/* ***************************************
 * Author: M.Babai@rug.nl                *
 * ***************************************
 */
/*
 * Example program. This code shows how to use the train procedure, in
 * order to generate weight file to be used by the KNN based
 * classifier.
 */
#include "PndKnnTrain.h"

#include "TRandom3.h"

int main(int argc, char** argv)
{
  if(argc < 3)
  {
    std::cerr << "\t<ERROR> Usage\n"
	      <<"\t./train <InFile> <OutFile>"
	      << std::endl;
    return 1;
  }
  
  std::string inpt   = argv[1];
  std::string oupt   = argv[2];
  
  std::vector<std::string> clas;
  std::vector<std::string> nam;
  
  // Class Names  
  clas.push_back("electron");
  clas.push_back("pion"); 
  //clas.push_back("kaon");
  //clas.push_back("muon");
  //clas.push_back("proton");
  
  // Parameter Names
  nam.push_back("emc");
  nam.push_back("lat");
  nam.push_back("z20");
  nam.push_back("z53");
  
  const char* file = inpt.c_str();
  
  // Create classifier object.
  PndKnnTrain kNNtr (file, clas, nam, true);
  
  //NormType tt = VARX;
  //kNNtr.NormalizeData(VARX);
  //kNNtr.NormalizeData(MINMAX);
  //kNNtr.NormalizeData(MEDIAN);

  // Transform using PCA
  //kNNtr.PCATransForm();
  
  //Set output file name
  kNNtr.SetOutPutFile(oupt);

  //Init and set data structures
  kNNtr.Initialize();

  // Perform training
  kNNtr.Train();

  return 0;
}