PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData.h

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//
//
/*
    Copyright (C) 2006- 2011, Hammersmith Imanet Ltd

    SPDX-License-Identifier: Apache-2.0

    See STIR/LICENSE.txt for details
*/
#ifndef __stir_recon_buildblock_PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData_H__
#define __stir_recon_buildblock_PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData_H__

#include "stir/recon_buildblock/PoissonLogLikelihoodWithLinearModelForMeanAndProjData.h"
#include "stir/VectorWithOffset.h"
#include "stir/DynamicProjData.h"
#include "stir/DynamicDiscretisedDensity.h"

START_NAMESPACE_STIR
// ChT::ToDo: If this class appears to be useful I have to define some of the functions that are not specifically defined, yet.

template <typename TargetT>
class PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData
    : public RegisteredParsingObject<PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData<TargetT>,
                                     GeneralisedObjectiveFunction<TargetT>,
                                     PoissonLogLikelihoodWithLinearModelForMean<TargetT>>
{
private:
  typedef RegisteredParsingObject<PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData<TargetT>,
                                  GeneralisedObjectiveFunction<TargetT>,
                                  PoissonLogLikelihoodWithLinearModelForMean<TargetT>>
      base_type;
  typedef PoissonLogLikelihoodWithLinearModelForMeanAndProjData<DiscretisedDensity<3, float>> SingleFrameObjFunc;
  VectorWithOffset<SingleFrameObjFunc> _single_frame_obj_funcs;

public:
  static const char* const registered_name;
#if 0  // ChT::ToDo
  PoissonLogLikelihoodWithLinearModelForMeanAndDynamicProjData();


  virtual TargetT *
    construct_target_ptr() const; 

  virtual void 
    compute_sub_gradient_without_penalty_plus_sensitivity(TargetT& gradient, 
                                                          const TargetT &current_estimate, 
                                                          const int subset_num); 

  virtual float 
    actual_compute_objective_function_without_penalty(const TargetT& current_estimate,
                                                      const int subset_num);

  virtual Succeeded set_up_before_sensitivity(shared_ptr <TargetT> const& target_sptr);

  virtual void
    add_subset_sensitivity(TargetT& sensitivity, const int subset_num) const;

  void set_recompute_sensitivity(const bool);
  void set_sensitivity_sptr(const shared_ptr<TargetT>&);

  virtual int set_num_subsets(const int num_subsets);
#endif // ChT::ToDo
protected:
  std::string _input_filename;

  shared_ptr<DynamicProjData> _dyn_proj_data_sptr;


  int _max_segment_num_to_process;

  /**********************/
  // image stuff
  // TODO to be replaced with single class or so (TargetT obviously)

  int _output_image_size_xy; // KT 10122001 appended _xy


  int _output_image_size_z; // KT 10122001 new

  double _zoom;

  double _Xoffset;

  double _Yoffset;

  // KT 20/06/2001 new
  double _Zoffset;

  TimeFrameDefinitions _frame_defs;

  /********************************/
  std::string _additive_dyn_proj_data_filename;

  shared_ptr<DynamicProjData> _additive_dyn_proj_data_sptr;
  shared_ptr<BinNormalisation> _normalisation_sptr;
  shared_ptr<ProjectorByBinPair> _projector_pair_ptr;
  bool _zero_seg0_end_planes;

  bool actual_subsets_are_approximately_balanced(std::string& warning_message) const;


  virtual void set_defaults();
  virtual void initialise_keymap();
  virtual bool post_processing();
};

END_NAMESPACE_STIR

#endif