Marginals.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
 
 * -------------------------------------------------------------------------- */
 
#pragma once
 
#include <gtsam/linear/GaussianBayesTree.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/Values.h>
 
namespace gtsam {
 
class JointMarginal;
 
class GTSAM_EXPORT Marginals {
 
public:
 
  enum Factorization {
    CHOLESKY,
    QR
  };
 
protected:
 
  GaussianFactorGraph graph_;
  Values values_;
  Factorization factorization_;
  GaussianBayesTree bayesTree_;
 
public:
 
  Marginals(){}
 
  Marginals(const NonlinearFactorGraph& graph, const Values& solution, Factorization factorization = CHOLESKY);
 
  Marginals(const NonlinearFactorGraph& graph, const Values& solution, const Ordering& ordering,
              Factorization factorization = CHOLESKY);
 
  Marginals(const GaussianFactorGraph& graph, const Values& solution, Factorization factorization = CHOLESKY);
 
  Marginals(const GaussianFactorGraph& graph, const Values& solution, const Ordering& ordering,
              Factorization factorization = CHOLESKY);
 
  Marginals(const GaussianFactorGraph& graph, const VectorValues& solution, Factorization factorization = CHOLESKY);
 
  Marginals(const GaussianFactorGraph& graph, const VectorValues& solution, const Ordering& ordering,
              Factorization factorization = CHOLESKY);
 
  void print(const std::string& str = "Marginals: ", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
 
  GaussianFactor::shared_ptr marginalFactor(Key variable) const;
 
  Matrix marginalInformation(Key variable) const;
 
  Matrix marginalCovariance(Key variable) const;
 
  JointMarginal jointMarginalCovariance(const KeyVector& variables) const;
 
  JointMarginal jointMarginalInformation(const KeyVector& variables) const;
 
  VectorValues optimize() const;
 
protected:
  
  void computeBayesTree();
 
  void computeBayesTree(const Ordering& ordering);
};
 
class GTSAM_EXPORT JointMarginal {
 
protected:
  SymmetricBlockMatrix blockMatrix_;
  KeyVector keys_;
  FastMap<Key, size_t> indices_;
 
public:
  JointMarginal() {}
 
  Matrix operator()(Key iVariable, Key jVariable) const {
    const auto indexI = indices_.at(iVariable);
    const auto indexJ = indices_.at(jVariable);
    return blockMatrix_.block(indexI, indexJ);
  }
 
  Matrix at(Key iVariable, Key jVariable) const {
    return (*this)(iVariable, jVariable);
  }
 
  Matrix fullMatrix() const {
    return blockMatrix_.selfadjointView();
  }
 
  void print(const std::string& s = "", const KeyFormatter& formatter = DefaultKeyFormatter) const;
 
protected:
  JointMarginal(const Matrix& fullMatrix, const std::vector<size_t>& dims, const KeyVector& keys) :
    blockMatrix_(dims, fullMatrix), keys_(keys), indices_(Ordering(keys).invert()) {}
 
  friend class Marginals;
 
};
 
} /* namespace gtsam */