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e5c3583
1
Parent(s):
024b191
Update app
Browse files- data.py +5 -0
- demo.py +95 -75
- gradio_function.py +5 -4
data.py
CHANGED
@@ -153,6 +153,10 @@ df = (
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).sort(['game_pk', 'pa_pk', 'pitch_id'])
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pitch_stats, rhb_pitch_stats, lhb_pitch_stats = [
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(
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_df
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@@ -164,6 +168,7 @@ pitch_stats, rhb_pitch_stats, lhb_pitch_stats = [
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pl.len().alias('Count')
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)
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.sort(['name', 'Count'], descending=[False, True])
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)
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for _df
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in (
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)
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).sort(['game_pk', 'pa_pk', 'pitch_id'])
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# add players to pa_df
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# unfortunately we have pas that don't show up in the pitch data, so this would be useful for
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pa_df = pa_df.join(player_df.rename({'player_id': 'pitcher'}), on='pitcher', how='inner')
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pitch_stats, rhb_pitch_stats, lhb_pitch_stats = [
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(
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_df
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pl.len().alias('Count')
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)
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.sort(['name', 'Count'], descending=[False, True])
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.rename({'name': 'Player', 'pitch_name': 'Pitch'})
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)
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for _df
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in (
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demo.py
CHANGED
@@ -39,86 +39,106 @@ with gr.Blocks(
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app_pitch_stats = gr.State(pitch_stats)
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app_league_pitch_stats = gr.State(league_pitch_stats)
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with gr.
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gr.Markdown('''
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## Pitch Locations
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Pitcher's persective
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<br>
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`NPB` refers to the top 10% of pitches thrown across the league with the current search constraints e.g. handedness
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<br>
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Note: To speed up the KDE, we restrict the league-wide pitches to 5,000 pitches
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''')
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pitch_rows = []
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pitch_groups = []
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pitch_names = []
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pitch_infos = []
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pitch_velos = []
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pitch_locs = []
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for row in range(max_rows):
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visible = row==0
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pitch_row = gr.Row(visible=visible)
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pitch_rows.append(pitch_row)
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with pitch_row:
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_locs_per_row = locs_per_row if row < max_rows-1 else max_locs - locs_per_row * (max_rows - 1)
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for col in range(_locs_per_row):
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with gr.Column(min_width=256):
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pitch_group = gr.Group(visible=visible)
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pitch_groups.append(pitch_group)
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with pitch_group:
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pitch_names.append(gr.Markdown(f'### Pitch {col+1}', visible=visible))
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pitch_infos.append(gr.DataFrame(pl.DataFrame([{'Whiff%': None, 'CSW%': None}]), interactive=False, visible=visible))
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pitch_velos.append(gr.Plot(show_label=False, elem_classes='pitch-velo', visible=visible))
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pitch_locs.append(gr.Plot(label='Pitch Location', elem_classes='pitch-loc', visible=visible))
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gr.Markdown('## Pitch Velocity')
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velo_stats = gr.DataFrame(pl.DataFrame([{'Avg. Velo': None, 'League Avg. Velo': None}]), interactive=False, label='Pitch Velocity')
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-
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(
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player
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.input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
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.then(lambda : gr.update(value='Both', interactive=True), outputs=handedness)
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)
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handedness.input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
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# app_df.change(preview_df, inputs=app_df, outputs=preview)
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# app_df.change(set_download_file, inputs=app_df, outputs=download_file)
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# app_df.change(plot_usage, inputs=[app_df, player], outputs=usage)
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# app_df.change(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
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# app_df.change(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
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# app_df.change(plot_pitch_cards, inputs=[app_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
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app_pitch_stats.change(update_velo_stats, inputs=[app_pitch_stats, app_league_pitch_stats], outputs=velo_stats)
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(
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app_df
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.change(set_download_file, inputs=app_df, outputs=download_file)
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.then(plot_usage, inputs=[app_df, player], outputs=usage)
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.then(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
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.then(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
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.then(plot_pitch_cards, inputs=[app_df, app_league_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
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)
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gr.Markdown('## Bugs and other notes')
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with gr.Accordion('Click to open', open=False):
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gr.Markdown('''
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-
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-
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)
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demo.launch(
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app_pitch_stats = gr.State(pitch_stats)
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app_league_pitch_stats = gr.State(league_pitch_stats)
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with gr.Tab('Pitcher Dashboard'):
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with gr.Row():
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player = gr.Dropdown(value=None, choices=sorted(player_df.filter(pl.col('name').is_not_null())['name'].to_list()), label='Player')
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handedness = gr.Radio(value='Both', choices=['Both', 'Left', 'Right'], type='value', interactive=False, label='Batter Handedness')
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# preview = gr.DataFrame()
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download_file = gr.DownloadButton(label='Download player data')
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with gr.Group():
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with gr.Row():
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usage = gr.Plot(label='Pitch usage')
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velo_summary = gr.Plot(label='Velocity summary', elem_classes='pitch-velo-summary')
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loc_summary = gr.Plot(label='Overall location')
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max_locs = len(jp_pitch_to_en_pitch)
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locs_per_row = 4
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max_rows = ceil(max_locs/locs_per_row)
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gr.Markdown('''
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+
## Pitch Locations
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+
Pitcher's persective
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+
<br>
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+
`NPB` refers to the top 10% of pitches thrown across the league with the current search constraints e.g. handedness
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+
<br>
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+
Note: To speed up the KDE, we restrict the league-wide pitches to 5,000 pitches
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+
''')
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pitch_rows = []
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pitch_groups = []
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pitch_names = []
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pitch_infos = []
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pitch_velos = []
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pitch_locs = []
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for row in range(max_rows):
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visible = row==0
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pitch_row = gr.Row(visible=visible)
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pitch_rows.append(pitch_row)
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with pitch_row:
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_locs_per_row = locs_per_row if row < max_rows-1 else max_locs - locs_per_row * (max_rows - 1)
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for col in range(_locs_per_row):
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with gr.Column(min_width=256):
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pitch_group = gr.Group(visible=visible)
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pitch_groups.append(pitch_group)
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with pitch_group:
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pitch_names.append(gr.Markdown(f'### Pitch {col+1}', visible=visible))
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pitch_infos.append(gr.DataFrame(pl.DataFrame([{'Whiff%': None, 'CSW%': None}]), interactive=False, visible=visible))
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pitch_velos.append(gr.Plot(show_label=False, elem_classes='pitch-velo', visible=visible))
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pitch_locs.append(gr.Plot(label='Pitch Location', elem_classes='pitch-loc', visible=visible))
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gr.Markdown('## Pitch Velocity')
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velo_stats = gr.DataFrame(pl.DataFrame([{'Avg. Velo': None, 'League Avg. Velo': None}]), interactive=False, label='Pitch Velocity')
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(
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player
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.input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
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.then(lambda : gr.update(value='Both', interactive=True), outputs=handedness)
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)
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handedness.input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
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# app_df.change(preview_df, inputs=app_df, outputs=preview)
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# app_df.change(set_download_file, inputs=app_df, outputs=download_file)
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# app_df.change(plot_usage, inputs=[app_df, player], outputs=usage)
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# app_df.change(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
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# app_df.change(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
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# app_df.change(plot_pitch_cards, inputs=[app_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
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app_pitch_stats.change(update_velo_stats, inputs=[app_pitch_stats, app_league_pitch_stats], outputs=velo_stats)
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(
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app_df
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.change(create_set_download_file_fn('files/player.csv'), inputs=app_df, outputs=download_file)
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.then(plot_usage, inputs=[app_df, player], outputs=usage)
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.then(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
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.then(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
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.then(plot_pitch_cards, inputs=[app_df, app_league_df, app_pitch_stats], outputs=pitch_rows+pitch_groups+pitch_names+pitch_infos+pitch_velos+pitch_locs)
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)
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gr.Markdown('## Bugs and other notes')
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with gr.Accordion('Click to open', open=False):
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gr.Markdown('''
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- Y axis ticks messy when no velocity distribution is plotted
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- DataFrame precision inconsistent
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'''
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)
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with gr.Tab('Pitch Leaderboard'):
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def filter_pitch_leaderboard(min_pitches):
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return pitch_stats.filter(pl.col('Count') >= min_pitches).sort('CSW%', descending=True)
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init_min_pitches = 100
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pitch_stats.write_csv('pitch_leaderboard.csv')
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pitch_leaderboard_df = gr.State(filter_pitch_leaderboard(init_min_pitches))
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min_pitches = gr.Number(init_min_pitches, precision=0, label='Min. Pitches')
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pitch_leaderboard_download_file = gr.DownloadButton(value='pitch_leaderboard.csv', label='Download leaderboard')
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pitch_leaderboard = gr.Dataframe(value=pitch_leaderboard_df.value)
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min_pitches.change(filter_pitch_leaderboard, inputs=min_pitches, outputs=pitch_leaderboard_df)
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(
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pitch_leaderboard_df
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.change(create_set_download_file_fn('files/pitch_leaderboard.csv'), inputs=pitch_leaderboard_df, outputs=pitch_leaderboard_download_file)
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.then(lambda df: df, inputs=pitch_leaderboard_df, outputs=pitch_leaderboard)
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)
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demo.launch(
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gradio_function.py
CHANGED
@@ -325,10 +325,11 @@ def update_dfs(player, handedness, df):
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final_filter = player_filter & handedness_filter
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return df.filter(final_filter), df.filter(handedness_filter), _pitch_stats.filter(player_filter), _league_pitch_stats,
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def
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def preview_df(df):
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return df.head()
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final_filter = player_filter & handedness_filter
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return df.filter(final_filter), df.filter(handedness_filter), _pitch_stats.filter(player_filter), _league_pitch_stats,
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def create_set_download_file_fn(filepath):
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def set_download_file(df):
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df.write_csv(filepath)
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return filepath
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return set_download_file
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def preview_df(df):
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return df.head()
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