FillkNN.h

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#ifndef ANP_FILLKNN_H
#define ANP_FILLKNN_H

// $Id: FillkNN.h,v 1.11 2009/02/17 19:15:40 rustem Exp $
//
// FillkNN algorithm fills muon track probability using
// k-nearest neighbors method. The algorithm does two tasks:
//    1) creates prototype files storing events
//    2) finds k-nearest neighbors for signal and background
//       reconstructed tracks and/or events using prototype file.
//
// This algorithm depends on FillMuonId algorithm, which fills
// input variables.
//

// C++
#include <map>
#include <iostream>
#include <string>
#include <vector>

// Local
#include "PhysicsNtuple/AlgEvent.h"
#include "PhysicsNtuple/AlgSnarl.h"

// Local
#include "Node.h"

class TFile;

namespace Lit
{
   class LikeModule;
}

namespace Anp
{
   class FillkNN : public AlgSnarl, public AlgEvent
   {
   public:
      
      FillkNN();
      virtual ~FillkNN();

      bool Run(Record &record);

      bool Run(Event &event, const Record& record, bool pass);
      
      void Config(const Registry &reg);

      bool Init(const Header &);

      void End(const DataBlock &);

   private:

      typedef std::vector<short> ShortVec;
      typedef std::map<short, int> ShortMap;

   private:

      bool Fill(DataIter beg, DataIter end, double weight);

      const DataVec Find(DataIter beg, DataIter end, short keybase) const;

      double PidKer(Lit::List::const_iterator beg, Lit::List::const_iterator end) const;

      const std::vector<float> Get(DataIter beg, DataIter end, const ShortVec &kvec) const;

      double Kernel(const double value) const;

   private:

      mutable unsigned int fNAbortFind; // # of aborted knn searches: knn value already exists
      unsigned int fNTrackMiss;         // # of tracks with not enough data to filled knn
      unsigned int fNTrackFill;         // # of tracks with correctly filled knn
      unsigned int fNEventMiss;         // # of events with not enough data to filled knn
      unsigned int fNEventFill;         // # of events with correctly filled knn

      std::string fDirName;
      std::string fFilePath;

      int fMaxNEvent;   // maximum number of events read from knn protype file
      int fKeyBase;     // key base for knn pid = base + type(optional) + knn
      int fKeySignal;   // when type is option, then this gives type of signal events
      int fKeyTruth;    // key where true type is stored
      int fTrimDelta;   // do not fill events that exceed min # of events by fTrimDelta

      unsigned int fKNeighbor;    // k-nearest neighbors
      unsigned int fKNeighborMod; // report pid for knn = count % fKNeighborMod 

      bool fAddAll;     // add all signal types?
      bool fAddEvent;   // when running as AlgSnarl && fUseTrack=true, add keys to event?
      bool fCreateNew;  // create new knn prototype?
      bool fPrint;      // print knn list?
      bool fRegression; // run regression analysis
      bool fTrim;       // use equal number of events of each type?
      bool fUseKernel;  // use kernel?
      bool fUseTrack;   // get input variables from track data vector?

      Lit::LikeModule *fModule;

      ShortVec fKeys;
      ShortVec fTgts;
      ShortVec fTypes;
      ShortMap fCount;
   };
}

#endif

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