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| import polars as pl | |
| import numpy as np | |
| import pandas as pd | |
| import api_scraper | |
| scrape = api_scraper.MLB_Scrape() | |
| from functions import df_update | |
| from functions import pitch_summary_functions | |
| update = df_update.df_update() | |
| from stuff_model import feature_engineering as fe | |
| from stuff_model import stuff_apply | |
| import requests | |
| import joblib | |
| from matplotlib.gridspec import GridSpec | |
| from shiny import App, reactive, ui, render | |
| from shiny.ui import h2, tags | |
| import matplotlib.pyplot as plt | |
| import matplotlib.gridspec as gridspec | |
| import seaborn as sns | |
| from functions.pitch_summary_functions import * | |
| from shiny import App, reactive, ui, render | |
| from shiny.ui import h2, tags | |
| colour_palette = ['#FFB000','#648FFF','#785EF0', | |
| '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED'] | |
| year_list = [2017,2018,2019,2020,2021,2022,2023,2024] | |
| level_dict = {'1':'MLB', | |
| '11':'AAA', | |
| '12':'AA', | |
| '13':'A+', | |
| '14':'A', | |
| '17':'AFL', | |
| '22':'College', | |
| '21':'Prospects', | |
| '51':'International' } | |
| function_dict={ | |
| 'velocity_kdes':'Velocity Distributions', | |
| 'break_plot':'Pitch Movement', | |
| 'tj_stuff_roling':'Rolling tjStuff+ by Pitch', | |
| 'tj_stuff_roling_game':'Rolling tjStuff+ by Game', | |
| 'location_plot_lhb':'Locations vs LHB', | |
| 'location_plot_rhb':'Locations vs RHB', | |
| } | |
| split_dict = {'all':'All', | |
| 'left':'LHH', | |
| 'right':'RHH'} | |
| split_dict_hand = {'all':['L','R'], | |
| 'left':['L'], | |
| 'right':['R']} | |
| type_dict = {'R':'Regular Season', | |
| 'S':'Spring', | |
| 'P':'Playoffs' } | |
| from shiny import App, reactive, ui, render | |
| from shiny.ui import h2, tags | |
| # Define the UI layout for the app | |
| app_ui = ui.page_fluid( | |
| ui.layout_sidebar( | |
| ui.panel_sidebar( | |
| # Row for selecting season and level | |
| ui.row( | |
| ui.column(4, ui.input_select('year_input', 'Select Season', year_list, selected=2024)), | |
| ui.column(4, ui.input_select('level_input', 'Select Level', level_dict)), | |
| ui.column(4, ui.input_select('type_input', 'Select Type', type_dict,selected='R')) | |
| ), | |
| # Row for the action button to get player list | |
| ui.row(ui.input_action_button("player_button", "Get Player List", class_="btn-primary")), | |
| # Row for selecting the player | |
| ui.row(ui.column(12, ui.output_ui('player_select_ui', 'Select Player'))), | |
| # Row for selecting the date range | |
| ui.row(ui.column(12, ui.output_ui('date_id', 'Select Date'))), | |
| # Rows for selecting plots and split options | |
| ui.row( | |
| ui.column(4, ui.input_select('plot_id_1', 'Plot Left', function_dict, multiple=False, selected='velocity_kdes')), | |
| ui.column(4, ui.input_select('plot_id_2', 'Plot Middle', function_dict, multiple=False, selected='tj_stuff_roling')), | |
| ui.column(4, ui.input_select('plot_id_3', 'Plot Right', function_dict, multiple=False, selected='break_plot')) | |
| ), | |
| ui.row( | |
| ui.column(6, ui.input_select('split_id', 'Select Split', split_dict, multiple=False)), | |
| ui.column(6, ui.input_numeric('rolling_window', 'Rolling Window (for tjStuff+ Plot)', min=1, value=50)) | |
| ), | |
| # Row for the action button to generate plot | |
| ui.row(ui.input_action_button("generate_plot", "Generate Plot", class_="btn-primary")), | |
| ), | |
| ui.panel_main( | |
| ui.navset_tab( | |
| # Tab for game summary plot | |
| ui.nav("Pitching Summary", | |
| ui.output_text("status"), | |
| ui.output_plot('plot', width='2100px', height='2100px') | |
| ), | |
| ) | |
| ) | |
| ) | |
| ) | |
| def server(input, output, session): | |
| def cached_data(): | |
| year_input = int(input.year_input()) | |
| sport_id = int(input.level_input()) | |
| player_input = int(input.pitcher_id()) | |
| start_date = str(input.date_id()[0]) | |
| end_date = str(input.date_id()[1]) | |
| # Simulate an expensive data operation | |
| game_list = scrape.get_player_games_list(sport_id = sport_id, | |
| season = year_input, | |
| player_id = player_input, | |
| start_date = start_date, | |
| end_date = end_date, | |
| game_type = [input.type_input()]) | |
| data_list = scrape.get_data(game_list_input = game_list[:]) | |
| df = (stuff_apply.stuff_apply(fe.feature_engineering(update.update(scrape.get_data_df(data_list = data_list).filter( | |
| (pl.col("pitcher_id") == player_input)& | |
| (pl.col("is_pitch") == True)& | |
| (pl.col('batter_hand').is_in(split_dict_hand[input.split_id()])) | |
| )))).with_columns( | |
| pl.col('pitch_type').count().over('pitch_type').alias('pitch_count') | |
| )) | |
| return df | |
| def player_select_ui(): | |
| # Get the list of pitchers for the selected level and season | |
| df_pitcher_info = scrape.get_players(sport_id=int(input.level_input()), season=int(input.year_input()), game_type = [input.type_input()]).filter( | |
| pl.col("position").is_in(['P','TWP'])).sort("name") | |
| # Create a dictionary of pitcher IDs and names | |
| pitcher_dict = dict(zip(df_pitcher_info['player_id'], df_pitcher_info['name'])) | |
| # Return a select input for choosing a pitcher | |
| return ui.input_select("pitcher_id", "Select Pitcher", pitcher_dict, selectize=True) | |
| def date_id(): | |
| # Create a date range input for selecting the date range within the selected year | |
| return ui.input_date_range("date_id", "Select Date Range", | |
| start=f"{int(input.year_input())}-01-01", | |
| end=f"{int(input.year_input())}-12-31", | |
| min=f"{int(input.year_input())}-01-01", | |
| max=f"{int(input.year_input())}-12-31") | |
| def status(): | |
| # Only show status when generating | |
| if input.generate == 0: | |
| return "" | |
| return "" | |
| def plot(): | |
| # Show progress/loading notification | |
| with ui.Progress(min=0, max=1) as p: | |
| p.set(message="Generating plot", detail="This may take a while...") | |
| p.set(0.3, "Gathering data...") | |
| year_input = int(input.year_input()) | |
| sport_id = int(input.level_input()) | |
| player_input = int(input.pitcher_id()) | |
| start_date = str(input.date_id()[0]) | |
| end_date = str(input.date_id()[1]) | |
| print(year_input, sport_id, player_input, start_date, end_date) | |
| df = cached_data() | |
| df = df.clone() | |
| p.set(0.6, "Creating plot...") | |
| #plt.rcParams["figure.figsize"] = [10,10] | |
| fig = plt.figure(figsize=(26,26)) | |
| plt.rcParams.update({'figure.autolayout': True}) | |
| fig.set_facecolor('white') | |
| sns.set_theme(style="whitegrid", palette=colour_palette) | |
| print('this is the one plot') | |
| gs = gridspec.GridSpec(6, 8, | |
| height_ratios=[5,20,12,36,36,7], | |
| width_ratios=[4,18,18,18,18,18,18,4]) | |
| gs.update(hspace=0.2, wspace=0.5) | |
| # Define the positions of each subplot in the grid | |
| ax_headshot = fig.add_subplot(gs[1,1:3]) | |
| ax_bio = fig.add_subplot(gs[1,3:5]) | |
| ax_logo = fig.add_subplot(gs[1,5:7]) | |
| ax_season_table = fig.add_subplot(gs[2,1:7]) | |
| ax_plot_1 = fig.add_subplot(gs[3,1:3]) | |
| ax_plot_2 = fig.add_subplot(gs[3,3:5]) | |
| ax_plot_3 = fig.add_subplot(gs[3,5:7]) | |
| ax_table = fig.add_subplot(gs[4,1:7]) | |
| ax_footer = fig.add_subplot(gs[-1,1:7]) | |
| ax_header = fig.add_subplot(gs[0,1:7]) | |
| ax_left = fig.add_subplot(gs[:,0]) | |
| ax_right = fig.add_subplot(gs[:,-1]) | |
| # Hide axes for footer, header, left, and right | |
| ax_footer.axis('off') | |
| ax_header.axis('off') | |
| ax_left.axis('off') | |
| ax_right.axis('off') | |
| sns.set_theme(style="whitegrid", palette=colour_palette) | |
| fig.set_facecolor('white') | |
| df_teams = scrape.get_teams() | |
| player_headshot(player_input=player_input, ax=ax_headshot,sport_id=sport_id,season=year_input) | |
| player_bio(pitcher_id=player_input, ax=ax_bio,sport_id=sport_id,year_input=year_input) | |
| plot_logo(pitcher_id=player_input, ax=ax_logo, df_team=df_teams,df_players=scrape.get_players(sport_id,year_input)) | |
| stat_summary_table(df=df, | |
| ax=ax_season_table, | |
| player_input=player_input, | |
| split=input.split_id(), | |
| sport_id=sport_id, | |
| game_type=[input.type_input()]) | |
| # break_plot(df=df_plot,ax=ax2) | |
| for x,y,z in zip([input.plot_id_1(),input.plot_id_2(),input.plot_id_3()],[ax_plot_1,ax_plot_2,ax_plot_3],[1,3,5]): | |
| if x == 'velocity_kdes': | |
| velocity_kdes(df, | |
| ax=y, | |
| gs=gs, | |
| gs_x=[3,4], | |
| gs_y=[z,z+2], | |
| fig=fig) | |
| if x == 'tj_stuff_roling': | |
| tj_stuff_roling(df=df, | |
| window=int(input.rolling_window()), | |
| ax=y) | |
| if x == 'tj_stuff_roling_game': | |
| tj_stuff_roling_game(df=df, | |
| window=int(input.rolling_window()), | |
| ax=y) | |
| if x == 'break_plot': | |
| break_plot(df = df,ax=y) | |
| if x == 'location_plot_lhb': | |
| location_plot(df = df,ax=y,hand='L') | |
| if x == 'location_plot_rhb': | |
| location_plot(df = df,ax=y,hand='R') | |
| summary_table(df=df, | |
| ax=ax_table) | |
| plot_footer(ax_footer) | |
| fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01) | |
| app = App(app_ui, server) | |
| app = App(app_ui, server) |