def write_table(metrics1: MetricsDict, metrics2: MetricsDict,
difference: MetricsDict, rel_difference: MetricsDict,
output_path: str) -> None:
# Put all of the data into tuples and sort by the relative difference
data = []
for key in rel_difference.keys():
if 'f1' in rel_difference[key]:
value1 = metrics1[key]['f1']
value2 = metrics2[key]['f1']
data.append((key, value1, value2, difference[key]['f1'],
rel_difference[key]['f1']))
data.sort(key=lambda t: -t[4])
# Prepare the lines for writing
lines = []
for category, value1, value2, diff, rel_diff in data:
lines.append(' & '.join([
category, f'{value1:.1f}', f'{value2:.1f}', f'{diff:.1f}',
f'{rel_diff:.1f}'
]) + ' \\\\')
dirname = os.path.dirname(output_path)
if dirname:
os.makedirs(dirname, exist_ok=True)
with open(output_path, 'w') as out:
out.write('\n'.join(lines))
def _combine_metrics(self, recall_metrics: MetricsDict,
precision_metrics: MetricsDict) -> MetricsDict:
combined = MetricsDict()
combined.update(recall_metrics)
combined.update(precision_metrics)
for key in combined.keys():
if 'precision' and 'recall' in combined[key]:
precision = combined[key]['precision']
recall = combined[key]['recall']
f1 = 0.0
if precision + recall != 0.0:
f1 = 2 * (precision * recall) / (precision + recall)
combined[key]['f1'] = f1
return combined