Update app.py

app.py

@@ -1,803 +0,0 @@
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-import pitch_summary_functions as psf
-import requests
-import matplotlib
-from api_scraper import MLB_Scrape
-from shinywidgets import output_widget, render_widget
-import shinyswatch
-
-
-
-colour_palette = ['#FFB000','#648FFF','#785EF0',
-                  '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']
-
-import datasets
-from datasets import load_dataset
-### Import Datasets
-dataset = load_dataset('nesticot/mlb_data', data_files=['mlb_pitch_data_2024.csv' ])
-dataset_train = dataset['train']
-df_2024 = dataset_train.to_pandas().set_index(list(dataset_train.features.keys())[0]).reset_index(drop=True).drop_duplicates(subset=['play_id'],keep='last')
-
-# ### Import Datasets
-# import datasets
-# from datasets import load_dataset
-# dataset = load_dataset('nesticot/mlb_data', data_files=['mlb_pitch_data_2020.csv' ])
-# dataset_train = dataset['train']
-# df_2024 = dataset_train.to_pandas().set_index(list(dataset_train.features.keys())[0]).reset_index(drop=True)
-
-### PITCH COLOURS ###
-pitch_colours = {
-        'Four-Seam Fastball':'#FF007D',#BC136F
-        'Sinker':'#98165D',#DC267F
-        'Cutter':'#BE5FA0',
-
-        'Changeup':'#F79E70',#F75233
-        'Splitter':'#FE6100',#F75233
-        'Screwball':'#F08223',
-        'Forkball':'#FFB000',
-        
-        'Slider':'#67E18D',#1BB999#785EF0
-        'Sweeper':'#1BB999',#37CD85#904039
-        'Slurve':'#376748',#785EF0#549C07#BEABD8
-
-        'Knuckle Curve':'#311D8B',  
-        'Curveball':'#3025CE',
-        'Slow Curve':'#274BFC',
-        'Eephus':'#648FFF',
-
-        'Knuckleball':'#867A08',
-
-        'Pitch Out':'#472C30',
-        'Other':'#9C8975',
-        }
-
-spring_teams = df_2024.groupby(['pitcher_id']).tail(1)[['pitcher_id','pitcher_team']].set_index(['pitcher_id'])['pitcher_team'].to_dict()
-
-season_start = '2024-03-20'
-season_end = '2024-09-29'
-season_fg=2024 
-chad_fg = requests.get(f'https://www.fangraphs.com/api/leaders/major-league/data?age=&pos=all&stats=pit&lg=all&qual=0&season={season_fg}&season={season_fg}&month=1000&season1={season_fg}&ind=0&pageitems=2000000000&pagenum=1&ind=0&rost=0&players=&type=36&postseason=&sortdir=default&sortstat=sp_pitching').json()
-
-
-chadwick_df_small = pd.DataFrame(data={
-'key_mlbam':[x['xMLBAMID'] for x in chad_fg['data']],
-'key_fangraphs':[x['playerid'] for x in chad_fg['data']],
-'Name':[x['PlayerName'] for x in chad_fg['data']],
-})    
-
-pitcher_dicts = chadwick_df_small.set_index('key_mlbam')['Name'].sort_values().to_dict()
-mlb_fg_dicts = chadwick_df_small.set_index('key_mlbam')['key_fangraphs'].sort_values().to_dict()
-
-
-statcast_pitch_summary = pd.read_csv('statcast_pitch_summary.csv')
-cmap_sum = matplotlib.colors.LinearSegmentedColormap.from_list("", ['#648FFF','#FFFFFF','#FFB000',])
-
-
-df_2024_codes = psf.df_update_code(df_2024)
-
-df_2024_update = psf.df_clean(df_2024_codes)
-import joblib
-model = joblib.load('joblib_model/tjstuff_model_20240318.joblib')
-y_pred_mean = 0.0011434511
-y_pred_std = 0.006554768
-
-features = ['start_speed','spin_rate','extension','ivb','hb','x0','z0','fb_max_velo_diff','fb_max_ivb_diff','fb_max_hb_diff']
-
-targets = ['delta_run_exp_mean']
-
-
-df_2024_update['y_pred'] = model.predict(df_2024_update[features])
-
-df_2024_update['tj_stuff_plus'] = 100 + 10*((-df_2024_update.y_pred +y_pred_mean) / y_pred_std)
-
-team_logos = pd.read_csv('team_logos.csv')
-
-mlb_stats = MLB_Scrape()
-teams_df = mlb_stats.get_teams()
-team_logo_dict = teams_df.set_index(['team_id'])['parent_org_id'].to_dict()
-
-font_properties = {'family': 'calibi', 'size': 12}
-font_properties_titles = {'family': 'calibi', 'size': 20}
-font_properties_axes = {'family': 'calibi', 'size': 16}
-df_plot = []
-ax2_loc = []
-gs = []
-fig = []
-
-function_dict={
-    'velocity_kde':'Velocity Distributions',
-    'break_plot':'Pitch Movement',
-    'rolling_tj_stuff':'Rolling tjStuff+',
-    'location_lhb':'Locations vs LHB',
-    'location_rhb':'Locations vs RHB',
-}
-
-split_dict =  {'all':'All',
-               'left':'LHB',
-               'right':'RHB'}
-
-split_dict_hand =  {'all':['L','R'],
-               'left':['L'],
-               'right':['R']}
-
-ball_dict =  {'0':'0',
-               '1':'1',
-               '2':'2',
-               '3':'3'}
-
-strike_dict =  {'0':'0',
-               '1':'1',
-               '2':'2'}
-
-# count_dict = {'0_0':'Through 0-0',
-#                  '0_1':'Through 0-1',
-#                  '0_2':'Through 0-2',
-#                  '1_0':'Through 1-0',
-#                  '1_1':'Through 1-1',
-#                  '1_2':'Through 1-2',
-#                  '2_1':'Through 2-1',
-#                  '2_0':'Through 2-0',
-#                  '3_0':'Through 3-0',
-#                  '3_1':'Through 3-1',
-#                  '2_2':'Through 2-2',
-#                  '3_2':'Through 3-2'}
-
-# count_dict_fg = {'0_0':'',
-#                  '0_1':'61',
-#                  '0_2':'62',
-#                  '1_0':'63',
-#                  '1_1':'64',
-#                  '1_2':'65',
-#                  '2_1':'66',
-#                  '2_0':'67',
-#                  '3_0':'68',
-#                  '3_1':'69',
-#                  '2_2':'70',
-#                  '3_2':'71'}
-
-from urllib.request import Request, urlopen
-from shiny import App, reactive, ui, render
-from shiny.ui import h2, tags
-# importing OpenCV(cv2) module
-app_ui = ui.page_fluid(
-    ui.tags.div(
-         {"style": "width:90%;margin: 0 auto;max-width: 1600px;"},
-        ui.tags.style(
-            """
-            h4 {
-                margin-top: 1em;font-size:35px;
-            }
-            h2{
-                font-size:25px;
-            }
-            """
-         ),
-    shinyswatch.theme.simplex(),
-    ui.tags.h4("TJStats"),
-    ui.tags.i("Baseball Analytics and Visualizations"),
-    ui.row(
-
-    
-    ui.layout_sidebar(
- 
-        ui.panel_sidebar(
-                ui.row(
-                ui.column(6,
-                    ui.input_select('player_id','Select Player',pitcher_dicts,selectize=True,multiple=False)),
-                ui.column(6,    ui.output_ui('test','Select Game'))),
-                
-                ui.row(
-                ui.column(4,
-                    ui.input_select('plot_id_1','Plot Left',function_dict,multiple=False,selected='velocity_kde')),
-                ui.column(4,
-                    ui.input_select('plot_id_2','Plot Middle',function_dict,multiple=False,selected='rolling_tj_stuff')),
-                ui.column(4,
-                    ui.input_select('plot_id_3','Plot Right',function_dict,multiple=False,selected='break_plot'))),
-
-                # ui.input_select('count_id','Count',count_dict,multiple=True,selectize=True,selected='0_0'),
-
-                ui.row(
-                ui.column(6,
-                        ui.input_select('ball_id','Balls',ball_dict,multiple=False,selected='0'),
-                                                ui.input_radio_buttons(
-                                                    "count_id_balls",
-                                                    "Count Filter Balls",
-                                                    {
-                                                        "exact": "Exact Balls",
-                                                        "greater": ">= Balls",
-                                                        "lesser": "<= Balls",
-                                                    },selected='greater')),
-                ui.column(6,                                    
-                        ui.input_select('strike_id','Strikes',strike_dict,multiple=False,selected='0'),
-                        ui.input_radio_buttons(
-                                                    "count_id_strikes",
-                                                    "Count Filter Strikes",
-                                                    {
-                                                        "exact": "Exact Strikes",
-                                                        "greater": ">= Strikes",
-                                                        "lesser": "<= Strikes",
-                                                    },selected='greater'))),
-                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=10))),
-
-
-                
-                ui.input_action_button("go", "Generate",class_="btn-primary"),
-                               
-                                       
-                                       width=4)
-                ,
-        ui.panel_main(     
-            ui.navset_tab(
-            # ui.nav("Raw Data",
-            #     ui.output_data_frame("raw_table")),                
-            ui.nav("Season Summary",
-                   ui.output_plot('plot',
-                                  width='2000px',
-                                  height='2000px')),
-            ui.nav("Game Summary",
-                   ui.output_plot('plot_game',
-                                  width='2000px',
-                                  height='2000px'))
-                ,id="my_tabs"))))))
-
-
-
-
-
-
-
-
-
-
-#print(app_ui)
-def server(input, output, session):
-
-    @render.ui
-    def test():
-
-            # @reactive.Effect
-            if input.my_tabs() == 'Season Summary':   
-
-                return ui.input_date_range("date_range_id", "Date range input",start = df_2024.game_date.min(),
-                                     end = df_2024.game_date.max(),width=2,min=df_2024.game_date.min(),
-                                       max=df_2024.game_date.max()),        
-            # @reactive.Effect
-            if input.my_tabs() == 'Game Summary':
-                pitcher_id_select = int(input.player_id())
-                df_plot = df_2024_update[(df_2024_update['pitcher_id']==pitcher_id_select)]
-                
-
-                # ax0.text(x=0.5,y=0.30,s=f'2024 Spring Training',fontname='Calibri',ha='center',fontsize=30,va='top')
-                df_plot['game_opp'] = df_plot['game_date'].astype(str) + ' vs ' + df_plot['batter_team'].astype(str)
-                #print(df_plot['game_opp'])
-
-                date_dict = pd.concat([df_plot.drop_duplicates(subset=['pitcher_id','game_id','game_opp'])[['game_id','game_opp']]]).set_index('game_id').to_dict()
-                return ui.input_select("game_id", "Select Game",date_dict,selectize=True)
-            
-    @output
-    @render.plot
-    @reactive.event(input.go, ignore_none=False)
-    def plot():
-        #fig, ax = plt.subplots(3, 2, figsize=(9, 9))
-
-        font_properties = {'family': 'calibi', 'size': 12}
-        font_properties_titles = {'family': 'calibi', 'size': 20}
-        font_properties_axes = {'family': 'calibi', 'size': 16}
-                
-        if len((input.player_id()))<1:
-            fig, ax = plt.subplots(1, 1, figsize=(9, 9))
-            ax.text(x=0.5,y=0.5,s='Please Select\nA Player',fontsize=150,ha='center')
-            ax.grid('off')
-            return                
-        
-        pitcher_id_select = int(input.player_id())
-
-
-        df_plot = df_2024_update[(df_2024_update['pitcher_id']==pitcher_id_select)]
-
-        df_plot = df_plot[df_plot['batter_hand'].isin(split_dict_hand[input.split_id()])]
-
-        if input.count_id_balls()=='greater' and input.count_id_strikes()=='greater' and int(input.ball_id())==0 and int(input.strike_id())==0:
-            ball_title = ''
-            strike_title = ''
-        else: 
-            if input.count_id_balls()=='exact':
-                df_plot = df_plot[df_plot['balls']==int(input.ball_id())]
-                ball_title = str(f'{(input.ball_id())} Ball Count; ')                                                   
-            elif input.count_id_balls()=='greater':
-                df_plot = df_plot[df_plot['balls']>=int(input.ball_id())]
-                ball_title = str(f'At Least {(input.ball_id())} Ball Count; ')                         
-            elif input.count_id_balls()=='lesser':  
-                df_plot = df_plot[df_plot['balls']<=int(input.ball_id())]
-                ball_title = str(f'At Most {(input.ball_id())} Ball Count; ')                                        
-
-            if input.count_id_strikes()=='exact':
-                df_plot = df_plot[df_plot['strikes']==int(input.strike_id())]     
-                strike_title = str(f'{(input.strike_id())} Strike Count; ')                           
-            elif input.count_id_strikes()=='greater':
-                df_plot = df_plot[df_plot['strikes']>=int(input.strike_id())]     
-                strike_title = str(f'At Least {(input.strike_id())} Strike Count; ')            
-            elif input.count_id_strikes()=='lesser':
-                df_plot = df_plot[df_plot['strikes']<=int(input.strike_id())]  
-                strike_title = str(f'At Most {(input.strike_id())} Strike Count; ')                                        
-                                      
-
-
-        if input.split_id() == 'all':
-            split_title = ''
-
-        elif input.split_id() == 'left':
-            split_title = 'vs. LHH'
-            
-        elif input.split_id() == 'right':
-            split_title = 'vs. RHH'
-
-
-        if len(df_plot)<1:
-            fig, ax = plt.subplots(1, 1, figsize=(9, 9))
-            ax.text(x=0.5,y=0.5,s='Please Select\nOther Parameters',fontsize=150,ha='center')
-            ax.grid('off')
-            return
-
-        df_plot['pitch_type_count'] = df_plot.groupby(['pitcher_id'])['pitch_type'].cumcount()+1
-        df_plot['pitch_type_count_each'] = df_plot.groupby(['pitch_type'])['pitch_type'].cumcount()+1
-        #df_plot = df_plot.merge(df_2024_update[['tj_stuff_plus','play_id']],left_on=['play_id'],right_on=['play_id'],how='left')
-        df_plot = df_plot.sort_values(by=['pitch_description'])
-
-        grouped_ivb = psf.group_ivb_update(df=df_plot,agg_list=['pitcher_id','pitcher_name','pitcher_hand','pitch_type','pitch_description'])
-        grouped_ivb_all = psf.group_ivb_update(df=df_plot,agg_list=['pitcher_id','pitcher_name','pitcher_hand'])
-
-
-
-        from matplotlib.gridspec import GridSpec
-        plt.rcParams['font.family'] = 'Calibri'
-        df_plot['prop'] = df_plot.groupby("pitch_type")["is_pitch"].transform("sum")
-        label_labels = df_plot.sort_values(by=['prop','pitch_type'],ascending=[False,True]).pitch_description.unique()
-
-        #plt.rcParams["figure.figsize"] = [10,10]
-        fig = plt.figure(figsize=(20, 20))
-        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(7, 2, width_ratios=[1,1], height_ratios=[1.5,1,1,1,1,1,2.5])
-        gs = GridSpec(5, 5,  height_ratios=[150,75,225,325,50],width_ratios=[1,100,100,100,1])
-        #### NO FG
-        ####gs = GridSpec(5, 5,  height_ratios=[225,0,225,325,50],width_ratios=[1,100,100,100,1])
-        #gs = GridSpec(4, 1, width_ratios=[1], height_ratios=[1,0.75,7-len(label_labels)/4,1+len(label_labels)/4])
-
-        gs.update(hspace=0.2, wspace=0.3)
-
-        # Add subplots to the grid
-        ax0 = fig.add_subplot(gs[0, :]) 
-        ax1_table = fig.add_subplot(gs[1, :])
-        ax2_left = fig.add_subplot(gs[2, 1]) 
-        ax2_middle = fig.add_subplot(gs[2, 2]) 
-        ax2_right = fig.add_subplot(gs[2, 3])
-        ax3 = fig.add_subplot(gs[-2, :])
-        #axfooter = fig.add_subplot(gs[-1, :])
-
-        ax1_table.axis('off')
-
-        sns.set_theme(style="whitegrid", palette=colour_palette)
-        fig.set_facecolor('white')
-
-        font_properties = {'family': 'calibi', 'size': 12}
-        font_properties_titles = {'family': 'calibi', 'size': 20}
-        font_properties_axes = {'family': 'calibi', 'size': 16}
-
-        ## FANGRAPHS TABLE ###
-        data_pull = psf.fangraphs_scrape(pitcher_id=pitcher_id_select,
-                            split=input.split_id(),
-                            start_date=input.date_range_id()[0],
-                            end_date=input.date_range_id()[1])
-
-
-        psf.fangraphs_table(data=data_pull,
-                            stats=['IP','WHIP','ERA','FIP','TBF','K%','BB%','K-BB%'],
-                            ax=ax1_table)
-
-        for x,y,z in zip([input.plot_id_1(),input.plot_id_2(),input.plot_id_3()],[ax2_left,ax2_middle,ax2_right],[1,2,3]):
-            if x == 'velocity_kde':
-                psf.velocity_kdes(df=df_plot,ax=y,gs=gs,gs_list=z,fig=fig)
-            if x == 'rolling_tj_stuff':
-                psf.tj_stuff_roling(df = df_plot,window = int(input.rolling_window()),ax=y)
-            if x == 'break_plot':
-                psf.break_plot(df=df_plot,ax=y) 
-            if x == 'location_lhb':
-                psf.location_plot(df=df_plot,ax=y,hand='L')
-            if x == 'location_rhb':
-                psf.location_plot(df=df_plot,ax=y,hand='R')
-
-        pitches_list = df_plot['pitch_description'].unique()
-        colour_pitches = [pitch_colours[x] for x in pitches_list]
-        
-    #     handles, labels = ax2_right.get_legend_handles_labels()
-
-    #   # Manually create handles and labels for each pitch-color pair
-        handles = [plt.scatter([], [], color=color, marker='o', s=100) for color in colour_pitches]
-        labels = pitches_list  
-        
-                
-
-
-        ### FANGRAPHS TABLE ###
-        psf.table_summary(df=df_plot.copy(),
-                        pitcher_id=pitcher_id_select,
-                        ax=ax3,
-                        df_group=grouped_ivb.copy(),
-                        df_group_all=grouped_ivb_all.copy(),
-                        statcast_pitch_summary=statcast_pitch_summary.copy())
-
-
-        # ############ FOOTER ################
-        # #fig.text(x=0.5,y=0.05,s='Note: Colour Coding Compares to League Average By Pitch',ha='center',fontname='Calibri',fontsize=10)
-        # axfooter.text(x=0.05,y=1,s='By: Thomas Nestico\n      @TJStats',fontname='Calibri',ha='left',fontsize=24,va='top')
-        # axfooter.text(x=1-0.05,y=1,s='Data: MLB, Fangraphs',ha='right',fontname='Calibri',fontsize=24,va='top')
-
-
-        # axfooter.text(x=0.5,y=0.8,s='Colour Coding Compares to League Average By Pitch\ntjStuff+ calculates the Expected Run Value (xRV) of a pitch regardless of type\ntjStuff+ is normally distributed, where 100 is the mean and Standard Deviation is 10',
-        #             ha='center',va='center',fontname='Calibri',fontsize=16)
-        # axfooter.axis('off')
-        # #fig.tight_layout()
-
-        
-
-        # Get value counts of the column and sort in descending order
-        sorted_value_counts = df_plot['pitch_description'].value_counts().sort_values(ascending=False)
-
-        # Get the list of items ordered from most to least frequent
-        items_in_order = sorted_value_counts.index.tolist()
-        # Create a dictionary to map names to colors
-        name_to_color = dict(zip(labels, handles))
-
-        # Order the colors based on the correct order of names
-        ordered_colors = [name_to_color[name] for name in items_in_order]
-
-
-        ax3.legend(ordered_colors, items_in_order, bbox_to_anchor=(0.1, 0.81, 0.8, 0.2), ncol=5,
-                fancybox=True,loc='lower center',fontsize=20,framealpha=1.0, markerscale=2,prop={'family': 'calibi', 'size': 20})
-
-
-        ################## Title ##########
-        title_spot = f'{df_plot.pitcher_name.values[0]}'
-
-
-        ax0.text(x=0.5,y=0.8,s=title_spot,fontname='Calibri',ha='center',fontsize=56,va='top')
-        ax0.text(x=0.5,y=0.5,s='Season Pitching Summary',fontname='Calibri',ha='center',fontsize=40,va='top',fontstyle='italic')
-
-
-        #ax0.text(x=0.5,y=0.25,s=f'2024 Spring Training',fontname='Calibri',ha='center',fontsize=30,va='top')
-        # ax0.text(x=0.5,y=0.25,s=f'{season_fg} MLB Season',fontname='Calibri',ha='center',fontsize=30,va='top')
-        # ax0.axis('off')
-
-
-        ax0.text(x=0.5,y=0.25,s=f'{input.date_range_id()[0]} to {input.date_range_id()[1]}',fontname='Calibri',ha='center',fontsize=30,va='top',fontstyle='italic')
-        
-        ax0.text(x=0.5,y=0.05,s=f'{ball_title}{strike_title}{split_title}',fontname='Calibri',ha='center',fontsize=20,va='top')
-        ax0.axis('off')
-
-        from matplotlib.offsetbox import (OffsetImage, AnnotationBbox)
-        import urllib
-        import urllib.request
-        import urllib.error
-        from urllib.error import HTTPError
-
-        try: 
-            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/d_people:generic:headshot:67:current.png/w_213,q_auto:best/v1/people/{pitcher_id_select}/headshot/67/current.png'
-            test_mage = plt.imread(url)
-        except urllib.error.HTTPError as err:
-            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/d_people:generic:headshot:67:current.png/w_213,q_auto:best/v1/people/1/headshot/67/current.png'                
-        imagebox = OffsetImage(test_mage, zoom = 0.5)
-        ab = AnnotationBbox(imagebox, (0.125, 0.4), frameon = False)
-        ax0.add_artist(ab)
-
-        player_bio = requests.get(url=f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id_select}&hydrate=currentTeam").json()
-
-
-
-
-        if 'currentTeam' in player_bio['people'][0]:
-            try:
-                url = team_logos[team_logos['id'] == team_logo_dict[player_bio['people'][0]['currentTeam']['id']]]['imageLink'].values[0]
-
-                im = plt.imread(url)
-                # response = requests.get(url)
-                # im = Image.open(BytesIO(response.content))
-                # im = plt.imread(team_logos[team_logos['id'] == player_bio['people'][0]['currentTeam']['parentOrgId']]['imageLink'].values[0])
-                # ax = fig.add_axes([0,0,1,0.85], anchor='C', zorder=1)
-                imagebox = OffsetImage(im, zoom = 0.4)
-                ab = AnnotationBbox(imagebox, (0.875, 0.40), frameon = False)
-                ax0.add_artist(ab)
-            except IndexError:
-                print()
-            
-
-        ############ FOOTER ################
-        #fig.text(x=0.5,y=0.05,s='Note: Colour Coding Compares to League Average By Pitch',ha='center',fontname='Calibri',fontsize=10)
-        axfooter = fig.add_subplot(gs[-1, :])
-        axfooter.text(x=0.05,y=1,s='By: Thomas Nestico\n      @TJStats',fontname='Calibri',ha='left',fontsize=24,va='top')
-        axfooter.text(x=1-0.05,y=1,s='Data: MLB, Fangraphs',ha='right',fontname='Calibri',fontsize=24,va='top')
-
-
-        axfooter.text(x=0.5,y=0.8,s='Colour Coding Compares to League Average By Pitch\ntjStuff+ calculates the Expected Run Value (xRV) of a pitch regardless of type\ntjStuff+ is normally distributed, where 100 is the mean and Standard Deviation is 10',
-                    ha='center',va='center',fontname='Calibri',fontsize=16)
-        axfooter.axis('off')
-        #fig.tight_layout()
-
-        fig.subplots_adjust(left=0.03, right=0.97, top=0.97, bottom=0.03)
-
-
-    @output
-    @render.plot
-    @reactive.event(input.go, ignore_none=False)
-    def plot_game():
-        #fig, ax = plt.subplots(3, 2, figsize=(9, 9))
-
-        font_properties = {'family': 'calibi', 'size': 12}
-        font_properties_titles = {'family': 'calibi', 'size': 20}
-        font_properties_axes = {'family': 'calibi', 'size': 16}
-                
-        if len((input.player_id()))<1:
-            fig, ax = plt.subplots(1, 1, figsize=(9, 9))
-            ax.text(x=0.5,y=0.5,s='Please Select\nA Player',fontsize=150,ha='center')
-            ax.grid('off')
-            return        
-        
-        pitcher_id_select = int(input.player_id())
-
-
-
-
-        df_plot = df_2024_update[(df_2024_update['pitcher_id']==pitcher_id_select)&(df_2024_update['game_id']==int(input.game_id()))]
-        df_plot = df_plot[df_plot['batter_hand'].isin(split_dict_hand[input.split_id()])]
-
-        if input.count_id_balls()=='greater' and input.count_id_strikes()=='greater' and int(input.ball_id())==0 and int(input.strike_id())==0:
-            ball_title = ''
-            strike_title = ''
-        else: 
-            if input.count_id_balls()=='exact':
-                df_plot = df_plot[df_plot['balls']==int(input.ball_id())]
-                ball_title = str(f'{(input.ball_id())} Ball Count; ')                                                   
-            elif input.count_id_balls()=='greater':
-                df_plot = df_plot[df_plot['balls']>=int(input.ball_id())]
-                ball_title = str(f'At Least {(input.ball_id())} Ball Count; ')                         
-            elif input.count_id_balls()=='lesser':  
-                df_plot = df_plot[df_plot['balls']<=int(input.ball_id())]
-                ball_title = str(f'At Most {(input.ball_id())} Ball Count; ')                                        
-
-            if input.count_id_strikes()=='exact':
-                df_plot = df_plot[df_plot['strikes']==int(input.strike_id())]     
-                strike_title = str(f'{(input.strike_id())} Strike Count; ')                           
-            elif input.count_id_strikes()=='greater':
-                df_plot = df_plot[df_plot['strikes']>=int(input.strike_id())]     
-                strike_title = str(f'At Least {(input.strike_id())} Strike Count; ')            
-            elif input.count_id_strikes()=='lesser':
-                df_plot = df_plot[df_plot['strikes']<=int(input.strike_id())]  
-                strike_title = str(f'At Most {(input.strike_id())} Strike Count; ')                                        
-                                      
-
-                                    
-
-
-        if input.split_id() == 'all':
-            split_title = ''
-
-        elif input.split_id() == 'left':
-            split_title = 'vs. LHH'
-            
-        elif input.split_id() == 'right':
-            split_title = 'vs. RHH'
-
-        if len(df_plot)<1:
-            fig, ax = plt.subplots(1, 1, figsize=(9, 9))
-            ax.text(x=0.5,y=0.5,s='Please Select\nOther Parameters',fontsize=150,ha='center')
-            ax.grid('off')
-            return
-
-
-        df_plot['pitch_type_count'] = df_plot.groupby(['pitcher_id'])['pitch_type'].cumcount()+1
-        df_plot['pitch_type_count_each'] = df_plot.groupby(['pitch_type'])['pitch_type'].cumcount()+1
-        #df_plot = df_plot.merge(df_2024_update[['tj_stuff_plus','play_id']],left_on=['play_id'],right_on=['play_id'],how='left')
-        df_plot = df_plot.sort_values(by=['pitch_description'])
-
-        # ax0.text(x=0.5,y=0.30,s=f'2024 Spring Training',fontname='Calibri',ha='center',fontsize=30,va='top')
-        df_plot['game_opp'] = df_plot['game_date'].astype(str) + ' vs ' + df_plot['batter_team'].astype(str)
-        #print(df_plot['game_opp'])
-
-        #date_dict = pd.concat([df_plot.drop_duplicates(subset=['pitcher_id','game_id','game_opp'])[['game_id','game_opp']]]).set_index('game_id').to_dict()
-
-        grouped_ivb = psf.group_ivb_update(df=df_plot,agg_list=['pitcher_id','pitcher_name','pitcher_hand','pitch_type','pitch_description'])
-        grouped_ivb_all = psf.group_ivb_update(df=df_plot,agg_list=['pitcher_id','pitcher_name','pitcher_hand'])
-
-
-
-        from matplotlib.gridspec import GridSpec
-        plt.rcParams['font.family'] = 'Calibri'
-        df_plot['prop'] = df_plot.groupby("pitch_type")["is_pitch"].transform("sum")
-        label_labels = df_plot.sort_values(by=['prop','pitch_type'],ascending=[False,True]).pitch_description.unique()
-
-        #plt.rcParams["figure.figsize"] = [10,10]
-        fig = plt.figure(figsize=(20, 20))
-        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(7, 2, width_ratios=[1,1], height_ratios=[1.5,1,1,1,1,1,2.5])
-        gs = GridSpec(5, 5,  height_ratios=[150,75,225,325,50],width_ratios=[1,100,100,100,1])
-        #### NO FG
-        ####gs = GridSpec(5, 5,  height_ratios=[225,0,225,325,50],width_ratios=[1,100,100,100,1])
-        #gs = GridSpec(4, 1, width_ratios=[1], height_ratios=[1,0.75,7-len(label_labels)/4,1+len(label_labels)/4])
-
-        gs.update(hspace=0.2, wspace=0.3)
-
-        # Add subplots to the grid
-        ax0 = fig.add_subplot(gs[0, :]) 
-        ax1_table = fig.add_subplot(gs[1, :])
-        ax2_left = fig.add_subplot(gs[2, 1]) 
-        ax2_middle = fig.add_subplot(gs[2, 2]) 
-        ax2_right = fig.add_subplot(gs[2, 3])
-        ax3 = fig.add_subplot(gs[-2, :])
-        # axfooter = fig.add_subplot(gs[-1, :])
-
-        ax1_table.axis('off')
-
-        sns.set_theme(style="whitegrid", palette=colour_palette)
-        fig.set_facecolor('white')
-
-        font_properties = {'family': 'calibi', 'size': 12}
-        font_properties_titles = {'family': 'calibi', 'size': 20}
-        font_properties_axes = {'family': 'calibi', 'size': 16}
-
-        print(df_2024_update['game_date'].values[0])
-        ## FANGRAPHS TABLE ###
-        data_pull = psf.fangraphs_scrape(pitcher_id=pitcher_id_select,
-                            split=input.split_id(),
-                            start_date=df_plot['game_date'].values[0],
-                            end_date=df_plot['game_date'].values[0])
-
-
-        psf.fangraphs_table(data=data_pull,
-                            stats=['IP','WHIP','ERA','FIP','TBF','K%','BB%','K-BB%'],
-                            ax=ax1_table)
-
-        # psf.velocity_kdes(df=df_plot,
-        #                 ax=ax2_loc,
-        #                 gs=gs,
-        #                 fig=fig)
-
-        # # psf.tj_stuff_roling(df = df_plot,
-        # #                     window = 5,
-        # #                     ax=ax2_velo)
-        # psf.location_plot(df=df_plot,ax=ax2_velo,hand='L')
-
-        # psf.location_plot(df=df_plot,ax=ax2_loc,hand='R')
-        # # # ## Break Plot
-        # psf.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()],[ax2_left,ax2_middle,ax2_right],[1,2,3]):
-            if x == 'velocity_kde':
-                psf.velocity_kdes(df=df_plot,ax=y,gs=gs,gs_list=z,fig=fig)
-            if x == 'rolling_tj_stuff':
-                psf.tj_stuff_roling(df = df_plot,window = int(input.rolling_window()),ax=y)
-            if x == 'break_plot':
-                psf.break_plot(df=df_plot,ax=y) 
-            if x == 'location_lhb':
-                psf.location_plot(df=df_plot,ax=y,hand='L')
-            if x == 'location_rhb':
-                psf.location_plot(df=df_plot,ax=y,hand='R')
-
-        pitches_list = df_plot['pitch_description'].unique()
-        colour_pitches = [pitch_colours[x] for x in pitches_list]
-        
-    #     handles, labels = ax2_right.get_legend_handles_labels()
-
-    #   # Manually create handles and labels for each pitch-color pair
-        handles = [plt.scatter([], [], color=color, marker='o', s=100) for color in colour_pitches]
-        labels = pitches_list  
-
-
-        ### FANGRAPHS TABLE ###
-        psf.table_summary(df=df_plot.copy(),
-                        pitcher_id=pitcher_id_select,
-                        ax=ax3,
-                        df_group=grouped_ivb.copy(),
-                        df_group_all=grouped_ivb_all.copy(),
-                        statcast_pitch_summary=statcast_pitch_summary.copy())
-
-
-
-
-
-        # Get value counts of the column and sort in descending order
-        sorted_value_counts = df_plot['pitch_description'].value_counts().sort_values(ascending=False)
-
-        # Get the list of items ordered from most to least frequent
-        items_in_order = sorted_value_counts.index.tolist()
-        # Create a dictionary to map names to colors
-        name_to_color = dict(zip(labels, handles))
-
-        # Order the colors based on the correct order of names
-        ordered_colors = [name_to_color[name] for name in items_in_order]
-
-
-        ax3.legend(ordered_colors, items_in_order, bbox_to_anchor=(0.1, 0.81, 0.8, 0.2), ncol=5,
-                fancybox=True,loc='lower center',fontsize=20,framealpha=1.0, markerscale=2,prop={'family': 'calibi', 'size': 20})
-
-
-        ################## Title ##########
-        title_spot = f'{df_plot.pitcher_name.values[0]}'
-
-
-        ax0.text(x=0.5,y=0.8,s=title_spot,fontname='Calibri',ha='center',fontsize=56,va='top')
-        ax0.text(x=0.5,y=0.5,s='Game Pitching Summary',fontname='Calibri',ha='center',fontsize=40,va='top',fontstyle='italic')
-
-
-        #ax0.text(x=0.5,y=0.25,s=f'2024 Spring Training',fontname='Calibri',ha='center',fontsize=30,va='top')
-        #ax0.text(x=0.5,y=0.25,s=f'{season_fg} MLB Season',fontname='Calibri',ha='center',fontsize=30,va='top')
-        #ax0.text(x=0.5,y=0.25,s=f'2024 Spring Training',fontname='Calibri',ha='center',fontsize=30,va='top')
-        # ax0.text(x=0.5,y=0.25,s=f'{season_fg} MLB Season',fontname='Calibri',ha='center',fontsize=30,va='top')
-
-        ax0.text(x=0.5,y=0.25,s= df_plot['game_opp'].values[0],fontname='Calibri',ha='center',fontstyle='italic',fontsize=30,va='top')
-        
-        ax0.text(x=0.5,y=0.05,s=f'{ball_title}{strike_title}{split_title}',fontname='Calibri',ha='center',fontsize=20,va='top')
-        ax0.axis('off')
-
-
-        from matplotlib.offsetbox import (OffsetImage, AnnotationBbox)
-        import urllib
-        import urllib.request
-        import urllib.error
-        from urllib.error import HTTPError
-
-        try: 
-            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/d_people:generic:headshot:67:current.png/w_213,q_auto:best/v1/people/{pitcher_id_select}/headshot/67/current.png'
-            test_mage = plt.imread(url)
-        except urllib.error.HTTPError as err:
-            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/d_people:generic:headshot:67:current.png/w_213,q_auto:best/v1/people/1/headshot/67/current.png'                
-        imagebox = OffsetImage(test_mage, zoom = 0.5)
-        ab = AnnotationBbox(imagebox, (0.125, 0.4), frameon = False)
-        ax0.add_artist(ab)
-
-        player_bio = requests.get(url=f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id_select}&hydrate=currentTeam").json()
-
-
-
-
-        if 'currentTeam' in player_bio['people'][0]:
-            try:
-                url = team_logos[team_logos['id'] == team_logo_dict[player_bio['people'][0]['currentTeam']['id']]]['imageLink'].values[0]
-
-                im = plt.imread(url)
-                # response = requests.get(url)
-                # im = Image.open(BytesIO(response.content))
-                # im = plt.imread(team_logos[team_logos['id'] == player_bio['people'][0]['currentTeam']['parentOrgId']]['imageLink'].values[0])
-                # ax = fig.add_axes([0,0,1,0.85], anchor='C', zorder=1)
-                imagebox = OffsetImage(im, zoom = 0.4)
-                ab = AnnotationBbox(imagebox, (0.875, 0.40), frameon = False)
-                ax0.add_artist(ab)
-            except IndexError:
-                print()
-            
-        ############ FOOTER ################
-        #fig.text(x=0.5,y=0.05,s='Note: Colour Coding Compares to League Average By Pitch',ha='center',fontname='Calibri',fontsize=10)
-        axfooter = fig.add_subplot(gs[-1, :])
-        axfooter.text(x=0.05,y=1,s='By: Thomas Nestico\n      @TJStats',fontname='Calibri',ha='left',fontsize=24,va='top')
-        axfooter.text(x=1-0.05,y=1,s='Data: MLB, Fangraphs',ha='right',fontname='Calibri',fontsize=24,va='top')
-
-
-        axfooter.text(x=0.5,y=0.8,s='Colour Coding Compares to League Average By Pitch\ntjStuff+ calculates the Expected Run Value (xRV) of a pitch regardless of type\ntjStuff+ is normally distributed, where 100 is the mean and Standard Deviation is 10',
-                    ha='center',va='center',fontname='Calibri',fontsize=16)
-        axfooter.axis('off')
-        #fig.tight_layout()
-
-
-        fig.subplots_adjust(left=0.03, right=0.97, top=0.97, bottom=0.03)
-
-app = App(app_ui, server)