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gtsam/inference/BayesTree-inl.h

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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
*/
#pragma once
#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 <boost/pool/pool_alloc.hpp>
#include <fstream>
using namespace boost::assign;
namespace lam = boost::lambda;
#include <gtsam/inference/Conditional.h>
#include <gtsam/inference/BayesTree.h>
#include <gtsam/inference/inference-inl.h>
namespace gtsam {
using namespace std;
/* ************************************************************************* */
template<class Conditional>
BayesTree<Conditional>::Clique::Clique() {}
/* ************************************************************************* */
template<class Conditional>
BayesTree<Conditional>::Clique::Clique(const sharedConditional& conditional) {
separator_.assign(conditional->parents().begin(), conditional->parents().end());
this->push_back(conditional);
}
/* ************************************************************************* */
template<class Conditional>
BayesTree<Conditional>::Clique::Clique(const BayesNet<Conditional>& bayesNet)
: BayesNet<Conditional>(bayesNet) {
if(bayesNet.size() > 0) {
#ifndef NDEBUG
// Debug check that each parent variable is either a frontal variable in
// a later conditional in the Bayes net fragment, or that the parent is
// also a parent of the last conditional. This checks that the fragment
// is "enough like a clique". todo: this should really check that the
// fragment *is* a clique.
if(bayesNet.size() > 1) {
typename BayesNet<Conditional>::const_reverse_iterator cond = bayesNet.rbegin();
++ cond;
typename Conditional::shared_ptr lastConditional = *cond;
for( ; cond != bayesNet.rend(); ++cond)
for(typename Conditional::const_iterator parent=(*cond)->beginParents(); parent!=(*cond)->endParents(); ++parent) {
bool infragment = false;
typename BayesNet<Conditional>::const_reverse_iterator parentCond = cond;
do {
if(*parent == (*parentCond)->key())
infragment = true;
--parentCond;
} while(parentCond != bayesNet.rbegin());
assert(infragment || find(lastConditional->beginParents(), lastConditional->endParents(), *parent) != lastConditional->endParents());
}
}
#endif
// separator_.assign((*bayesNet.rbegin())->parents().begin(), (*bayesNet.rbegin())->parents().end());
separator_.assign((*bayesNet.rbegin())->beginParents(), (*bayesNet.rbegin())->endParents());
}
}
/* ************************************************************************* */
template<class Conditional>
vector<Index> BayesTree<Conditional>::Clique::keys() const {
vector<Index> keys;
keys.reserve(this->size() + separator_.size());
BOOST_FOREACH(const sharedConditional conditional, *this) {
keys.push_back(conditional->key());
}
keys.insert(keys.end(), separator_.begin(), separator_.end());
return keys;
}
/* ************************************************************************* */
template<class Conditional>
void BayesTree<Conditional>::Clique::print(const string& s) const {
cout << s << "Clique ";
BOOST_FOREACH(const sharedConditional& conditional, this->conditionals_) { cout << conditional->key() << " "; }
cout << "| ";
BOOST_FOREACH(const Index sep, separator_) { cout << sep << " "; }
cout << "\n";
BOOST_FOREACH(const sharedConditional& conditional, this->conditionals_) {
conditional->print(" " + s + "conditional");
// cout << " " << conditional->key();
}
// if (!separator_.empty()) {
// cout << " :";
// BOOST_FOREACH(Index key, separator_)
// cout << " " << key;
// }
// cout << endl;
}
/* ************************************************************************* */
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) {
BayesNet<Conditional>::permuteWithInverse(inversePermutation);
BOOST_FOREACH(Index& separatorKey, separator_) { separatorKey = inversePermutation[separatorKey]; }
if(cachedFactor_) cachedFactor_->permuteWithInverse(inversePermutation);
BOOST_FOREACH(const shared_ptr& child, children_) {
child->permuteWithInverse(inversePermutation);
}
}
/* ************************************************************************* */
template<class Conditional>
bool BayesTree<Conditional>::Clique::permuteSeparatorWithInverse(const Permutation& inversePermutation) {
bool changed = BayesNet<Conditional>::permuteSeparatorWithInverse(inversePermutation);
#ifndef NDEBUG
if(!changed) {
BOOST_FOREACH(Index& separatorKey, separator_) { assert(separatorKey == inversePermutation[separatorKey]); }
BOOST_FOREACH(const shared_ptr& child, children_) {
assert(child->permuteSeparatorWithInverse(inversePermutation) == false);
}
}
#endif
if(changed) {
BOOST_FOREACH(Index& separatorKey, separator_) { separatorKey = inversePermutation[separatorKey]; }
if(cachedFactor_) cachedFactor_->permuteWithInverse(inversePermutation);
BOOST_FOREACH(const shared_ptr& child, children_) {
(void)child->permuteSeparatorWithInverse(inversePermutation);
}
}
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->conditionals_.size());
data.separatorSizes.push_back(clique->separator_.size());
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
// TODO, why do we actually return a shared pointer, why does eliminate?
/* ************************************************************************* */
template<class Conditional>
template<class FactorGraph>
BayesNet<Conditional>
BayesTree<Conditional>::Clique::shortcut(shared_ptr R) {
// 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 parent clique has a Conditional for each frontal node in Fp
// so we can obtain P(Fp|Sp) in factor graph form
FactorGraph p_Fp_Sp(*parent);
// If not the base case, obtain the parent shortcut P(Sp|R) as factors
FactorGraph p_Sp_R(parent->shortcut<FactorGraph>(R));
// now combine P(Cp|R) = P(Fp|Sp) * P(Sp|R)
FactorGraph p_Cp_R = combine(p_Fp_Sp, 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.
typedef set<Index, std::less<Index>, boost::fast_pool_allocator<Index> > FastJSet;
// Get the key list Cp=Fp+Sp, which will form the basis for the integrands
vector<Index> parentKeys(parent->keys());
FastJSet integrands(parentKeys.begin(), parentKeys.end());
// Start ordering with the separator
FastJSet separator(separator_.begin(), separator_.end());
// remove any variables in the root, after this integrands = Cp\R, ordering = S\R
BOOST_FOREACH(Index key, R->ordering()) {
integrands.erase(key);
separator.erase(key);
}
// remove any variables in the separator, after this integrands = Cp\R\S
BOOST_FOREACH(Index key, separator_) integrands.erase(key);
// form the ordering as [Cp\R\S S\R]
vector<Index> ordering; ordering.reserve(integrands.size() + separator.size());
BOOST_FOREACH(Index key, integrands) ordering.push_back(key);
BOOST_FOREACH(Index key, separator) ordering.push_back(key);
// eliminate to get marginal
typename FactorGraph::variableindex_type varIndex(p_Cp_R);
Permutation toFront = Permutation::PullToFront(ordering, varIndex.size());
Permutation::shared_ptr toFrontInverse(toFront.inverse());
BOOST_FOREACH(const typename FactorGraph::sharedFactor& factor, p_Cp_R) {
factor->permuteWithInverse(*toFrontInverse);
}
varIndex.permute(toFront);
BayesNet<Conditional> p_S_R = *Inference::EliminateUntil(p_Cp_R, ordering.size(), varIndex);
// remove all integrands
for(Index j=0; j<integrands.size(); ++j)
p_S_R.pop_front();
// Undo the permutation on the shortcut
p_S_R.permuteWithInverse(toFront);
// return the parent shortcut P(Sp|R)
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>
template<class FactorGraph>
FactorGraph
BayesTree<Conditional>::Clique::marginal(shared_ptr R) {
// If we are the root, just return this root
if (R.get()==this) return *R;
// Combine P(F|S), P(S|R), and P(R)
BayesNet<Conditional> p_FSR = this->shortcut<FactorGraph>(R);
p_FSR.push_front(*this);
p_FSR.push_back(*R);
// Find marginal on the keys we are interested in
return Inference::Marginal(FactorGraph(p_FSR), keys());
}
// /* ************************************************************************* */
// // P(C1,C2) = \int_R P(F1|S1) P(S1|R) P(F2|S1) P(S2|R) P(R)
// /* ************************************************************************* */
// template<class Conditional>
// template<class Factor>
// pair<FactorGraph<Factor>, Ordering>
// BayesTree<Conditional>::Clique::joint(shared_ptr C2, shared_ptr R) {
// // For now, assume neither is the root
//
// // Combine P(F1|S1), P(S1|R), P(F2|S2), P(S2|R), and P(R)
// sharedBayesNet bn(new BayesNet<Conditional>);
// if (!isRoot()) bn->push_back(*this); // P(F1|S1)
// if (!isRoot()) bn->push_back(shortcut<Factor>(R)); // P(S1|R)
// if (!C2->isRoot()) bn->push_back(*C2); // P(F2|S2)
// if (!C2->isRoot()) bn->push_back(C2->shortcut<Factor>(R)); // P(S2|R)
// bn->push_back(*R); // P(R)
//
// // Find the keys of both C1 and C2
// Ordering keys12 = keys();
// BOOST_FOREACH(Index key,C2->keys()) keys12.push_back(key);
// keys12.unique();
//
// // Calculate the marginal
// return make_pair(marginalize<Factor,Conditional>(*bn,keys12), keys12);
// }
/* ************************************************************************* */
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));
Index key = conditional->key();
nodes_.resize(std::max(key+1, nodes_.size()));
nodes_[key] = new_clique;
if (parent_clique != NULL) {
new_clique->parent_ = parent_clique;
parent_clique->children_.push_back(new_clique);
}
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));
Index key = conditional->key();
nodes_.resize(max(key+1, nodes_.size()));
nodes_[key] = new_clique;
new_clique->children_ = child_cliques;
BOOST_FOREACH(sharedClique& child, child_cliques)
child->parent_ = new_clique;
return new_clique;
}
/* ************************************************************************* */
template<class Conditional>
inline void BayesTree<Conditional>::addToCliqueFront(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->key());
bool hasParent = false;
const Clique& cliquer(*clique);
BOOST_FOREACH(const sharedConditional& child, cliquer) {
if(child->key() == parent) {
hasParent = true;
break;
}
}
if(!hasParent)
if(find(clique->separator_.begin(), clique->separator_.end(), parent) != clique->separator_.end())
hasParent = true;
assert(hasParent);
}
#endif
if(debug) conditional->print("Adding conditional ");
if(debug) clique->print("To clique ");
Index key = conditional->key();
nodes_.resize(std::max(key+1, nodes_.size()));
nodes_[key] = clique;
clique->push_front(conditional);
if(debug) clique->print("Expanded clique is ");
}
/* ************************************************************************* */
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->separator_) {
nodes_[key].reset();
}
const Clique& cliquer(*clique);
BOOST_FOREACH(const sharedConditional& conditional, cliquer) {
nodes_[conditional->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(*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(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(const sharedConditional& conditional)
{
static const bool debug = false;
// get key and parents
typename Conditional::Parents parents = conditional->parents(); // todo: const reference?
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;
root_ = addClique(conditional);
return;
}
// otherwise, find the parent clique by using the index data structure
// to find the lowest-ordered parent
Index parentRepresentative = findParentClique(parents);
if(debug) cout << "First-eliminated parent is " << parentRepresentative << endl;
sharedClique parent_clique = (*this)[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(conditional, parent_clique);
} else {
if(debug) cout << "Starting new clique" << endl;
// otherwise, start a new clique and add it to the tree
addClique(conditional,parent_clique);
}
}
/* ************************************************************************* */
//TODO: remove this function after removing TSAM.cpp
template<class Conditional>
typename BayesTree<Conditional>::sharedClique BayesTree<Conditional>::insert(
const BayesNet<Conditional>& bayesNet, list<sharedClique>& children, bool isRootClique)
{
static const bool debug = false;
if (bayesNet.size() == 0)
throw invalid_argument("BayesTree::insert: empty bayes net!");
// 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(debug) conditional->print("Inserting conditional: ");
if (!new_clique.get())
new_clique = addClique(conditional,children);
else
addToCliqueFront(conditional, new_clique);
}
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 typename Conditional::shared_ptr& cond, *subtree) { nodes_[cond->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->separator_.empty()) {
assert(!root_);
root_ = subtree;
} else {
Index parentRepresentative = findParentClique(subtree->separator_);
sharedClique parent = (*this)[parentRepresentative];
parent->children_ += subtree;
subtree->parent_ = parent; // set new parent!
}
// Now fill in the nodes index
if(subtree->back()->key() > (nodes_.size() - 1))
nodes_.resize(subtree->back()->key() + 1);
fillNodesIndex(subtree);
}
}
/* ************************************************************************* */
// First finds clique marginal then marginalizes that
/* ************************************************************************* */
template<class Conditional>
template<class FactorGraph>
FactorGraph
BayesTree<Conditional>::marginal(Index key) const {
// get clique containing key
sharedClique clique = (*this)[key];
// calculate or retrieve its marginal
FactorGraph cliqueMarginal = clique->marginal<FactorGraph>(root_);
// Reorder so that only the requested key is not eliminated
typename FactorGraph::variableindex_type varIndex(cliqueMarginal);
vector<Index> keyAsVector(1); keyAsVector[0] = key;
Permutation toBack(Permutation::PushToBack(keyAsVector, varIndex.size()));
Permutation::shared_ptr toBackInverse(toBack.inverse());
varIndex.permute(toBack);
BOOST_FOREACH(const typename FactorGraph::sharedFactor& factor, cliqueMarginal) {
factor->permuteWithInverse(*toBackInverse);
}
// partially eliminate, remaining factor graph is requested marginal
Inference::EliminateUntil(cliqueMarginal, varIndex.size()-1, varIndex);
BOOST_FOREACH(const typename FactorGraph::sharedFactor& factor, cliqueMarginal) {
if(factor)
factor->permuteWithInverse(toBack);
}
return cliqueMarginal;
}
/* ************************************************************************* */
template<class Conditional>
template<class FactorGraph>
BayesNet<Conditional>
BayesTree<Conditional>::marginalBayesNet(Index key) const {
// calculate marginal as a factor graph
FactorGraph fg = this->marginal<FactorGraph>(key);
// eliminate further to Bayes net
return *Inference::Eliminate(fg);
}
// /* ************************************************************************* */
// // Find two cliques, their joint, then marginalizes
// /* ************************************************************************* */
// template<class Conditional>
// template<class Factor>
// FactorGraph<Factor>
// BayesTree<Conditional>::joint(Index key1, Index key2) const {
//
// // get clique C1 and C2
// sharedClique C1 = (*this)[key1], C2 = (*this)[key2];
//
// // calculate joint
// Ordering ord;
// FactorGraph<Factor> p_C1C2;
// boost::tie(p_C1C2,ord) = C1->joint<Factor>(C2,root_);
//
// // create an ordering where both requested keys are not eliminated
// ord.remove(key1);
// ord.remove(key2);
//
// // partially eliminate, remaining factor graph is requested joint
// // TODO, make eliminate functional
// eliminate<Factor,Conditional>(p_C1C2,ord);
// return p_C1C2;
// }
// /* ************************************************************************* */
// template<class Conditional>
// template<class Factor>
// BayesNet<Conditional>
// BayesTree<Conditional>::jointBayesNet(Index key1, Index key2) const {
//
// // calculate marginal as a factor graph
// FactorGraph<Factor> fg = this->joint<Factor>(key1,key2);
//
// // eliminate further to Bayes net
// Ordering ordering;
// ordering += key1, key2;
// return eliminate<Factor,Conditional>(fg,ordering);
// }
/* ************************************************************************* */
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);
}
}
/* ************************************************************************* */
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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