BatchFixedLagSmoother.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/nonlinear/FixedLagSmoother.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <queue>
 
namespace gtsam {
 
class GTSAM_EXPORT BatchFixedLagSmoother : public FixedLagSmoother {
 
public:

  typedef std::shared_ptr<BatchFixedLagSmoother> shared_ptr;

  BatchFixedLagSmoother(double smootherLag = 0.0, const LevenbergMarquardtParams& parameters = LevenbergMarquardtParams(), bool enforceConsistency = true) :
    FixedLagSmoother(smootherLag), parameters_(parameters), enforceConsistency_(enforceConsistency) {
  }

  ~BatchFixedLagSmoother() override {}

  void print(const std::string& s = "BatchFixedLagSmoother:\n", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const override;

  bool equals(const FixedLagSmoother& rhs, double tol = 1e-9) const override;

  Result update(const NonlinearFactorGraph& newFactors = NonlinearFactorGraph(),
                const Values& newTheta = Values(),
                const KeyTimestampMap& timestamps = KeyTimestampMap(),
                const FactorIndices& factorsToRemove = FactorIndices()) override;

  Values calculateEstimate() const override {
    return theta_.retract(delta_);
  }

  Values calculateEstimate(const KeyVector& keys) const override {
    return theta_.retract(delta_, keys);
  }

  template<class VALUE>
  VALUE calculateEstimate(Key key) const {
    const Vector delta = delta_.at(key);
    return traits<VALUE>::Retract(theta_.at<VALUE>(key), delta);
  }

  const LevenbergMarquardtParams& params() const {
    return parameters_;
  }

  LevenbergMarquardtParams& params() {
    return parameters_;
  }

  const NonlinearFactorGraph& getFactors() const {
    return factors_;
  }

  const Values& getLinearizationPoint() const {
    return theta_;
  }

  const Ordering& getOrdering() const {
    return ordering_;
  }

  const VectorValues& getDelta() const {
    return delta_;
  }

  Matrix marginalCovariance(Key key) const;

  static GaussianFactorGraph CalculateMarginalFactors(
      const GaussianFactorGraph& graph, const KeyVector& keys,
      const GaussianFactorGraph::Eliminate& eliminateFunction = EliminatePreferCholesky);

  static NonlinearFactorGraph CalculateMarginalFactors(
      const NonlinearFactorGraph& graph, const Values& theta, const KeyVector& keys,
      const GaussianFactorGraph::Eliminate& eliminateFunction = EliminatePreferCholesky);
 
protected:

  typedef std::map<Key, KeySet > FactorIndex;

  LevenbergMarquardtParams parameters_;

  bool enforceConsistency_;

  NonlinearFactorGraph factors_;

  Values theta_;

  Values linearValues_;

  Ordering ordering_;

  VectorValues delta_;

  std::queue<size_t> availableSlots_;

  FactorIndex factorIndex_;

  void insertFactors(const NonlinearFactorGraph& newFactors);

  void removeFactors(const std::set<size_t>& deleteFactors);

  void eraseKeys(const KeyVector& keys);

  void reorder(const KeyVector& marginalizeKeys = KeyVector());

  Result optimize();

  void marginalize(const KeyVector& marginalizableKeys);
 
private:
  static void PrintKeySet(const KeySet& keys, const std::string& label);
  static void PrintSymbolicFactor(const NonlinearFactor::shared_ptr& factor);
  static void PrintSymbolicFactor(const GaussianFactor::shared_ptr& factor);
  static void PrintSymbolicGraph(const NonlinearFactorGraph& graph, const std::string& label);
  static void PrintSymbolicGraph(const GaussianFactorGraph& graph, const std::string& label);
}; // BatchFixedLagSmoother
 
}