| import Levenshtein | |
| import numpy as np | |
| import pandas as pd | |
| import plotly.figure_factory as ff | |
| def get_statistics(start_msg, end_msg, annotated_msg): | |
| edit_ops = Levenshtein.editops(start_msg, end_msg) | |
| n_deletes = sum([1 if op == 'delete' else 0 for op, _, _ in edit_ops]) | |
| n_inserts = sum([1 if op == 'insert' else 0 for op, _, _ in edit_ops]) | |
| n_replaces = sum([1 if op == 'replace' else 0 for op, _, _ in edit_ops]) | |
| n_changes = n_deletes + n_inserts + n_replaces | |
| n_deletes += n_replaces | |
| n_inserts += n_replaces | |
| return { | |
| "deletions": n_deletes, | |
| "insertions": n_inserts, | |
| "changes": n_changes, | |
| "deletions_norm": n_deletes / len(start_msg), | |
| "insertions_norm": n_inserts / len(end_msg), | |
| "changes_norm": n_changes / len(end_msg), | |
| } | |
| def get_statistics_for_df(df: pd.DataFrame): | |
| stats = [get_statistics(row["commit_msg_start"], row["commit_msg_end"], row["annotated_diff"]) for _, row in | |
| df.iterrows()] | |
| assert len(stats) > 0 | |
| return {stat_name: np.asarray([e[stat_name] for e in stats]) for stat_name in stats[0]} | |
| def build_plotly_chart(stat_golden, stat_e2s, stat_s2e, stat_e2s_s2e, stat_name): | |
| hist_data = [stat_golden, stat_e2s, stat_s2e, stat_e2s_s2e, | |
| np.concatenate((stat_e2s, stat_s2e, stat_e2s_s2e), axis=0)] | |
| group_labels = ['Golden', 'e2s', 's2e', 'e2s+s 2e', 'Synthetic'] | |
| fig = ff.create_distplot(hist_data, group_labels, | |
| bin_size=.1, show_rug=False, show_hist=False) | |
| fig.update_layout(title_text=stat_name) | |
| return fig | |