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| import gradio as gr | |
| # import pandas as pd | |
| import polars as pl | |
| from math import ceil | |
| import os | |
| from data import player_df | |
| from gradio_function import get_data | |
| 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: 256px} | |
| .pitch-loc .js-plotly-plot {height: 100%} | |
| .pitch-velo-summary {height: 384px} | |
| .pitch-velo-summary .js-plotly-plot {height: 100%} | |
| ''' | |
| # display: flex; | |
| # align-items: center; | |
| # justify-content: center; | |
| with gr.Blocks(css=css) as demo: | |
| gr.Markdown(''' | |
| # NPB data visualization demo | |
| [Data from SportsNavi](https://sports.yahoo.co.jp/) | |
| ''') | |
| # player = gr.Dropdown(value=None, choices=sorted(player_df['name'].dropna().tolist()), label='Player') | |
| 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') | |
| player_info = gr.Markdown() | |
| download_file = gr.DownloadButton(label='Download player data') | |
| with gr.Group(): | |
| with gr.Row(): | |
| usage = gr.Plot(label='Pitch Distribution')#, elem_classes='pitch-usage') | |
| pitch_velo_summary = gr.Plot(label='Velocity Summary')#, elem_classes='pitch-velo-summary') | |
| pitch_loc_summary = gr.Plot(label='Overall Location') | |
| max_pitch_maps = len(jp_pitch_to_en_pitch) | |
| pitch_maps_per_row = 4 | |
| max_rows = ceil(max_pitch_maps/pitch_maps_per_row) | |
| gr.Markdown(''' | |
| ## Pitch Locations | |
| Pitcher's persective | |
| ''') | |
| pitch_groups = [] | |
| pitch_names = [] | |
| pitch_infos = [] | |
| pitch_velos = [] | |
| pitch_maps = [] | |
| for row in range(max_rows): | |
| with gr.Row(): | |
| _pitch_maps_per_row = pitch_maps_per_row if row < max_rows-1 else max_pitch_maps - pitch_maps_per_row * (max_rows - 1) | |
| visible = row==0 | |
| for col in range(_pitch_maps_per_row): | |
| with gr.Column(elem_classes='pitch-col', 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_maps.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') | |
| 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 | |
| ''' | |
| ) | |
| inputs = [player, handedness] | |
| outputs = [player_info, handedness, download_file, usage, pitch_velo_summary, pitch_loc_summary, *pitch_groups, *pitch_names, *pitch_infos, *pitch_velos, *pitch_maps, velo_stats] | |
| player.input(get_data, inputs=inputs, outputs=outputs) | |
| handedness.input(get_data, inputs=inputs, outputs=outputs) | |
| demo.launch( | |
| share=True, | |
| debug=True | |
| ) | |