gtsam/gtsam/nonlinear/GaussianISAM2.h

67 lines
2.5 KiB
C++

/**
* @file GaussianISAM
* @brief Full non-linear ISAM.
* @author Michael Kaess
*/
// \callgraph
#pragma once
#include <gtsam/linear/GaussianConditional.h>
#include <gtsam/nonlinear/ISAM2.h>
namespace gtsam {
/**
* @ingroup ISAM2
* @brief The main ISAM2 class that is exposed to gtsam users, see ISAM2 for usage.
*
* This is a thin wrapper around an ISAM2 class templated on
* GaussianConditional, and the values on which that GaussianISAM2 is
* templated.
*
* @tparam VALUES The Values or TupleValues\Emph{N} that contains the
* variables.
* @tparam GRAPH The NonlinearFactorGraph structure to store factors. Defaults to standard NonlinearFactorGraph<VALUES>
*/
template <class VALUES, class GRAPH = NonlinearFactorGraph<VALUES> >
class GaussianISAM2 : public ISAM2<GaussianConditional, VALUES, GRAPH> {
typedef ISAM2<GaussianConditional, VALUES, GRAPH> Base;
public:
/** Create an empty ISAM2 instance */
GaussianISAM2(const ISAM2Params& params) : ISAM2<GaussianConditional, VALUES, GRAPH>(params) {}
/** Create an empty ISAM2 instance using the default set of parameters (see ISAM2Params) */
GaussianISAM2() : ISAM2<GaussianConditional, VALUES, GRAPH>() {}
void cloneTo(boost::shared_ptr<GaussianISAM2>& newGaussianISAM2) const {
boost::shared_ptr<Base> isam2 = boost::static_pointer_cast<Base>(newGaussianISAM2);
Base::cloneTo(isam2);
}
};
// optimize the BayesTree, starting from the root
template<class CLIQUE>
void optimize2(const boost::shared_ptr<CLIQUE>& root, VectorValues& delta);
// optimize the BayesTree, starting from the root; "replaced" needs to contain
// all variables that are contained in the top of the Bayes tree that has been
// redone; "delta" is the current solution, an offset from the linearization
// point; "threshold" is the maximum change against the PREVIOUS delta for
// non-replaced variables that can be ignored, ie. the old delta entry is kept
// and recursive backsubstitution might eventually stop if none of the changed
// variables are contained in the subtree.
// returns the number of variables that were solved for
template<class CLIQUE>
int optimize2(const boost::shared_ptr<CLIQUE>& root,
double threshold, const std::vector<bool>& replaced, Permuted<VectorValues>& delta);
// calculate the number of non-zero entries for the tree starting at clique (use root for complete matrix)
template<class CLIQUE>
int calculate_nnz(const boost::shared_ptr<CLIQUE>& clique);
}/// namespace gtsam
#include <gtsam/nonlinear/GaussianISAM2-inl.h>