Petr Tsvetkov
Generate charts for the presentation & diploma;some refactoring; add (commented) Student's t-test
7ab7be2
import gradio as gr | |
import analysis_util | |
import generate_annotated_diffs | |
import dataset_statistics | |
df_manual = generate_annotated_diffs.manual_data_with_annotated_diffs() | |
df_manual["end_to_start"] = False | |
df_manual["start_to_end"] = False | |
n_diffs_manual = len(df_manual) | |
df_synthetic = generate_annotated_diffs.synthetic_data_with_annotated_diffs() | |
n_diffs_synthetic = len(df_synthetic) | |
def golden(): | |
return df_manual | |
def e2s(): | |
return df_synthetic[(df_synthetic['end_to_start'] == True) & (df_synthetic['start_to_end'] == False)] | |
def s2e(): | |
return df_synthetic[(df_synthetic['end_to_start'] == False) & (df_synthetic['start_to_end'] == True)] | |
def e2s_s2e(): | |
return df_synthetic[(df_synthetic['end_to_start'] == True) & (df_synthetic['start_to_end'] == True)] | |
def synthetic(): | |
return df_synthetic[(df_synthetic['end_to_start'] == True) | (df_synthetic['start_to_end'] == True)] | |
STATISTICS = {"manual": dataset_statistics.get_statistics_for_df(df_manual), | |
"e2s": dataset_statistics.get_statistics_for_df(e2s()), | |
"s2e": dataset_statistics.get_statistics_for_df(s2e()), | |
"e2s_s2e": dataset_statistics.get_statistics_for_df(e2s_s2e()), | |
"synthetic": dataset_statistics.get_statistics_for_df(synthetic()), | |
"all": dataset_statistics.get_statistics_for_df(df_synthetic)} | |
STATISTICS_T_TEST = dataset_statistics.t_test(STATISTICS, main_group='manual') | |
STAT_NAMES = list(STATISTICS['manual'].keys()) | |
def update_dataset_view(diff_idx, df): | |
diff_idx -= 1 | |
return (df.iloc[diff_idx]['annotated_diff'], | |
df.iloc[diff_idx]['commit_msg_start'], | |
df.iloc[diff_idx]['commit_msg_end'], | |
df.iloc[diff_idx]['session'], | |
str(df.iloc[diff_idx]['end_to_start']), | |
str(df.iloc[diff_idx]['start_to_end']), | |
f"https://github.com/{df.iloc[diff_idx]['repo']}/commit/{df.iloc[diff_idx]['hash']}",) | |
def update_dataset_view_manual(diff_idx): | |
return update_dataset_view(diff_idx, df_manual) | |
def update_dataset_view_synthetic(diff_idx): | |
return update_dataset_view(diff_idx, df_synthetic) | |
force_light_theme_js_func = """ | |
function refresh() { | |
const url = new URL(window.location); | |
if (url.searchParams.get('__theme') !== 'light') { | |
url.searchParams.set('__theme', 'light'); | |
window.location.href = url.href; | |
} | |
} | |
""" | |
if __name__ == '__main__': | |
with gr.Blocks(theme=gr.themes.Soft(), js=force_light_theme_js_func) as application: | |
def dataset_view_tab(n_items): | |
slider = gr.Slider(minimum=1, maximum=n_items, step=1, value=1, | |
label=f"Sample number (total: {n_items})") | |
diff_view = gr.Highlightedtext(combine_adjacent=True, color_map={'+': "green", '-': "red"}) | |
start_view = gr.Textbox(interactive=False, label="Start message", container=True) | |
end_view = gr.Textbox(interactive=False, label="End message", container=True) | |
session_view = gr.Textbox(interactive=False, label="Session", container=True) | |
is_end_to_start_view = gr.Textbox(interactive=False, | |
label="Is generated on the 'end-to-start' synthesis step?", | |
container=True) | |
is_start_to_end_view = gr.Textbox(interactive=False, | |
label="Is generated on the 'start-to-end' synthesis step?", | |
container=True) | |
link_view = gr.Markdown() | |
view = [ | |
diff_view, | |
start_view, | |
end_view, | |
session_view, | |
is_end_to_start_view, | |
is_start_to_end_view, | |
link_view | |
] | |
return slider, view | |
with gr.Tab("Manual"): | |
slider_manual, view_manual = dataset_view_tab(n_diffs_manual) | |
slider_manual.change(update_dataset_view_manual, inputs=slider_manual, | |
outputs=view_manual) | |
with gr.Tab("Synthetic"): | |
slider_synthetic, view_synthetic = dataset_view_tab(n_diffs_synthetic) | |
slider_synthetic.change(update_dataset_view_synthetic, inputs=slider_synthetic, | |
outputs=view_synthetic) | |
with gr.Tab("Analysis"): | |
def layout_for_statistics(statistics_group_name): | |
gr.Markdown(f"### {statistics_group_name}") | |
stats = STATISTICS[statistics_group_name] | |
gr.Number(label="Count", interactive=False, | |
value=len(stats['deletions_norm']), min_width=00) | |
gr.Number(label="Avg deletions number (rel to the initial msg length)", interactive=False, | |
value=stats['deletions_norm'].mean().item(), precision=3, min_width=00) | |
gr.Number(label="Avg insertions number (rel to the result length)", interactive=False, | |
value=stats['insertions_norm'].mean().item(), precision=3, min_width=00) | |
gr.Number(label="Avg changes number (rel to the initial msg length)", interactive=False, | |
value=stats['changes_norm'].mean().item(), precision=3, min_width=00) | |
gr.Number(label="Avg deletions number", interactive=False, | |
value=stats['deletions'].mean().item(), precision=3, min_width=00) | |
gr.Number(label="Avg insertions number", interactive=False, | |
value=stats['insertions'].mean().item(), precision=3, min_width=00) | |
gr.Number(label="Avg changes number", interactive=False, | |
value=stats['changes'].mean().item(), precision=3, min_width=00) | |
def layout_for_statistics_t_test(statistics_group_name): | |
gr.Markdown(f"### {statistics_group_name}") | |
stats = STATISTICS_T_TEST[statistics_group_name] | |
gr.Number(label="Deletions number (rel to the initial msg length)", interactive=False, | |
value=stats['deletions_norm'], precision=3, min_width=00) | |
gr.Number(label="Insertions number (rel to the result length)", interactive=False, | |
value=stats['insertions_norm'], precision=3, min_width=00) | |
gr.Number(label="Changes number (rel to the initial msg length)", interactive=False, | |
value=stats['changes_norm'], precision=3, min_width=00) | |
gr.Number(label="Deletions number", interactive=False, | |
value=stats['deletions'], precision=3, min_width=00) | |
gr.Number(label="Insertions number", interactive=False, | |
value=stats['insertions'], precision=3, min_width=00) | |
gr.Number(label="Changes number", interactive=False, | |
value=stats['changes'], precision=3, min_width=00) | |
with gr.Row(): | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("manual") | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("e2s") | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("s2e") | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("e2s_s2e") | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("synthetic") | |
with gr.Column(scale=1, min_width=100): | |
layout_for_statistics("all") | |
# gr.Markdown(f"### Student t-test (p-value)") | |
# with gr.Row(): | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("manual") | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("e2s") | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("s2e") | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("e2s_s2e") | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("synthetic") | |
# with gr.Column(scale=1, min_width=100): | |
# layout_for_statistics_t_test("all") | |
with gr.Row(): | |
with gr.Column(scale=1): | |
for stat_name in filter(lambda s: "_norm" not in s, STAT_NAMES): | |
chart = dataset_statistics.build_plotly_chart( | |
stat_golden=STATISTICS['manual'][stat_name], | |
stat_e2s=STATISTICS['e2s'][stat_name], | |
stat_s2e=STATISTICS['s2e'][stat_name], | |
stat_e2s_s2e=STATISTICS['e2s_s2e'][stat_name], | |
stat_name=stat_name | |
) | |
gr.Plot(value=chart) | |
with gr.Column(scale=1): | |
with gr.Column(scale=1): | |
for stat_name in filter(lambda s: "_norm" in s, STAT_NAMES): | |
chart = dataset_statistics.build_plotly_chart( | |
stat_golden=STATISTICS['manual'][stat_name], | |
stat_e2s=STATISTICS['e2s'][stat_name], | |
stat_s2e=STATISTICS['s2e'][stat_name], | |
stat_e2s_s2e=STATISTICS['e2s_s2e'][stat_name], | |
stat_name=stat_name | |
) | |
gr.Plot(value=chart) | |
gr.Markdown(f"### Reference-only correlations") | |
gr.Markdown(value=analysis_util.get_correlations_for_groups(df_synthetic, right_side="ind").to_markdown()) | |
gr.Markdown(f"### Aggregated correlations") | |
gr.Markdown(value=analysis_util.get_correlations_for_groups(df_synthetic, right_side="aggr").to_markdown()) | |
application.load(update_dataset_view_manual, inputs=slider_manual, | |
outputs=view_manual) | |
application.load(update_dataset_view_synthetic, inputs=slider_synthetic, | |
outputs=view_synthetic) | |
application.launch() | |