<class CONDITIONAL>
size_t BayesTree<CONDITIONAL>::Clique::treeSize() const {
size_t size = 1;
BOOST_FOREACH(const shared_ptr& child, children_)
size += child->treeSize();
return size;
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::Clique::printTree(const string& indent) const {
print(indent);
BOOST_FOREACH(const shared_ptr& child, children_)
child->printTree(indent+" ");
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::Clique::permuteWithInverse(const Permutation& inversePermutation) {
conditional_->permuteWithInverse(inversePermutation);
if(cachedFactor_) cachedFactor_->permuteWithInverse(inversePermutation);
BOOST_FOREACH(const shared_ptr& child, children_) {
child->permuteWithInverse(inversePermutation);
}
assertInvariants();
}
/* ************************************************************************* */
template<class CONDITIONAL>
bool BayesTree<CONDITIONAL>::Clique::permuteSeparatorWithInverse(const Permutation& inversePermutation) {
bool changed = conditional_->permuteSeparatorWithInverse(inversePermutation);
#ifndef NDEBUG
if(!changed) {
BOOST_FOREACH(Index& separatorKey, conditional_->parents()) { assert(separatorKey == inversePermutation[separatorKey]); }
BOOST_FOREACH(const shared_ptr& child, children_) {
assert(child->permuteSeparatorWithInverse(inversePermutation) == false);
}
}
#endif
if(changed) {
if(cachedFactor_) cachedFactor_->permuteWithInverse(inversePermutation);
BOOST_FOREACH(const shared_ptr& child, children_) {
(void)child->permuteSeparatorWithInverse(inversePermutation);
}
}
assertInvariants();
return changed;
}
/* ************************************************************************* */
template<class CONDITIONAL>
typename BayesTree<CONDITIONAL>::CliqueData
BayesTree<CONDITIONAL>::getCliqueData() const {
CliqueData data;
getCliqueData(data, root_);
return data;
}
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::getCliqueData(CliqueData& data,
BayesTree<CONDITIONAL>::sharedClique clique) const {
data.conditionalSizes.push_back((*clique)->nrFrontals());
data.separatorSizes.push_back((*clique)->nrParents());
BOOST_FOREACH(sharedClique c, clique->children_) {
getCliqueData(data, c);
}
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::saveGraph(const std::string &s) const {
if (!root_.get()) throw invalid_argument("the root of bayes tree has not been initialized!");
ofstream of(s.c_str());
of<< "digraph G{\n";
saveGraph(of, root_);
of<<"}";
of.close();
}
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::saveGraph(ostream &s,
BayesTree<CONDITIONAL>::sharedClique clique,
int parentnum) const {
static int num = 0;
bool first = true;
std::stringstream out;
out << num;
string parent = out.str();
parent += "[label=\"";
BOOST_FOREACH(boost::shared_ptr<CONDITIONAL> c, clique->conditionals_) {
if(!first) parent += ","; first = false;
parent += (string(c->key())).c_str();
}
if( clique != root_){
parent += " : ";
s << parentnum << "->" << num << "\n";
}
first = true;
BOOST_FOREACH(Index sep, clique->separator_) {
if(!first) parent += ","; first = false;
parent += (boost::format("%1%")%sep).str();
}
parent += "\"];\n";
s << parent;
parentnum = num;
BOOST_FOREACH(sharedClique c, clique->children_) {
num++;
saveGraph(s, c, parentnum);
}
}
template<class CONDITIONAL>
typename BayesTree<CONDITIONAL>::CliqueStats
BayesTree<CONDITIONAL>::CliqueData::getStats() const {
CliqueStats stats;
double sum = 0.0;
size_t max = 0;
BOOST_FOREACH(size_t s, conditionalSizes) {
sum += (double)s;
if(s > max) max = s;
}
stats.avgConditionalSize = sum / (double)conditionalSizes.size();
stats.maxConditionalSize = max;
sum = 0.0;
max = 1;
BOOST_FOREACH(size_t s, separatorSizes) {
sum += (double)s;
if(s > max) max = s;
}
stats.avgSeparatorSize = sum / (double)separatorSizes.size();
stats.maxSeparatorSize = max;
return stats;
}
/* ************************************************************************* */
// The shortcut density is a conditional P(S|R) of the separator of this
// clique on the root. We can compute it recursively from the parent shortcut
// P(Sp|R) as \int P(Fp|Sp) P(Sp|R), where Fp are the frontal nodes in p
/* ************************************************************************* */
template<class CONDITIONAL>
BayesNet<CONDITIONAL> BayesTree<CONDITIONAL>::Clique::shortcut(shared_ptr R,
Eliminate function) {
static const bool debug = false;
// A first base case is when this clique or its parent is the root,
// in which case we return an empty Bayes net.
sharedClique parent(parent_.lock());
if (R.get()==this || parent==R) {
BayesNet<CONDITIONAL> empty;
return empty;
}
// The root conditional
FactorGraph<FactorType> p_R(BayesNet<CONDITIONAL>(R->conditional()));
// The parent clique has a CONDITIONAL for each frontal node in Fp
// so we can obtain P(Fp|Sp) in factor graph form
FactorGraph<FactorType> p_Fp_Sp(BayesNet<CONDITIONAL>(parent->conditional()));
// If not the base case, obtain the parent shortcut P(Sp|R) as factors
FactorGraph<FactorType> p_Sp_R(parent->shortcut(R, function));
// now combine P(Cp|R) = P(Fp|Sp) * P(Sp|R)
FactorGraph<FactorType> p_Cp_R;
p_Cp_R.push_back(p_R);
p_Cp_R.push_back(p_Fp_Sp);
p_Cp_R.push_back(p_Sp_R);
// Eliminate into a Bayes net with ordering designed to integrate out
// any variables not in *our* separator. Variables to integrate out must be
// eliminated first hence the desired ordering is [Cp\S S].
// However, an added wrinkle is that Cp might overlap with the root.
// Keys corresponding to the root should not be added to the ordering at all.
if(debug) {
p_R.print("p_R: ");
p_Fp_Sp.print("p_Fp_Sp: ");
p_Sp_R.print("p_Sp_R: ");
}
// We want to factor into a conditional of the clique variables given the
// root and the marginal on the root, integrating out all other variables.
// The integrands include any parents of this clique and the variables of
// the parent clique.
FastSet<Index> variablesAtBack;
FastSet<Index> separator;
size_t uniqueRootVariables = 0;
BOOST_FOREACH(const Index separatorIndex, this->conditional()->parents()) {
variablesAtBack.insert(separatorIndex);
separator.insert(separatorIndex);
if(debug) cout << "At back (this): " << separatorIndex << endl;
}
BOOST_FOREACH(const Index key, R->conditional()->keys()) {
if(variablesAtBack.insert(key).second)
++ uniqueRootVariables;
if(debug) cout << "At back (root): " << key << endl;
}
Permutation toBack = Permutation::PushToBack(
vector<Index>(variablesAtBack.begin(), variablesAtBack.end()),
R->conditional()->lastFrontalKey() + 1);
Permutation::shared_ptr toBackInverse(toBack.inverse());
BOOST_FOREACH(const typename FactorType::shared_ptr& factor, p_Cp_R) {
factor->permuteWithInverse(*toBackInverse); }
typename BayesNet<CONDITIONAL>::shared_ptr eliminated(EliminationTree<
FactorType>::Create(p_Cp_R)->eliminate(function));
// Take only the conditionals for p(S|R). We check for each variable being
// in the separator set because if some separator variables overlap with
// root variables, we cannot rely on the number of root variables, and also
// want to include those variables in the conditional.
BayesNet<CONDITIONAL> p_S_R;
BOOST_REVERSE_FOREACH(typename CONDITIONAL::shared_ptr conditional, *eliminated) {
assert(conditional->nrFrontals() == 1);
if(separator.find(toBack[conditional->firstFrontalKey()]) != separator.end()) {
if(debug)
conditional->print("Taking C|R conditional: ");
p_S_R.push_front(conditional);
}
if(p_S_R.size() == separator.size())
break;
}
// Undo the permutation
if(debug) toBack.print("toBack: ");
p_S_R.permuteWithInverse(toBack);
// return the parent shortcut P(Sp|R)
assertInvariants();
return p_S_R;
}
/* ************************************************************************* */
// P(C) = \int_R P(F|S) P(S|R) P(R)
// TODO: Maybe we should integrate given parent marginal P(Cp),
// \int(Cp\S) P(F|S)P(S|Cp)P(Cp)
// Because the root clique could be very big.
/* ************************************************************************* */
template<class CONDITIONAL>
FactorGraph<typename CONDITIONAL::FactorType> BayesTree<CONDITIONAL>::Clique::marginal(
shared_ptr R, Eliminate function) {
// If we are the root, just return this root
// NOTE: immediately cast to a factor graph
BayesNet<CONDITIONAL> bn(R->conditional());
if (R.get()==this) return bn;
// Combine P(F|S), P(S|R), and P(R)
BayesNet<CONDITIONAL> p_FSR = this->shortcut(R, function);
p_FSR.push_front(this->conditional());
p_FSR.push_back(R->conditional());
assertInvariants();
GenericSequentialSolver<FactorType> solver(p_FSR);
return *solver.jointFactorGraph(conditional_->keys(), function);
}
/* ************************************************************************* */
// P(C1,C2) = \int_R P(F1|S1) P(S1|R) P(F2|S1) P(S2|R) P(R)
/* ************************************************************************* */
template<class CONDITIONAL>
FactorGraph<typename CONDITIONAL::FactorType> BayesTree<CONDITIONAL>::Clique::joint(
shared_ptr C2, shared_ptr R, Eliminate function) {
// For now, assume neither is the root
// Combine P(F1|S1), P(S1|R), P(F2|S2), P(S2|R), and P(R)
FactorGraph<FactorType> joint;
if (!isRoot()) joint.push_back(this->conditional()->toFactor()); // P(F1|S1)
if (!isRoot()) joint.push_back(shortcut(R, function)); // P(S1|R)
if (!C2->isRoot()) joint.push_back(C2->conditional()->toFactor()); // P(F2|S2)
if (!C2->isRoot()) joint.push_back(C2->shortcut(R, function)); // P(S2|R)
joint.push_back(R->conditional()->toFactor()); // P(R)
// Find the keys of both C1 and C2
vector<Index> keys1(conditional_->keys());
vector<Index> keys2(C2->conditional_->keys());
FastSet<Index> keys12;
keys12.insert(keys1.begin(), keys1.end());
keys12.insert(keys2.begin(), keys2.end());
// Calculate the marginal
vector<Index> keys12vector; keys12vector.reserve(keys12.size());
keys12vector.insert(keys12vector.begin(), keys12.begin(), keys12.end());
assertInvariants();
GenericSequentialSolver<FactorType> solver(joint);
return *solver.jointFactorGraph(keys12vector, function);
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::Cliques::print(const std::string& s) const {
cout << s << ":\n";
BOOST_FOREACH(sharedClique clique, *this)
clique->printTree();
}
/* ************************************************************************* */
template<class CONDITIONAL>
bool BayesTree<CONDITIONAL>::Cliques::equals(const Cliques& other, double tol) const {
return other == *this;
}
/* ************************************************************************* */
template<class CONDITIONAL>
typename BayesTree<CONDITIONAL>::sharedClique BayesTree<CONDITIONAL>::addClique(
const sharedConditional& conditional, sharedClique parent_clique) {
sharedClique new_clique(new Clique(conditional));
nodes_.resize(std::max(conditional->lastFrontalKey()+1, nodes_.size()));
BOOST_FOREACH(Index key, conditional->frontals())
nodes_[key] = new_clique;
if (parent_clique != NULL) {
new_clique->parent_ = parent_clique;
parent_clique->children_.push_back(new_clique);
}
new_clique->assertInvariants();
return new_clique;
}
/* ************************************************************************* */
template<class CONDITIONAL>
typename BayesTree<CONDITIONAL>::sharedClique BayesTree<CONDITIONAL>::addClique(
const sharedConditional& conditional, list<sharedClique>& child_cliques) {
sharedClique new_clique(new Clique(conditional));
nodes_.resize(std::max(conditional->lastFrontalKey()+1, nodes_.size()));
BOOST_FOREACH(Index key, conditional->frontals())
nodes_[key] = new_clique;
new_clique->children_ = child_cliques;
BOOST_FOREACH(sharedClique& child, child_cliques)
child->parent_ = new_clique;
new_clique->assertInvariants();
return new_clique;
}
/* ************************************************************************* */
template<class CONDITIONAL>
inline void BayesTree<CONDITIONAL>::addToCliqueFront(BayesTree<CONDITIONAL>& bayesTree, const sharedConditional& conditional, const sharedClique& clique) {
static const bool debug = false;
#ifndef NDEBUG
// Debug check to make sure the conditional variable is ordered lower than
// its parents and that all of its parents are present either in this
// clique or its separator.
BOOST_FOREACH(Index parent, conditional->parents()) {
assert(parent > conditional->lastFrontalKey());
const Clique& cliquer(*clique);
assert(find(cliquer->begin(), cliquer->end(), parent) != cliquer->end());
}
#endif
if(debug) conditional->print("Adding conditional ");
if(debug) clique->print("To clique ");
Index key = conditional->lastFrontalKey();
bayesTree.nodes_.resize(std::max(key+1, bayesTree.nodes_.size()));
bayesTree.nodes_[key] = clique;
FastVector<Index> newKeys((*clique)->size() + 1);
newKeys[0] = key;
std::copy((*clique)->begin(), (*clique)->end(), newKeys.begin()+1);
clique->conditional_ = CONDITIONAL::FromKeys(newKeys, (*clique)->nrFrontals() + 1);
// clique->conditional_->addFrontal(conditional);
if(debug) clique->print("Expanded clique is ");
clique->assertInvariants();
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::removeClique(sharedClique clique) {
if (clique->isRoot())
root_.reset();
else // detach clique from parent
clique->parent_.lock()->children_.remove(clique);
// orphan my children
BOOST_FOREACH(sharedClique child, clique->children_)
child->parent_ = typename BayesTree<CONDITIONAL>::Clique::weak_ptr();
BOOST_FOREACH(Index key, (*clique->conditional())) {
nodes_[key].reset();
}
}
/* ************************************************************************* */
template<class CONDITIONAL>
BayesTree<CONDITIONAL>::BayesTree() {
}
/* ************************************************************************* */
template<class CONDITIONAL>
BayesTree<CONDITIONAL>::BayesTree(const BayesNet<CONDITIONAL>& bayesNet) {
typename BayesNet<CONDITIONAL>::const_reverse_iterator rit;
for ( rit=bayesNet.rbegin(); rit != bayesNet.rend(); ++rit )
insert(*this, *rit);
}
/* ************************************************************************* */
template<class CONDITIONAL>
BayesTree<CONDITIONAL>::BayesTree(const BayesNet<CONDITIONAL>& bayesNet, std::list<BayesTree<CONDITIONAL> > subtrees) {
if (bayesNet.size() == 0)
throw invalid_argument("BayesTree::insert: empty bayes net!");
// get the roots of child subtrees and merge their nodes_
list<sharedClique> childRoots;
BOOST_FOREACH(const BayesTree<CONDITIONAL>& subtree, subtrees) {
nodes_.insert(subtree.nodes_.begin(), subtree.nodes_.end());
childRoots.push_back(subtree.root());
}
// create a new clique and add all the conditionals to the clique
sharedClique new_clique;
typename BayesNet<CONDITIONAL>::sharedConditional conditional;
BOOST_REVERSE_FOREACH(conditional, bayesNet) {
if (!new_clique.get())
new_clique = addClique(conditional,childRoots);
else
addToCliqueFront(*this, conditional, new_clique);
}
root_ = new_clique;
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::print(const string& s) const {
if (root_.use_count() == 0) {
printf("WARNING: BayesTree.print encountered a forest...\n");
return;
}
cout << s << ": clique size == " << size() << ", node size == " << nodes_.size() << endl;
if (nodes_.empty()) return;
root_->printTree("");
}
/* ************************************************************************* */
// binary predicate to test equality of a pair for use in equals
template<class CONDITIONAL>
bool check_sharedCliques(
const typename BayesTree<CONDITIONAL>::sharedClique& v1,
const typename BayesTree<CONDITIONAL>::sharedClique& v2
) {
return v1->equals(*v2);
}
/* ************************************************************************* */
template<class CONDITIONAL>
bool BayesTree<CONDITIONAL>::equals(const BayesTree<CONDITIONAL>& other,
double tol) const {
return size()==other.size() &&
std::equal(nodes_.begin(), nodes_.end(), other.nodes_.begin(), &check_sharedCliques<CONDITIONAL>);
}
/* ************************************************************************* */
template<class CONDITIONAL>
template<class CONTAINER>
inline Index BayesTree<CONDITIONAL>::findParentClique(const CONTAINER& parents) const {
typename CONTAINER::const_iterator lowestOrderedParent = min_element(parents.begin(), parents.end());
assert(lowestOrderedParent != parents.end());
return *lowestOrderedParent;
// boost::optional<Index> parentCliqueRepresentative;
// boost::optional<size_t> lowest;
// BOOST_FOREACH(Index p, parents) {
// size_t i = index(p);
// if (!lowest || i<*lowest) {
// lowest.reset(i);
// parentCliqueRepresentative.reset(p);
// }
// }
// if (!lowest) throw
// invalid_argument("BayesTree::findParentClique: no parents given or key not present in index");
// return *parentCliqueRepresentative;
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::insert(BayesTree<CONDITIONAL>& bayesTree, const sharedConditional& conditional)
{
static const bool debug = false;
// get key and parents
const typename CONDITIONAL::Parents& parents = conditional->parents();
if(debug) conditional->print("Adding conditional ");
// if no parents, start a new root clique
if (parents.empty()) {
if(debug) cout << "No parents so making root" << endl;
bayesTree.root_ = bayesTree.addClique(conditional);
return;
}
// otherwise, find the parent clique by using the index data structure
// to find the lowest-ordered parent
Index parentRepresentative = bayesTree.findParentClique(parents);
if(debug) cout << "First-eliminated parent is " << parentRepresentative << ", have " << bayesTree.nodes_.size() << " nodes." << endl;
sharedClique parent_clique = bayesTree[parentRepresentative];
if(debug) parent_clique->print("Parent clique is ");
// if the parents and parent clique have the same size, add to parent clique
if ((*parent_clique)->size() == size_t(parents.size())) {
if(debug) cout << "Adding to parent clique" << endl;
#ifndef NDEBUG
// Debug check that the parent keys of the new conditional match the keys
// currently in the clique.
// list<Index>::const_iterator parent = parents.begin();
// typename Clique::const_iterator cond = parent_clique->begin();
// while(parent != parents.end()) {
// assert(cond != parent_clique->end());
// assert(*parent == (*cond)->key());
// ++ parent;
// ++ cond;
// }
#endif
addToCliqueFront(bayesTree, conditional, parent_clique);
} else {
if(debug) cout << "Starting new clique" << endl;
// otherwise, start a new clique and add it to the tree
bayesTree.addClique(conditional,parent_clique);
}
}
/* ************************************************************************* */
//TODO: remove this function after removing TSAM.cpp
template<class CONDITIONAL>
typename BayesTree<CONDITIONAL>::sharedClique BayesTree<CONDITIONAL>::insert(
const sharedConditional& clique, list<sharedClique>& children, bool isRootClique) {
if (clique->nrFrontals() == 0)
throw invalid_argument("BayesTree::insert: empty clique!");
// create a new clique and add all the conditionals to the clique
sharedClique new_clique = addClique(clique, children);
if (isRootClique) root_ = new_clique;
return new_clique;
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::fillNodesIndex(const sharedClique& subtree) {
// Add each frontal variable of this root node
BOOST_FOREACH(const Index& key, subtree->conditional()->frontals()) { nodes_[key] = subtree; }
// Fill index for each child
BOOST_FOREACH(const typename BayesTree<CONDITIONAL>::sharedClique& child, subtree->children_) {
fillNodesIndex(child); }
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::insert(const sharedClique& subtree) {
if(subtree) {
// Find the parent clique of the new subtree. By the running intersection
// property, those separator variables in the subtree that are ordered
// lower than the highest frontal variable of the subtree root will all
// appear in the separator of the subtree root.
if(subtree->conditional()->parents().empty()) {
assert(!root_);
root_ = subtree;
} else {
Index parentRepresentative = findParentClique(subtree->conditional()->parents());
sharedClique parent = (*this)[parentRepresentative];
parent->children_ += subtree;
subtree->parent_ = parent; // set new parent!
}
// Now fill in the nodes index
if(nodes_.size() == 0 || (subtree->conditional()->lastFrontalKey()) > (nodes_.size() - 1)) {
nodes_.resize(subtree->conditional()->lastFrontalKey() + 1);
}
fillNodesIndex(subtree);
}
}
/* ************************************************************************* */
// First finds clique marginal then marginalizes that
/* ************************************************************************* */
template<class CONDITIONAL>
typename CONDITIONAL::FactorType::shared_ptr BayesTree<CONDITIONAL>::marginalFactor(
Index key, Eliminate function) const {
// get clique containing key
sharedClique clique = (*this)[key];
// calculate or retrieve its marginal
FactorGraph<FactorType> cliqueMarginal = clique->marginal(root_,function);
return GenericSequentialSolver<FactorType>(cliqueMarginal).marginalFactor(
key, function);
}
/* ************************************************************************* */
template<class CONDITIONAL>
typename BayesNet<CONDITIONAL>::shared_ptr BayesTree<CONDITIONAL>::marginalBayesNet(
Index key, Eliminate function) const {
// calculate marginal as a factor graph
FactorGraph<FactorType> fg;
fg.push_back(this->marginalFactor(key,function));
// eliminate factor graph marginal to a Bayes net
return GenericSequentialSolver<FactorType>(fg).eliminate(function);
}
/* ************************************************************************* */
// Find two cliques, their joint, then marginalizes
/* ************************************************************************* */
template<class CONDITIONAL>
typename FactorGraph<typename CONDITIONAL::FactorType>::shared_ptr BayesTree<
CONDITIONAL>::joint(Index key1, Index key2, Eliminate function) const {
// get clique C1 and C2
sharedClique C1 = (*this)[key1], C2 = (*this)[key2];
// calculate joint
FactorGraph<FactorType> p_C1C2(C1->joint(C2, root_, function));
// eliminate remaining factor graph to get requested joint
vector<Index> key12(2); key12[0] = key1; key12[1] = key2;
GenericSequentialSolver<FactorType> solver(p_C1C2);
return solver.jointFactorGraph(key12,function);
}
/* ************************************************************************* */
template<class CONDITIONAL>
typename BayesNet<CONDITIONAL>::shared_ptr BayesTree<CONDITIONAL>::jointBayesNet(
Index key1, Index key2, Eliminate function) const {
// eliminate factor graph marginal to a Bayes net
return GenericSequentialSolver<FactorType> (
*this->joint(key1, key2, function)).eliminate(function);
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::clear() {
// Remove all nodes and clear the root pointer
nodes_.clear();
root_.reset();
}
/* ************************************************************************* */
template<class CONDITIONAL>
void BayesTree<CONDITIONAL>::removePath(sharedClique clique,
BayesNet<CONDITIONAL>& bn, typename BayesTree<CONDITIONAL>::Cliques& orphans) {
// base case is NULL, if so we do nothing and return empties above
if (clique!=NULL) {
// remove the clique from orphans in case it has been added earlier
orphans.remove(clique);
// remove me
this->removeClique(clique);
// remove path above me
this->removePath(clique->parent_.lock(), bn, orphans);
// add children to list of orphans (splice also removed them from clique->children_)
orphans.splice (orphans.begin(), clique->children_);
bn.push_back(clique->conditional());
}
}
/* ************************************************************************* */
template<class CONDITIONAL>
template<class CONTAINER>
void BayesTree<CONDITIONAL>::removeTop(const CONTAINER& keys,
BayesNet<CONDITIONAL>& bn, typename BayesTree<CONDITIONAL>::Cliques& orphans) {
// process each key of the new factor
BOOST_FOREACH(const Index& key, keys) {
// get the clique
if(key < nodes_.size()) {
const sharedClique& clique(nodes_[key]);
if(clique) {
// remove path from clique to root
this->removePath(clique, bn, orphans);
}
}
}
}
/* ************************************************************************* */
}
/// namespace gtsam
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