Spaces:
Build error
Build error
File size: 4,882 Bytes
3d0c0d1 b260f20 3a007f9 3d0c0d1 3a007f9 3d0c0d1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 |
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
from css import css
os.makedirs('files', exist_ok=True)
def create_pitcher_dashboard():
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.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
'''
)
return demo
if __name__ == '__main__':
create_pitcher_dashboard().launch(
share=True,
debug=True
)
|