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								/* ----------------------------------------------------------------------------
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								 * GTSAM Copyright 2010, Georgia Tech Research Corporation, 
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								 * Atlanta, Georgia 30332-0415
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								 * All Rights Reserved
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								 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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								 * See LICENSE for the license information
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								 * -------------------------------------------------------------------------- */
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								/**
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								 * @file    NonlinearFactorGraph.h
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								 * @brief   Factor Graph Constsiting of non-linear factors
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								 * @author  Frank Dellaert
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								 * @author  Carlos Nieto
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								 * @author  Christian Potthast
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								 */
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								// \callgraph
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								#pragma once
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								#include <math.h>
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								#include <gtsam/nonlinear/NonlinearFactor.h>
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								#include <gtsam/linear/GaussianFactorGraph.h>
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								#include <gtsam/inference/SymbolicFactorGraph.h>
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								#include <gtsam/nonlinear/Ordering.h>
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								namespace gtsam {
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									/**
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									 * A non-linear factor graph is templated on a values structure, but the factor type
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									 * is fixed as a NonlinearFactor. The values structures are typically (in SAM) more general
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									 * than just vectors, e.g., Rot3 or Pose3, which are objects in non-linear manifolds.
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									 * Linearizing the non-linear factor graph creates a linear factor graph on the 
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									 * tangent vector space at the linearization point. Because the tangent space is a true
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									 * vector space, the config type will be an VectorValues in that linearized factor graph.
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									 */
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									template<class VALUES>
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									class NonlinearFactorGraph: public FactorGraph<NonlinearFactor<VALUES> > {
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									public:
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									  typedef FactorGraph<NonlinearFactor<VALUES> > Base;
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										typedef typename boost::shared_ptr<NonlinearFactor<VALUES> > sharedFactor;
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								    /** print just calls base class */
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								    void print(const std::string& str = "NonlinearFactorGraph: ") const;
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										/** unnormalized error */
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										double error(const VALUES& c) const;
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										/** all individual errors */
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										Vector unwhitenedError(const VALUES& c) const;
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										/** Unnormalized probability. O(n) */
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										double probPrime(const VALUES& c) const {
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											return exp(-0.5 * error(c));
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										}
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										template<class F>
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										void add(const F& factor) {
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											push_back(boost::shared_ptr<F>(new F(factor)));
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										}
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										/**
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										 * Create a symbolic factor graph using an existing ordering
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										 */
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										SymbolicFactorGraph::shared_ptr symbolic(const VALUES& config, const Ordering& ordering) const;
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										/**
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										 * Create a symbolic factor graph and initial variable ordering that can
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										 * be used for graph operations like determining a fill-reducing ordering.
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										 * The graph and ordering should be permuted after such a fill-reducing
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										 * ordering is found.
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										 */
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										std::pair<SymbolicFactorGraph::shared_ptr, Ordering::shared_ptr>
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										symbolic(const VALUES& config) const;
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								    /**
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								     * Compute a fill-reducing ordering using COLAMD.  This returns the
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								     * ordering and a VariableIndex, which can later be re-used to save
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								     * computation.
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								     */
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										Ordering::shared_ptr orderingCOLAMD(const VALUES& config) const;
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										/**
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										 * linearize a nonlinear factor graph
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										 */
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										boost::shared_ptr<GaussianFactorGraph>
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												linearize(const VALUES& config, const Ordering& ordering) const;
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									};
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								} // namespace
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