Update gradio version

README.md

@@ -1,6 +1,6 @@
 ---
 title: npb
-app_file: demo.py
+app_file: app.py
 sdk: gradio
 sdk_version: 5.16.0
 ---

demo.py

@@ -1,147 +0,0 @@
-
-import gradio as gr
-# import pandas as pd
-import polars as pl
-
-from math import ceil
-import os
-
-from data import df, pitch_stats, league_pitch_stats, player_df
-from gradio_function import *
-from translate import jp_pitch_to_en_pitch, max_pitch_types
-
-os.makedirs('files', exist_ok=True)
-
-css = '''
-.pitch-usage {height: 256px}
-.pitch-usage .js-plotly-plot {height: 100%}
-
-.pitch-velo {height: 100px}
-.pitch-velo .js-plotly-plot {height: 100%}
-
-.pitch-loc {height: 320px}
-.pitch-loc .js-plotly-plot {height: 100%}
-
-.pitch-velo-summary div.plotly-notifier {visibility: hidden}
-'''
-
-with gr.Blocks(
-    css=css
-) as demo:
-  gr.Markdown('''
-  # NPB data visualization demo
-  [Data from SportsNavi](https://sports.yahoo.co.jp/)
-  ''')
-
-  source_df = gr.State(df)
-  app_df = gr.State(df)
-  app_league_df = gr.State(df)
-  app_pitch_stats = gr.State(pitch_stats)
-  app_league_pitch_stats = gr.State(league_pitch_stats)
-
-  with gr.Tab('Pitcher Dashboard'):
-    with gr.Row():
-      player = gr.Dropdown(value=None, choices=sorted(player_df.filter(pl.col('name').is_not_null())['name'].to_list()), label='Player')
-      handedness = gr.Radio(value='Both', choices=['Both', 'Left', 'Right'], type='value', interactive=False, label='Batter Handedness')
-
-    # preview = gr.DataFrame()
-    download_file = gr.DownloadButton(label='Download player data')
-
-    with gr.Group():
-      with gr.Row():
-        usage = gr.Plot(label='Pitch usage')
-        velo_summary = gr.Plot(label='Velocity summary', elem_classes='pitch-velo-summary')
-        loc_summary = gr.Plot(label='Overall location')
-
-    max_locs = len(jp_pitch_to_en_pitch)
-    locs_per_row = 4
-    max_rows = ceil(max_locs/locs_per_row)
-
-    gr.Markdown('''
-    ## Pitch Locations
-    Pitcher's persective
-    <br>
-    `NPB` refers to the top 10% of pitches thrown across the league with the current search constraints e.g. handedness
-    <br>
-    Note: To speed up the KDE, we restrict the league-wide pitches to 5,000 pitches
-    ''')
-    pitch_rows = []
-    pitch_groups = []
-    pitch_names = []
-    pitch_infos = []
-    pitch_velos = []
-    pitch_locs = []
-    for row in range(max_rows):
-      visible = row==0
-      pitch_row = gr.Row(visible=visible)
-      pitch_rows.append(pitch_row)
-      with pitch_row:
-        _locs_per_row = locs_per_row if row < max_rows-1 else max_locs - locs_per_row * (max_rows - 1)
-        for col in range(_locs_per_row):
-          with gr.Column(min_width=256):
-            pitch_group = gr.Group(visible=visible)
-            pitch_groups.append(pitch_group)
-            with pitch_group:
-              pitch_names.append(gr.Markdown(f'### Pitch {col+1}', visible=visible))
-              pitch_infos.append(gr.DataFrame(pl.DataFrame([{'Whiff%': None, 'CSW%': None}]), interactive=False, visible=visible))
-              pitch_velos.append(gr.Plot(show_label=False, elem_classes='pitch-velo', visible=visible))
-              pitch_locs.append(gr.Plot(label='Pitch Location', elem_classes='pitch-loc', visible=visible))
-
-    gr.Markdown('## Pitch Velocity')
-    velo_stats = gr.DataFrame(pl.DataFrame([{'Avg. Velo': None, 'League Avg. Velo': None}]), interactive=False, label='Pitch Velocity')
-
-    (
-        player
-        .input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
-        .then(lambda : gr.update(value='Both', interactive=True), outputs=handedness)
-    )
-    handedness.input(update_dfs, inputs=[player, handedness, source_df], outputs=[app_df, app_league_df, app_pitch_stats, app_league_pitch_stats])
-
-    # app_df.change(preview_df, inputs=app_df, outputs=preview)
-    # app_df.change(set_download_file, inputs=app_df, outputs=download_file)
-    # app_df.change(plot_usage, inputs=[app_df, player], outputs=usage)
-    # app_df.change(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
-    # app_df.change(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
-    # 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)
-    app_pitch_stats.change(update_velo_stats, inputs=[app_pitch_stats, app_league_pitch_stats], outputs=velo_stats)
-
-    (
-        app_df
-        .change(create_set_download_file_fn('files/player.csv'), inputs=app_df, outputs=download_file)
-        .then(plot_usage, inputs=[app_df, player], outputs=usage)
-        .then(plot_velo_summary, inputs=[app_df, app_league_df, player], outputs=velo_summary)
-        .then(lambda df: plot_loc(df), inputs=app_df, outputs=loc_summary)
-        .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)
-    )
-
-    gr.Markdown('## Bugs and other notes')
-    with gr.Accordion('Click to open', open=False):
-      gr.Markdown('''
-      - Y axis ticks messy when no velocity distribution is plotted
-      - DataFrame precision inconsistent
-      '''
-      )
-
-  with gr.Tab('Pitch Leaderboard'):
-    def filter_pitch_leaderboard(min_pitches):
-      return pitch_stats.filter(pl.col('Count') >= min_pitches).sort('CSW%', descending=True)
-
-    init_min_pitches = 100
-    pitch_stats.write_csv('pitch_leaderboard.csv')
-    pitch_leaderboard_df = gr.State(filter_pitch_leaderboard(init_min_pitches))
-
-    min_pitches = gr.Number(init_min_pitches, precision=0, label='Min. Pitches')
-    pitch_leaderboard_download_file = gr.DownloadButton(value='pitch_leaderboard.csv', label='Download leaderboard')
-    pitch_leaderboard = gr.Dataframe(value=pitch_leaderboard_df.value)
-
-    min_pitches.change(filter_pitch_leaderboard, inputs=min_pitches, outputs=pitch_leaderboard_df)
-    (
-        pitch_leaderboard_df
-        .change(create_set_download_file_fn('files/pitch_leaderboard.csv'), inputs=pitch_leaderboard_df, outputs=pitch_leaderboard_download_file)
-        .then(lambda df: df, inputs=pitch_leaderboard_df, outputs=pitch_leaderboard)
-    )
-
-demo.launch(
-    share=True,
-    debug=True
-)

pitch_leaderboard.csv

@@ -1,4 +1,4 @@
-name,pitch_name,Whiff%,CSW%,Velocity,Count
+Player,Pitch,Whiff%,CSW%,Velocity,Count
 Abe Shota,4-Seam Fastball,6.1,20.2,145.1,99
 Abe Shota,Splitter,40.6,28.6,133.7,63
 Abe Shota,Cutter,36.4,35.0,132.5,40
@@ -90,8 +90,8 @@ Corniel Robert,Cutter,0.0,0.0,143.0,1
 Diaz Yofrec,4-Seam Fastball,30.0,32.5,147.1,40
 Diaz Yofrec,Slider,42.9,14.3,133.5,21
 Diaz Yofrec,Splitter,50.0,25.0,135.0,4
-Diaz Yofrec,2-Seam Fastball,0.0,0.0,149.0,1
 Diaz Yofrec,Changeup,100.0,100.0,138.0,1
+Diaz Yofrec,2-Seam Fastball,0.0,0.0,149.0,1
 Endoh Atsushi,4-Seam Fastball,8.3,22.2,140.5,36
 Endoh Atsushi,Changeup,0.0,28.6,129.4,14
 Endoh Atsushi,Curveball,NaN,33.3,111.5,6
@@ -186,8 +186,8 @@ Hamaguchi Haruhiro,Curveball,0.0,15.4,119.2,13
 Hamaya Shota,4-Seam Fastball,0.0,38.1,140.0,21
 Hamaya Shota,2-Seam Fastball,0.0,22.2,139.6,9
 Hamaya Shota,Curveball,0.0,12.5,110.8,8
-Hamaya Shota,Changeup,66.7,66.7,121.2,6
 Hamaya Shota,Slider,100.0,33.3,123.5,6
+Hamaya Shota,Changeup,66.7,66.7,121.2,6
 Hamaya Shota,Forkball,0.0,0.0,129.8,5
 Hamaya Shota,Cutter,NaN,0.0,130.5,2
 Hara Juri,4-Seam Fastball,8.7,22.7,145.8,44
@@ -215,8 +215,8 @@ Hashimoto Yuki,4-Seam Fastball,14.5,25.5,148.2,490
 Hashimoto Yuki,Slider,30.6,34.4,131.5,320
 Hashimoto Yuki,Forkball,30.8,21.5,136.6,65
 Hatake Seishu,4-Seam Fastball,22.2,37.5,145.1,24
-Hatake Seishu,Cutter,NaN,40.0,138.0,5
 Hatake Seishu,Slider,33.3,40.0,127.0,5
+Hatake Seishu,Cutter,NaN,40.0,138.0,5
 Hatake Seishu,Forkball,50.0,33.3,136.0,3
 Hatch Thomas,4-Seam Fastball,16.7,31.6,150.7,79
 Hatch Thomas,Cutter,18.2,28.6,139.6,49
@@ -433,8 +433,8 @@ Iwashita Daiki,Slider,45.5,33.3,129.1,51
 Iwazaki Suguru,4-Seam Fastball,14.6,27.4,141.1,383
 Iwazaki Suguru,Slider,28.0,37.2,126.1,247
 Iwazaki Suguru,Changeup,21.9,24.0,128.4,171
-Iwazaki Suguru,Slow Curve,0.0,0.0,89.9,8
 Iwazaki Suguru,Cutter,16.7,12.5,132.5,8
+Iwazaki Suguru,Slow Curve,0.0,0.0,89.9,8
 Izumi Keisuke,4-Seam Fastball,10.8,23.5,148.4,294
 Izumi Keisuke,2-Seam Fastball,27.0,26.3,138.1,118
 Izumi Keisuke,Vertical Slider,30.4,39.5,117.2,76
@@ -871,10 +871,10 @@ Nabatame Tsubasa,2-Seam Fastball,7.3,14.9,149.0,101
 Nabatame Tsubasa,Slider,NaN,28.6,132.4,7
 Nakachi Reia,Curveball,33.3,50.0,115.3,4
 Nakachi Reia,4-Seam Fastball,NaN,66.7,143.0,3
+Nakachi Reia,Cutter,NaN,0.0,137.0,1
+Nakachi Reia,Changeup,100.0,100.0,122.0,1
 Nakachi Reia,Slider,NaN,0.0,122.0,1
 Nakachi Reia,2-Seam Fastball,0.0,0.0,127.0,1
-Nakachi Reia,Changeup,100.0,100.0,122.0,1
-Nakachi Reia,Cutter,NaN,0.0,137.0,1
 Nakagawa Hayate,2-Seam Fastball,9.2,27.1,130.5,299
 Nakagawa Hayate,Slider,27.4,32.2,120.9,242
 Nakagawa Hayate,4-Seam Fastball,8.2,25.0,131.8,204
@@ -965,8 +965,8 @@ Norimoto Takahiro,4-Seam Fastball,10.5,24.5,150.5,388
 Norimoto Takahiro,Forkball,36.8,27.4,139.4,226
 Norimoto Takahiro,Slider,36.0,32.0,132.5,122
 Norimoto Takahiro,Curveball,30.0,44.4,114.3,45
-Norimoto Takahiro,Cutter,20.0,15.4,142.8,13
 Norimoto Takahiro,Changeup,16.7,30.8,127.8,13
+Norimoto Takahiro,Cutter,20.0,15.4,142.8,13
 Ogasawara Shinnosuke,4-Seam Fastball,10.2,28.4,143.3,1007
 Ogasawara Shinnosuke,Knuckle Curve,18.8,27.4,112.5,343
 Ogasawara Shinnosuke,Changeup,26.8,28.4,125.6,261
@@ -1072,8 +1072,8 @@ Onaka Yuya,Forkball,NaN,0.0,134.5,2
 Ono Fumiya,4-Seam Fastball,9.1,23.3,151.9,30
 Ono Fumiya,Slider,20.0,31.6,136.0,19
 Ono Fumiya,Changeup,0.0,0.0,140.0,2
-Ono Fumiya,Curveball,NaN,100.0,126.0,1
 Ono Fumiya,Forkball,NaN,0.0,146.0,1
+Ono Fumiya,Curveball,NaN,100.0,126.0,1
 Osuna Roberto,4-Seam Fastball,20.9,23.7,152.5,186
 Osuna Roberto,Cutter,8.5,17.7,148.8,79
 Osuna Roberto,Changeup,44.7,32.4,137.4,71
@@ -1204,8 +1204,8 @@ Shimamoto Hiroya,4-Seam Fastball,8.9,22.1,142.0,149
 Shimamoto Hiroya,Slider,20.0,25.0,124.7,68
 Shimamoto Hiroya,Forkball,26.5,19.4,135.2,62
 Shimamoto Hiroya,Shootball,0.0,40.0,140.7,5
-Shimamoto Hiroya,Changeup,50.0,66.7,122.0,3
 Shimamoto Hiroya,Curveball,NaN,0.0,114.5,3
+Shimamoto Hiroya,Changeup,50.0,66.7,122.0,3
 Shimauchi Sotaro,4-Seam Fastball,19.8,25.7,152.2,487
 Shimauchi Sotaro,Changeup,38.5,36.1,130.2,302
 Shimauchi Sotaro,Forkball,40.0,30.0,139.5,10
@@ -1283,8 +1283,8 @@ Suzuki Hiroshi,Cutter,30.3,30.4,143.3,247
 Suzuki Hiroshi,2-Seam Fastball,14.2,25.8,149.7,244
 Suzuki Hiroshi,4-Seam Fastball,10.7,17.7,149.4,124
 Suzuki Hiroshi,Curveball,0.0,0.0,127.5,3
-Suzuki Hiroshi,Splitter,33.3,33.3,142.0,3
 Suzuki Hiroshi,Slider,50.0,33.3,136.0,3
+Suzuki Hiroshi,Splitter,33.3,33.3,142.0,3
 Suzuki Kenya,Slider,14.9,31.3,112.3,144
 Suzuki Kenya,4-Seam Fastball,7.1,20.5,127.1,73
 Suzuki Kenya,Sinker,12.5,7.7,125.4,39
@@ -1314,8 +1314,8 @@ Taira Kaima,2-Seam Fastball,7.7,18.2,145.7,33
 Taira Kaima,Hard Slider,45.5,23.8,139.6,21
 Taira Kaima,Curveball,50.0,50.0,114.0,14
 Taira Kentaro,4-Seam Fastball,16.7,37.9,143.6,103
-Taira Kentaro,Slider,27.1,31.3,127.3,80
 Taira Kentaro,Sinker,19.5,27.5,137.2,80
+Taira Kentaro,Slider,27.1,31.3,127.3,80
 Taira Kentaro,Cutter,21.4,27.6,138.0,29
 Tajima Daiki,4-Seam Fastball,17.2,29.1,144.7,836
 Tajima Daiki,Cutter,27.2,29.3,133.1,314
@@ -1326,8 +1326,8 @@ Tajima Daiki,Changeup,37.9,25.4,124.6,67
 Tajima Daiki,Curveball,5.3,17.2,106.6,58
 Tajima Daiki,Knuckle Curve,100.0,50.0,107.8,4
 Tajima Shinji,Shootball,0.0,33.3,140.4,6
-Tajima Shinji,Slider,50.0,16.7,128.8,6
 Tajima Shinji,Splitter,50.0,33.3,133.6,6
+Tajima Shinji,Slider,50.0,16.7,128.8,6
 Tajima Shinji,4-Seam Fastball,100.0,50.0,142.0,4
 Taka Taichi,4-Seam Fastball,28.6,44.0,146.4,25
 Taka Taichi,Cutter,0.0,25.0,130.3,4
@@ -1369,8 +1369,8 @@ Takahashi Kona,Shootball,22.2,11.8,144.6,17
 Takahashi Kona,Knuckle Curve,20.0,29.4,129.3,17
 Takahashi Kona,Curveball,NaN,0.0,122.5,2
 Takahashi Kouya,4-Seam Fastball,0.0,20.0,147.2,5
-Takahashi Kouya,Cutter,NaN,100.0,141.0,1
 Takahashi Kouya,Forkball,0.0,0.0,135.0,1
+Takahashi Kouya,Cutter,NaN,100.0,141.0,1
 Takahashi Rei,4-Seam Fastball,11.9,27.3,132.7,341
 Takahashi Rei,Slider,16.7,26.3,114.4,99
 Takahashi Rei,Sinker,32.0,21.7,114.6,46
@@ -1470,8 +1470,8 @@ Togo Shosei,4-Seam Fastball,12.9,27.4,146.8,1212
 Togo Shosei,Forkball,41.6,27.8,134.1,723
 Togo Shosei,Slider,23.5,33.2,129.9,473
 Togo Shosei,Curveball,13.9,41.0,124.1,122
-Togo Shosei,Cutter,NaN,0.0,,1
 Togo Shosei,2-Seam Fastball,0.0,0.0,145.0,1
+Togo Shosei,Cutter,NaN,0.0,,1
 Tokoda Hiroki,4-Seam Fastball,10.8,28.9,142.8,702
 Tokoda Hiroki,2-Seam Fastball,17.2,22.7,135.8,600
 Tokoda Hiroki,Cutter,18.2,32.8,135.8,564
@@ -1626,8 +1626,8 @@ Yamano Taichi,Changeup,40.0,32.4,120.6,37
 Yamaoka Taisuke,4-Seam Fastball,13.3,23.3,143.7,30
 Yamaoka Taisuke,Vertical Slider,15.4,31.0,130.7,29
 Yamaoka Taisuke,Cutter,16.7,28.6,136.6,14
-Yamaoka Taisuke,Knuckle Curve,NaN,100.0,115.5,2
 Yamaoka Taisuke,Changeup,0.0,0.0,,2
+Yamaoka Taisuke,Knuckle Curve,NaN,100.0,115.5,2
 Yamaoka Taisuke,Shootball,NaN,100.0,137.0,1
 Yamasaki Iori,4-Seam Fastball,10.9,27.9,146.4,779
 Yamasaki Iori,Cutter,31.0,33.7,134.2,433
@@ -1661,8 +1661,8 @@ Yan Jefry,4-Seam Fastball,19.1,26.8,152.7,314
 Yan Jefry,Slider,35.7,29.4,133.7,231
 Yan Jefry,Changeup,66.7,9.1,139.9,22
 Yan Jefry,2-Seam Fastball,0.0,20.0,152.3,5
-Yan Jefry,Splitter,100.0,100.0,139.0,1
 Yan Jefry,Cutter,NaN,0.0,139.0,1
+Yan Jefry,Splitter,100.0,100.0,139.0,1
 Yanagawa Taisei,4-Seam Fastball,14.7,24.3,149.7,284
 Yanagawa Taisei,Forkball,27.0,18.6,139.7,86
 Yanagawa Taisei,Cutter,28.0,25.5,136.2,51