run_pipeline_lib.py 文件源码

def calculate_stats(stats):
  """Calculate derived stats and put them into the given results_pb2.Stats."""
  stats.error_message = ''
  if stats.true_positives + stats.false_positives:
    stats.precision = (float(stats.true_positives) /
                       (stats.true_positives + stats.false_positives))
  else:
    stats.precision = float('NaN')
    stats.error_message += 'Precision has denominator of zero. '

  if stats.true_positives + stats.false_negatives:
    stats.recall = (float(stats.true_positives) /
                    (stats.true_positives + stats.false_negatives))
  else:
    stats.recall = float('NaN')
    stats.error_message += 'Recall has denominator of zero. '

  stats.f_score = hmean(stats.precision, stats.recall)
  if math.isnan(stats.f_score):
    stats.error_message += 'f-score is NaN'

  return stats