gtsam/gtsam/inference/GenericMultifrontalSolver-i...

108 lines
4.2 KiB
C++

/* ----------------------------------------------------------------------------
* 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 GenericMultifrontalSolver-inl.h
* @author Richard Roberts
* @date Oct 21, 2010
*/
#pragma once
#include <gtsam/inference/FactorOrdered-inl.h>
#include <gtsam/inference/JunctionTreeOrdered.h>
#include <gtsam/inference/BayesNetOrdered-inl.h>
namespace gtsam {
/* ************************************************************************* */
template<class F, class JT>
GenericMultifrontalSolver<F, JT>::GenericMultifrontalSolver(
const FactorGraphOrdered<F>& graph) :
structure_(new VariableIndexOrdered(graph)), junctionTree_(
new JT(graph, *structure_)) {
}
/* ************************************************************************* */
template<class F, class JT>
GenericMultifrontalSolver<F, JT>::GenericMultifrontalSolver(
const sharedGraph& graph,
const VariableIndexOrdered::shared_ptr& variableIndex) :
structure_(variableIndex), junctionTree_(new JT(*graph, *structure_)) {
}
/* ************************************************************************* */
template<class F, class JT>
void GenericMultifrontalSolver<F, JT>::print(const std::string& s) const {
this->structure_->print(s + " structure:\n");
this->junctionTree_->print(s + " jtree:");
}
/* ************************************************************************* */
template<class F, class JT>
bool GenericMultifrontalSolver<F, JT>::equals(
const GenericMultifrontalSolver& expected, double tol) const {
if (!this->structure_->equals(*expected.structure_, tol)) return false;
if (!this->junctionTree_->equals(*expected.junctionTree_, tol)) return false;
return true;
}
/* ************************************************************************* */
template<class F, class JT>
void GenericMultifrontalSolver<F, JT>::replaceFactors(const sharedGraph& graph) {
junctionTree_.reset(new JT(*graph, *structure_));
}
/* ************************************************************************* */
template<class FACTOR, class JUNCTIONTREE>
typename BayesTreeOrdered<typename FACTOR::ConditionalType>::shared_ptr
GenericMultifrontalSolver<FACTOR, JUNCTIONTREE>::eliminate(Eliminate function) const {
// eliminate junction tree, returns pointer to root
typename BayesTreeOrdered<typename FACTOR::ConditionalType>::sharedClique
root = junctionTree_->eliminate(function);
// create an empty Bayes tree and insert root clique
typename BayesTreeOrdered<typename FACTOR::ConditionalType>::shared_ptr
bayesTree(new BayesTreeOrdered<typename FACTOR::ConditionalType>);
bayesTree->insert(root);
// return the Bayes tree
return bayesTree;
}
/* ************************************************************************* */
template<class F, class JT>
typename FactorGraphOrdered<F>::shared_ptr GenericMultifrontalSolver<F, JT>::jointFactorGraph(
const std::vector<Index>& js, Eliminate function) const {
// FIXME: joint for arbitrary sets of variables not present
// TODO: develop and implement theory for shortcuts of more than two variables
if (js.size() != 2) throw std::domain_error(
"*MultifrontalSolver::joint(js) currently can only compute joint marginals\n"
"for exactly two variables. You can call marginal to compute the\n"
"marginal for one variable. *SequentialSolver::joint(js) can compute the\n"
"joint marginal over any number of variables, so use that if necessary.\n");
return eliminate(function)->joint(js[0], js[1], function);
}
/* ************************************************************************* */
template<class F, class JT>
typename boost::shared_ptr<F> GenericMultifrontalSolver<F, JT>::marginalFactor(
Index j, Eliminate function) const {
return eliminate(function)->marginalFactor(j, function);
}
}