code: def compute_performance(SC, verbose=True, output='dict'):
      counts = SC._counts
      tp_rate = float(counts['TP']) / counts['TOT_ST1'] * 100
      cl_rate = float(counts['CL']) / counts['TOT_ST1'] * 100
      fn_rate = float(counts['FN']) / counts['TOT_ST1'] * 100
      fp_st1 = float(counts['FP']) / counts['TOT_ST1'] * 100
      fp_st2 = float(counts['FP']) / counts['TOT_ST2'] * 100
      accuracy = tp_rate / (tp_rate + fn_rate + fp_st1) * 100
      sensitivity = tp_rate / (tp_rate + fn_rate) * 100
      miss_rate = fn_rate / (tp_rate + fn_rate) * 100
      precision = tp_rate / (tp_rate + fp_st1) * 100
      false_discovery_rate = fp_st1 / (tp_rate + fp_st1) * 100
      performance = {'tp': tp_rate, 'cl': cl_rate, 'fn': fn_rate, 'fp_st1': fp_st1, 'fp_st2': fp_st2,
                     'accuracy': accuracy, 'sensitivity': sensitivity, 'precision': precision, 'miss_rate': miss_rate,
                     'false_disc_rate': false_discovery_rate}
      if verbose:
          txt = _txt_performance.format(**performance)
          print(txt)
      if output == 'dict':
          return performance
      elif output == 'pandas':
          return pd.Series(performance)