gtsam/gtsam/linear/GaussianISAM.cpp

104 lines
3.8 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 GaussianISAM
* @brief Linear ISAM only
* @author Michael Kaess
*/
#include <gtsam/3rdparty/Eigen/Eigen/Dense>
#include <gtsam/linear/GaussianISAM.h>
#include <gtsam/inference/ISAM-inl.h>
using namespace std;
using namespace gtsam;
namespace gtsam {
// Explicitly instantiate so we don't have to include everywhere
template class ISAM<GaussianConditional>;
/* ************************************************************************* */
GaussianFactor::shared_ptr GaussianISAM::marginalFactor(Index j) const {
return Super::marginalFactor(j, &EliminateQR);
}
/* ************************************************************************* */
BayesNet<GaussianConditional>::shared_ptr GaussianISAM::marginalBayesNet(Index j) const {
return Super::marginalBayesNet(j, &EliminateQR);
}
/* ************************************************************************* */
Matrix GaussianISAM::marginalCovariance(Index j) const {
GaussianConditional::shared_ptr conditional = marginalBayesNet(j)->front();
return conditional->computeInformation().inverse();
}
/* ************************************************************************* */
BayesNet<GaussianConditional>::shared_ptr GaussianISAM::jointBayesNet(
Index key1, Index key2) const {
return Super::jointBayesNet(key1, key2, &EliminateQR);
}
/* ************************************************************************* */
void optimize(const BayesTree<GaussianConditional>::sharedClique& clique, VectorValues& result) {
// parents are assumed to already be solved and available in result
// RHS for current conditional should already be in place in result
clique->conditional()->solveInPlace(result);
BOOST_FOREACH(const BayesTree<GaussianConditional>::sharedClique& child, clique->children_)
optimize(child, result);
}
/* ************************************************************************* */
void treeRHS(const BayesTree<GaussianConditional>::sharedClique& clique, VectorValues& result) {
clique->conditional()->rhs(result);
BOOST_FOREACH(const BayesTree<GaussianConditional>::sharedClique& child, clique->children_)
treeRHS(child, result);
}
/* ************************************************************************* */
VectorValues rhs(const BayesTree<GaussianConditional>& bayesTree, boost::optional<const GaussianISAM::Dims&> dims) {
VectorValues result;
if(dims)
result = VectorValues(*dims);
else
result = *allocateVectorValues(bayesTree); // allocate
treeRHS(bayesTree.root(), result); // recursively fill
return result;
}
/* ************************************************************************* */
VectorValues optimize(const GaussianISAM& isam) {
VectorValues result = rhs(isam, isam.dims_);
// starting from the root, call optimize on each conditional
optimize(isam.root(), result);
return result;
}
/* ************************************************************************* */
VectorValues optimize(const BayesTree<GaussianConditional>& bayesTree) {
VectorValues result = rhs(bayesTree);
// starting from the root, call optimize on each conditional
optimize(bayesTree.root(), result);
return result;
}
/* ************************************************************************* */
BayesNet<GaussianConditional> GaussianISAM::shortcut(sharedClique clique, sharedClique root) {
return clique->shortcut(root,&EliminateQR);
}
/* ************************************************************************* */
} // \namespace gtsam