PndMvaTrainer.h

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/* **********************************************
 * MVA classifiers trainers interface.          *
 * Author: M. Babai                             *
 * M.Babai@rug.nl                               *
 * Version: 0.1 beta1.                          *
 * LICENSE:                                     *
 * **********************************************
 */
//#pragma once
#ifndef PND_MVA_TRAINER_H
#define PND_MVA_TRAINER_H

// C++ includes
#include <cassert>
#include <limits>
#include <ctime>
#include <iomanip>
#include <cstdlib>

// ROOT and PandaRoot
#include "TMVA/Tools.h"
#include "TMVA/PDEFoam.h"
#include "TMVA/Event.h"

class TRandom3;

// Local includes
#include "PndMvaDataSet.h"
#include "PndMvaUtil.h"

#define TRAIN_INC_FOAM 0

class PndMvaTrainer {
  //==============================================
  //================ Public =======================
 public:
  explicit PndMvaTrainer(std::vector<std::pair<std::string, std::vector<float> *>> const &InputEvtsParam, std::vector<std::string> const &ClassNames,
                         std::vector<std::string> const &VarNames, bool trim = true);

  explicit PndMvaTrainer(std::string const &InPut, std::vector<std::string> const &ClassNames, std::vector<std::string> const &VarNames, bool trim = true);

  virtual ~PndMvaTrainer();

  virtual void Train() = 0;

  virtual void storeWeights() = 0;

  void SetTestSetSize(size_t percent = 50);

  void SetTestSet(std::set<size_t> const &testSet);

  void NormalizeData(NormType t = NONORM);

  void PCATransForm();

  inline void SetOutPutFile(std::string const &outFile);

  void WriteErroVect(std::string const &FileName) const;

  inline std::vector<StepError> const &GetErrorValues() const;

  virtual void Initialize();

  inline std::set<size_t> const &GetTestEvetIdx() const;

  inline std::vector<PndMvaClass> const &GetClasses() const;

  inline std::vector<PndMvaVariable> const &GetVariables() const;

  virtual void EvalClassifierError();

  inline size_t GetRndSeed() const;
  inline void SetRndSeed(size_t const sd);

  //______________________________________________
  //================ Protected ===================
 protected:
  inline void SetAppType(AppType t);

  void WriteToWeightFile(std::vector<std::pair<std::string, std::vector<float> *>> const &weights) const;

#if (TRAIN_INC_FOAM > 0)

  void WriteToWeightFile(std::vector<TMVA::PDEFoam *> const &foams) const;
#endif
  // void WriteDataSetToOutFile();

  std::set<size_t> m_testSet_indices;

  PndMvaDataSet m_dataSets;

  std::vector<StepError> m_StepErro;

  std::string m_outFile;

  size_t m_RND_seed;

  void splitTetsSet();
  //______________________________________________
  //================ Private =====================
 private:
  PndMvaTrainer(PndMvaTrainer const &other);
  PndMvaTrainer &operator=(PndMvaTrainer const &other);

  // trim or not
  bool m_trim;
  size_t m_testSetSize;
}; // End of class definition.

//========================= Inline implementations =================
inline size_t PndMvaTrainer::GetRndSeed() const
{
  return this->m_RND_seed;
};

inline void PndMvaTrainer::SetRndSeed(size_t const sd)
{
  this->m_RND_seed = sd;
};

inline void PndMvaTrainer::SetOutPutFile(std::string const &outFile)
{
  m_outFile = outFile;
};

inline void PndMvaTrainer::SetAppType(AppType t)
{
  m_dataSets.SetAppType(t);
};

inline std::set<size_t> const &PndMvaTrainer::GetTestEvetIdx() const
{
  return m_testSet_indices;
};

inline std::vector<PndMvaClass> const &PndMvaTrainer::GetClasses() const
{
  return m_dataSets.GetClasses();
};

inline std::vector<PndMvaVariable> const &PndMvaTrainer::GetVariables() const
{
  return m_dataSets.GetVars();
};

// @return  List of evaluation objects.
inline std::vector<StepError> const &PndMvaTrainer::GetErrorValues() const
{
  return m_StepErro;
};
#endif