GaussianBayesNet.h

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/* ----------------------------------------------------------------------------

 * 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

 * -------------------------------------------------------------------------- */

// \callgraph

#pragma once

#include <gtsam/linear/GaussianConditional.h>
#include <gtsam/inference/FactorGraph.h>
#include <gtsam/global_includes.h>

namespace gtsam {

  class GTSAM_EXPORT GaussianBayesNet: public FactorGraph<GaussianConditional>
  {
  public:

    typedef FactorGraph<GaussianConditional> Base;
    typedef GaussianBayesNet This;
    typedef GaussianConditional ConditionalType;
    typedef boost::shared_ptr<This> shared_ptr;
    typedef boost::shared_ptr<ConditionalType> sharedConditional;


    GaussianBayesNet() {}

    template<typename ITERATOR>
    GaussianBayesNet(ITERATOR firstConditional, ITERATOR lastConditional) : Base(firstConditional, lastConditional) {}

    template<class CONTAINER>
    explicit GaussianBayesNet(const CONTAINER& conditionals) : Base(conditionals) {}

    template<class DERIVEDCONDITIONAL>
    GaussianBayesNet(const FactorGraph<DERIVEDCONDITIONAL>& graph) : Base(graph) {}



    bool equals(const This& bn, double tol = 1e-9) const;



    VectorValues optimize() const;

    VectorValues optimize(const VectorValues& solutionForMissing) const;

    Ordering ordering() const;



    std::pair<Matrix, Vector> matrix(boost::optional<const Ordering&> ordering = boost::none) const;

    VectorValues optimizeGradientSearch() const;

    VectorValues gradient(const VectorValues& x0) const;

    VectorValues gradientAtZero() const;

    double error(const VectorValues& x) const;

    double determinant() const;

    double logDeterminant() const;

    VectorValues backSubstitute(const VectorValues& gx) const;

    VectorValues backSubstituteTranspose(const VectorValues& gx) const;


  private:
    friend class boost::serialization::access;
    template<class ARCHIVE>
    void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
      ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(Base);
    }
  };

  template<>
  struct traits<GaussianBayesNet> : public Testable<GaussianBayesNet> {
  };

} //\ namespace gtsam