gtsam/gtsam/nonlinear/NonlinearFactorGraph.h

128 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 NonlinearFactorGraph.h
* @brief Factor Graph Constsiting of non-linear factors
* @author Frank Dellaert
* @author Carlos Nieto
* @author Christian Potthast
*/
// \callgraph
#pragma once
#include <gtsam/inference/SymbolicFactorGraph.h>
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/nonlinear/NonlinearFactor.h>
namespace gtsam {
/**
* A non-linear factor graph is a graph of non-Gaussian, i.e. non-linear factors,
* which derive from NonlinearFactor. The values structures are typically (in SAM) more general
* than just vectors, e.g., Rot3 or Pose3, which are objects in non-linear manifolds.
* Linearizing the non-linear factor graph creates a linear factor graph on the
* tangent vector space at the linearization point. Because the tangent space is a true
* vector space, the config type will be an VectorValues in that linearized factor graph.
*/
class NonlinearFactorGraph: public FactorGraph<NonlinearFactor> {
public:
typedef FactorGraph<NonlinearFactor> Base;
typedef boost::shared_ptr<NonlinearFactorGraph> shared_ptr;
typedef boost::shared_ptr<NonlinearFactor> sharedFactor;
/** print just calls base class */
void print(const std::string& str = "NonlinearFactorGraph: ", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
/** return keys as an ordered set - ordering is by key value */
FastSet<Key> keys() const;
/** unnormalized error, \f$ 0.5 \sum_i (h_i(X_i)-z)^2/\sigma^2 \f$ in the most common case */
double error(const Values& c) const;
/** Unnormalized probability. O(n) */
double probPrime(const Values& c) const;
template<class F>
void add(const F& factor) {
this->push_back(boost::shared_ptr<F>(new F(factor)));
}
/**
* Create a symbolic factor graph using an existing ordering
*/
SymbolicFactorGraph::shared_ptr symbolic(const Ordering& ordering) const;
/**
* Create a symbolic factor graph and initial variable ordering that can
* be used for graph operations like determining a fill-reducing ordering.
* The graph and ordering should be permuted after such a fill-reducing
* ordering is found.
*/
std::pair<SymbolicFactorGraph::shared_ptr, Ordering::shared_ptr>
symbolic(const Values& config) const;
/**
* Compute a fill-reducing ordering using COLAMD.
*/
Ordering::shared_ptr orderingCOLAMD(const Values& config) const;
/**
* Compute a fill-reducing ordering with constraints using CCOLAMD
*
* @param constraints is a map of Key->group, where 0 is unconstrained, and higher
* group numbers are further back in the ordering. Only keys with nonzero group
* indices need to appear in the constraints, unconstrained is assumed for all
* other variables
*/
Ordering::shared_ptr orderingCOLAMDConstrained(const Values& config,
const std::map<Key, int>& constraints) const;
/**
* linearize a nonlinear factor graph
*/
boost::shared_ptr<GaussianFactorGraph >
linearize(const Values& config, const Ordering& ordering) const;
/**
* Clone() performs a deep-copy of the graph, including all of the factors
*/
NonlinearFactorGraph clone() const;
/**
* Rekey() performs a deep-copy of all of the factors, and changes
* keys according to a mapping.
*
* Keys not specified in the mapping will remain unchanged.
*
* @param rekey_mapping is a map of old->new keys
* @result a cloned graph with updated keys
*/
NonlinearFactorGraph rekey(const std::map<Key,Key>& rekey_mapping) const;
private:
/** Serialization function */
friend class boost::serialization::access;
template<class ARCHIVE>
void serialize(ARCHIVE & ar, const unsigned int version) {
ar & boost::serialization::make_nvp("NonlinearFactorGraph",
boost::serialization::base_object<Base>(*this));
}
};
} // namespace