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Discrete variables

// Discrete variables
intro5()
{
  // Define a category with explicitly numbered states
  RooCategory b0flav("b0flav","B0 flavour eigenstate") ;
  b0flav.defineType("B0",-1) ;
  b0flav.defineType("B0bar",1) ;
  b0flav.Print("s") ;

  // Define a category with labels only
  RooCategory tagCat("tagCat","Tagging category") ;
  tagCat.defineType("Lepton") ;
  tagCat.defineType("Kaon") ;
  tagCat.defineType("NetTagger-1") ;
  tagCat.defineType("NetTagger-2") ;
  tagCat.Print("s") ;

  // Define a dummy PDF in x 
  RooRealVar x("x","x",0,10) ;
  RooArgusBG a("a","argus(x)",x,RooRealConstant::value(10),RooRealConstant::value(-1)) ;

  // Generate a dummy dataset 
  RooDataSet *data = a.generate(RooArgSet(x,b0flav,tagCat),10000) ;

  // Tables are equivalent of plots for categories
  RooTable* btable = data->table(b0flav) ;
  btable->Print() ;
  RooTable* ttable = data->table(tagCat,"x>8.23") ;
  ttable->Print() ;

  // Super-category is 'product' of categories
  RooSuperCategory b0Xtcat("b0Xtcat","b0flav X tagCat",RooArgSet(b0flav,tagCat)) ;
  RooTable* bttable = data->table(b0Xtcat) ;
  bttable->Print() ;

  // Mapped category is category->category function
  RooMappedCategory tcatType("tcatType","tagCat type",tagCat,"Unknown") ;
  tcatType.map("Lepton","Cut based") ;
  tcatType.map("Kaon","Cut based") ;
  tcatType.map("NetTagger*","Neural Network") ;
  (data->table(tcatType))->Print() ;

  // Threshold category is real->category function
  RooThresholdCategory xRegion("xRegion","region of x",x,"Background") ;
  xRegion.addThreshold(4.23,"Background") ;
  xRegion.addThreshold(5.23,"SideBand") ;
  xRegion.addThreshold(8.23,"Signal") ;
  xRegion.addThreshold(9.23,"SideBand") ; 
  //
  // Background | SideBand | Signal | SideBand | Background
  //           4.23       5.23     8.23       9.23 
  data->addColumn(xRegion) ;
  RooPlot* xframe = x.frame() ;
  data->plotOn(xframe) ;
  data->plotOn(xframe,Cut("xRegion==xRegion::SideBand"),MarkerColor(2),MarkerSize(2)) ;
  xframe->Draw() ;

}

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