eventcode.txt

TMVA::Reader reader
TTree tempTree

for tree in [signal_test_tree, background_test_tree]:
  output = {}
  first_entry = True
  prev_entry_event = -1
  for entry in tree:
    if not pass_preselection(entry):
      continue

    if entry.event != prev_entry_event:
      if first_entry:
        first_entry = False
      else:
        tempTree.Fill(output)
      for mva in classifiers:
        output[mva] = reader.EvaluateMVA(mva, entry)
    else:
      for mva in classifiers:
        # below min/max is taken depending which is better for the classifier in question
        output[mva] = min_or_max(output[mva], reader.EvaluateMVA(mva, entry))

    prev_entry_event = entry.event
  tempTree.Fill(output)

for entry in tempTree:
  for mva in classifiers:
    fill_classifier_output(mva, entry)
    fill_classifier_efficiency(mva, entry)

for mva in classifiers:
  normalize_classifier_efficiencies(mva)
  for bin in ROC_histogram:
    cut = find_cut_value(mva, bin)
    bkg_eff = background_efficiency(mva, cut)
    ROC_histogram.SetBinContent(bin, bkg_eff)

print_classifier_efficiencies()