ConcurrentBatchSmoother.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_unstable/nonlinear/ConcurrentFilteringAndSmoothing.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <queue>

namespace gtsam {

class GTSAM_UNSTABLE_EXPORT ConcurrentBatchSmoother : public ConcurrentSmoother {

public:
  typedef boost::shared_ptr<ConcurrentBatchSmoother> shared_ptr;
  typedef ConcurrentSmoother Base; 

  struct Result {
    size_t iterations; 
    size_t lambdas; 
    size_t nonlinearVariables; 
    size_t linearVariables; 
    double error; 

    Result() : iterations(0), lambdas(0), nonlinearVariables(0), linearVariables(0), error(0) {};

    size_t getIterations() const { return iterations; }
    size_t getLambdas() const { return lambdas; }
    size_t getNonlinearVariables() const { return nonlinearVariables; }
    size_t getLinearVariables() const { return linearVariables; }
    double getError() const { return error; }
  };

  ConcurrentBatchSmoother(const LevenbergMarquardtParams& parameters = LevenbergMarquardtParams()) : parameters_(parameters) {};

  virtual ~ConcurrentBatchSmoother() {};

  virtual void print(const std::string& s = "Concurrent Batch Smoother:\n", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;

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

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

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

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

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

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

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

  virtual Result update(const NonlinearFactorGraph& newFactors = NonlinearFactorGraph(), const Values& newTheta = Values(),
      const boost::optional< std::vector<size_t> >& removeFactorIndices = boost::none);

  virtual void presync();

  virtual void getSummarizedFactors(NonlinearFactorGraph& summarizedFactors, Values& separatorValues);

  virtual void synchronize(const NonlinearFactorGraph& smootherFactors, const Values& smootherValues,
      const NonlinearFactorGraph& summarizedFactors, const Values& separatorValues);

  virtual void postsync();

protected:

  LevenbergMarquardtParams parameters_;  
  NonlinearFactorGraph factors_;  
  Values theta_;  
  Ordering ordering_; 
  VectorValues delta_; 
  VariableIndex variableIndex_; 
  std::queue<size_t> availableSlots_; 
  Values separatorValues_; 
  std::vector<size_t> filterSummarizationSlots_;  

  // Storage for information to be sent to the filter
  NonlinearFactorGraph smootherSummarization_; 

private:

  std::vector<size_t> insertFactors(const NonlinearFactorGraph& factors);

  void removeFactors(const std::vector<size_t>& slots);

  void reorder();

  Result optimize();

  void updateSmootherSummarization();

  static void PrintNonlinearFactor(const NonlinearFactor::shared_ptr& factor,
      const std::string& indent = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter);

  static void PrintLinearFactor(const GaussianFactor::shared_ptr& factor,
      const std::string& indent = "", const KeyFormatter& keyFormatter = DefaultKeyFormatter);

}; // ConcurrentBatchSmoother

typedef ConcurrentBatchSmoother::Result ConcurrentBatchSmootherResult;

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

} //\ namespace gtsam