Update app.py

app.py

@@ -1,641 +1,641 @@
-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
-# from functions.PitchPlotFunctions import *
-import functions.PitchPlotFunctions as ppf
-ploter = ppf.PitchPlotFunctions()
-from shiny.plotutils import brushed_points
-from pytabulator import TableOptions, Tabulator, output_tabulator, render_tabulator, theme
-theme.tabulator_site()
-
-colour_palette = ['#FFB000','#648FFF','#785EF0',
-                  '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']
-cmap_sum = mcolors.LinearSegmentedColormap.from_list("", ['#648FFF', '#FFFFFF', '#FFB000'])
-
-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']}
-
-### PITCH COLOURS ###
-
-# Dictionary to map pitch types to their corresponding colors and names
-pitch_colours = {
-    ## Fastballs ##
-    'FF': {'colour': '#FF007D', 'name': '4-Seam Fastball'},
-    'FA': {'colour': '#FF007D', 'name': 'Fastball'},
-    'SI': {'colour': '#98165D', 'name': 'Sinker'},
-    'FC': {'colour': '#BE5FA0', 'name': 'Cutter'},
-
-    ## Offspeed ##
-    'CH': {'colour': '#F79E70', 'name': 'Changeup'},
-    'FS': {'colour': '#FE6100', 'name': 'Splitter'},
-    'SC': {'colour': '#F08223', 'name': 'Screwball'},
-    'FO': {'colour': '#FFB000', 'name': 'Forkball'},
-
-    ## Sliders ##
-    'SL': {'colour': '#67E18D', 'name': 'Slider'},
-    'ST': {'colour': '#1BB999', 'name': 'Sweeper'},
-    'SV': {'colour': '#376748', 'name': 'Slurve'},
-
-    ## Curveballs ##
-    'KC': {'colour': '#311D8B', 'name': 'Knuckle Curve'},
-    'CU': {'colour': '#3025CE', 'name': 'Curveball'},
-    'CS': {'colour': '#274BFC', 'name': 'Slow Curve'},
-    'EP': {'colour': '#648FFF', 'name': 'Eephus'},
-
-    ## Others ##
-    'KN': {'colour': '#867A08', 'name': 'Knuckleball'},
-    'KN': {'colour': '#867A08', 'name': 'Knuckle Ball'},
-    'PO': {'colour': '#472C30', 'name': 'Pitch Out'},
-    'UN': {'colour': '#9C8975', 'name': 'Unknown'},
-}
-
-# Create dictionaries for pitch types and their attributes
-dict_colour = {key: value['colour'] for key, value in pitch_colours.items()}
-dict_pitch = {key: value['name'] for key, value in pitch_colours.items()}
-dict_pitch_desc_type = {value['name']: key for key, value in pitch_colours.items()}
-dict_pitch_desc_type.update({'Four-Seam Fastball':'FF'})
-dict_pitch_desc_type.update({'All':'All'})
-dict_pitch_name = {value['name']: value['colour'] for key, value in pitch_colours.items()}
-dict_pitch_name.update({'Four-Seam Fastball':'#FF007D'})
-dict_pitch_name.update({'4-Seam':'#FF007D'})
-
-
-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(6, ui.input_select('year_input', 'Select Season', year_list, selected=2024)),
-                ui.column(6, ui.input_select('level_input', 'Select Level', level_dict))
-            ),
-            # 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'))),
-
-            ui.row(
-                ui.column(6, ui.input_select('split_id', 'Select Split', split_dict, multiple=False)),
-            ),
-            # Row for the action button to generate plot
-            ui.row(ui.input_action_button("generate_plot", "Generate Plot", class_="btn-primary")),
-            ui.row(ui.input_action_button("generate_table", "Generate Table", class_="btn-warning")),
-            
-        ),
-
-                
-        ui.panel_main(
-            # ui.navset_tab(
-                # Tab for game summary plot
-                # ui.nav(
-                    # "Pitching Summary",
-ui.card(
-    {"style": "width: 870px;"},
-    ui.head_content(
-        ui.tags.script(src="https://cdnjs.cloudflare.com/ajax/libs/d3/7.8.5/d3.min.js"),
-        ui.tags.script("""
-        async function downloadSVG() {
-            const content = document.getElementById('capture-section');
-            
-            // Create a new SVG element
-            const svg = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
-            const bbox = content.getBoundingClientRect();
-            
-            // Set SVG attributes
-            svg.setAttribute('width', bbox.width);
-            svg.setAttribute('height', bbox.height);
-            svg.setAttribute('viewBox', `0 0 ${bbox.width} ${bbox.height}`);
-            
-            // Create foreignObject to contain HTML content
-            const foreignObject = document.createElementNS('http://www.w3.org/2000/svg', 'foreignObject');
-            foreignObject.setAttribute('width', '100%');
-            foreignObject.setAttribute('height', '100%');
-            foreignObject.setAttribute('x', '0');
-            foreignObject.setAttribute('y', '0');
-            
-            // Clone the content and its styles
-            const clonedContent = content.cloneNode(true);
-            
-            // Add necessary style context
-            const style = document.createElement('style');
-            Array.from(document.styleSheets).forEach(sheet => {
-                try {
-                    Array.from(sheet.cssRules).forEach(rule => {
-                        style.innerHTML += rule.cssText + '\\n';
-                    });
-                } catch (e) {
-                    console.warn('Could not access stylesheet rules');
-                }
-            });
-            
-            // Create a wrapper div to hold styles and content
-            const wrapper = document.createElement('div');
-            wrapper.appendChild(style);
-            wrapper.appendChild(clonedContent);
-            
-            foreignObject.appendChild(wrapper);
-            svg.appendChild(foreignObject);
-            
-            // Convert to SVG string with XML declaration and DTD
-            const svgString = new XMLSerializer().serializeToString(svg);
-            const svgBlob = new Blob([
-                '<?xml version="1.0" standalone="no"?>\\n',
-                '<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">\\n',
-                svgString
-            ], {type: 'image/svg+xml;charset=utf-8'});
-            
-            // Create and trigger download
-            const url = URL.createObjectURL(svgBlob);
-            const link = document.createElement('a');
-            link.href = url;
-            link.download = 'plot_and_table.svg';
-            document.body.appendChild(link);
-            link.click();
-            document.body.removeChild(link);
-            URL.revokeObjectURL(url);
-        }
-        
-        $(document).on('click', '#capture_btn', function() {
-            downloadSVG();
-        });
-        """)
-    ),
-    ui.output_text("status"),
-    ui.div(
-        {
-            "id": "capture-section",
-            "style": "background-color: white; padding: 0; margin-left: 20px; margin-right: 20px; margin-top: 20px; margin-bottom: 20px;"  # Added margin-right
-        },
-        # Plot section with relative positioning for brush
-        ui.div(
-            {"style": "position: relative;"},
-            ui.output_ui("plot_ui")
-        ),
-        # Table section
-        ui.div(
-            {"style": "margin-top: 20px;"},
-            ui.row(ui.tags.b("Pitches in Selection"), ui.output_table("in_brush")),
-            
-
-        ),
-        ui.div({"style": "height: 20px;"}) 
-    ),
-    ui.input_action_button("capture_btn", "Save as SVG", class_="btn-primary"),
-)
-            #     ),
-            # )
-        )
-    )
-)
-
-
-def server(input, output, session):
-
-    @reactive.calc
-    @reactive.event(input.pitcher_id, input.date_id,input.split_id)
-    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)
-
-        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')
-            ))
-        
-        df = df.with_columns(
-            prop_percent=(pl.col('is_pitch') / pl.col('is_pitch').sum()).over("pitch_type"),
-            prop=pl.col('is_pitch').sum().over("pitch_type")
-        )
-
-        return df
-
-    @render.ui
-    @reactive.event(input.player_button, input.level_input,input.year_input, ignore_none=False)
-    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())).filter(
-            pl.col("position").is_in(['P'])).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)
-
-    @render.ui
-    @reactive.event(input.player_button,input.pitcher_id,input.year_input, ignore_none=False)
-    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())}-03-31",
-                                   min=f"{int(input.year_input())}-01-01",
-                                    max=f"{int(input.year_input())}-12-31")
-    @output
-    @render.text
-    def status():
-        # Only show status when generating
-        if input.generate == 0:
-            return ""
-        return ""   
-
-    @render.ui
-    @reactive.event(input.generate_plot)   
-    def plot_ui():
-        brush_opts_kwargs = {}
-        brush_opts_kwargs["direction"] = 'xy'
-        brush_opts_kwargs["delay"] = 60  # Optional: adds a small delay for better performance
-        brush_opts_kwargs["delay_type"] = "throttle"
-        
-    
-        return ui.output_plot('plot', 
-                            width='800px', 
-                            height='800px',
-                            brush=ui.brush_opts(**brush_opts_kwargs))
-
-    @render.table
-    @reactive.event(input.plot_brush, input.generate_table)  # Note: changed to match the brush ID
-    def in_brush():
-        # if input.plot_brush() is None:  # Note: changed to match the brush ID
-        #     return None
-        brushed_df = pl.DataFrame(brushed_points(
-            cached_data().to_pandas(),
-            input.plot_brush(),
-            xvar="hb",
-            yvar="ivb",
-            all_rows=False
-        ))
-
-    
-        brushed_df_final = (((brushed_df.group_by(['pitcher_id', 'pitch_description'])
-                .agg([
-                    pl.col('is_pitch').drop_nans().count().alias('pitches'),
-                    pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
-                    pl.col('vb').drop_nans().mean().round(1).alias('vb'),
-                    pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
-                    pl.col('hb').drop_nans().mean().round(1).alias('hb'),
-                    pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
-                    pl.col('x0').drop_nans().mean().round(1).alias('x0'),
-                    pl.col('z0').drop_nans().mean().round(1).alias('z0'),
-                    pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
-                ])
-                .with_columns(
-                    (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id'))
-                    # .round(1)
-                    # .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
-                    .alias('proportion')
-                )
-                )).sort('proportion', descending=True).
-                select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
-                                                                "spin_rate", "x0", "z0",'tj_stuff_plus'])
-                .with_columns(
-            pl.when(pl.col("pitch_description") == "Four-Seam Fastball")
-            .then(pl.lit("4-Seam"))
-            .otherwise(pl.col("pitch_description"))
-            .alias("pitch_description")
-        )
-                .rename({
-                    'pitch_description': 'Pitch Type',
-                    'pitches': 'Pitches',
-                    'proportion': 'Prop',
-                    'start_speed': 'Velo',
-                    'ivb': 'iVB',
-                    'hb': 'HB',
-                    'spin_rate': 'Spin',
-                    'x0': 'hRel',
-                    'z0': 'vRel',
-                    'tj_stuff_plus': 'tjStuff+'
-                }))
-        
-        # brushed_df_final = brushed_df_final
-        
-        # print(brushed_df_final)
-       
-        def change_font(val):
-            if val == "Cutter":
-                return "color: red; font-weight: bold;"
-            else:
-                ''
-                return "font-weight: bold;"
-        df_brush_style = (brushed_df_final.to_pandas().style.set_precision(1)
-                          
-                          .set_properties(**{'border': '3 px'},overwrite=False).set_table_styles([{
-            'selector': 'caption',
-            'props': [
-                ('color', ''),
-                ('fontname', 'Century Gothic'),
-                ('font-size', '16px'),
-                ('font-style', 'italic'),
-                ('font-weight', ''),
-                ('text-align', 'centre'),
-                ]
-
-                },{'selector' :'th', 'props':[('font-size', '16px'),('text-align', 'center'),('Height','px'),('color','black'),('border', '1px black solid !important')]},{'selector' :'td', 'props':[('text-align', 'center'),('font-size', '16px'),('color','black')]}],overwrite=False)
-                .set_properties(**{'background-color':'White','index':'White','min-width':'72px'},overwrite=False)
-                .set_table_styles([{'selector': 'th:first-child', 'props': [('background-color', 'white')]}],overwrite=False)
-                .set_table_styles([{'selector': 'tr:first-child', 'props': [('background-color', 'white')]}],overwrite=False)
-                .set_table_styles([{'selector': 'tr', 'props': [('line-height', '20px')]}],overwrite=False)
-                .set_properties(**{'Height': '8px'},**{'text-align': 'center'},overwrite=False)
-                .hide_index()
-                .set_properties(**{'border': '1px black solid !important'})
-                .format('{:.0%}',subset=(brushed_df_final.columns[2]))
-                .format('{:.0f}',subset=(brushed_df_final.columns[6]))
-                .format('{:.0f}',subset=(brushed_df_final.columns[-1]))
-                .set_properties(subset=brushed_df_final.columns, **{'height': '30px'})
-                .set_table_styles([{'selector': 'thead th', 'props': [('height', '30px')]}], overwrite=False)
-                # .set_table_styles([{'selector': 'table', 'props': [('width', '100px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(1)', 'props': [('min-width', '125px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(2)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(3)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(4)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(5)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(6)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(7)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .set_table_styles([{'selector': 'thead th:nth-child(8)', 'props': [('min-width', '40px')]}], overwrite=False)
-                .background_gradient(cmap=cmap_sum,subset = (brushed_df_final.columns[-1]),vmin=80,vmax=120)
-                .applymap(lambda x: f'background-color: {dict_pitch_name.get(x, "")}', subset=['Pitch Type'])
-                
-                                                
-    )
-
-        return df_brush_style
-
-        # return Tabulator(
-        #     brushed_df.to_pandas(),
-        #     table_options=TableOptions(
-        #         height=800,
-        #         resizable_column_fit=True,
-        #     )
-        # )
-        # return brushed_points(
-        #     ((brushed_df.group_by(['pitcher_id', 'pitch_description'])
-        #             .agg([
-        #                 pl.col('is_pitch').drop_nans().count().alias('pitches'),
-        #                 pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
-        #                 pl.col('vb').drop_nans().mean().round(1).alias('vb'),
-        #                 pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
-        #                 pl.col('hb').drop_nans().mean().round(1).alias('hb'),
-        #                 pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
-        #                 pl.col('x0').drop_nans().mean().round(1).alias('x0'),
-        #                 pl.col('z0').drop_nans().mean().round(1).alias('z0'),
-        #                 pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
-        #             ])
-        #             .with_columns(
-        #                 (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id') * 100)
-        #                 .round(1)
-        #                 .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
-        #                 .alias('proportion')
-        #             )
-        #             )).sort('proportion', descending=True).
-        #             select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
-        #                                                            "spin_rate", "x0", "z0",'tj_stuff_plus'])
-        #             .rename({
-        #                 'pitch_description': 'Pitch Type',
-        #                 'pitches': 'Pitches',
-        #                 'proportion': 'Proportion',
-        #                 'start_speed': 'Velocity',
-        #                 'ivb': 'iVB',
-        #                 'hb': 'HB',
-        #                 'spin_rate': 'Spin Rate',
-        #                 'x0': 'hRel',
-        #                 'z0': 'vRel',
-        #                 'tj_stuff_plus': 'tjStuff+'
-        #             }).to_pandas(),
-        #             input.plot_brush(),  # Note: changed to match the brush ID
-        #             xvar="HB",  # Replace "x" with your actual x-axis column name
-        #             yvar="iVB",  # Replace "y" with your actual y-axis column name
-        #             all_rows=False
-        # )
-       
-        
-
-        # return brushed_points(
-        #     ((cached_data().group_by(['pitcher_id', 'pitch_description'])
-        #             .agg([
-        #                 pl.col('is_pitch').drop_nans().count().alias('pitches'),
-        #                 pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
-        #                 pl.col('vb').drop_nans().mean().round(1).alias('vb'),
-        #                 pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
-        #                 pl.col('hb').drop_nans().mean().round(1).alias('hb'),
-        #                 pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
-        #                 pl.col('x0').drop_nans().mean().round(1).alias('x0'),
-        #                 pl.col('z0').drop_nans().mean().round(1).alias('z0'),
-        #                 pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
-        #             ])
-        #             .with_columns(
-        #                 (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id') * 100)
-        #                 .round(1)
-        #                 .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
-        #                 .alias('proportion')
-        #             )
-        #             )).sort('proportion', descending=True).
-        #             select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
-        #                                                            "spin_rate", "x0", "z0",'tj_stuff_plus'])
-        #             .rename({
-        #                 'pitch_description': 'Pitch Type',
-        #                 'pitches': 'Pitches',
-        #                 'proportion': 'Prop',
-        #                 'start_speed': 'Velocity',
-        #                 'ivb': 'iVB',
-        #                 'hb': 'HB',
-        #                 'spin_rate': 'Spin Rate',
-        #                 'x0': 'hRel',
-        #                 'z0': 'vRel',
-        #                 'tj_stuff_plus': 'tjStuff+'
-        #             }).to_pandas(),
-        #             input.plot_brush(),  # Note: changed to match the brush ID
-        #             xvar="HB",  # Replace "x" with your actual x-axis column name
-        #             yvar="iVB",  # Replace "y" with your actual y-axis column name
-        #             all_rows=False
-        # )
-    # @output
-    @render.plot
-    @reactive.event(input.generate_plot)   
-    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...")
-
-
-            ploter.final_plot(
-                df=df,
-                pitcher_id=player_input,
-                plot_picker='short_form_movement',#plot_picker,
-                sport_id=sport_id)
-
-  
-            # #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)
-
-            # # 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)
-
-            # fig.savefig('test.svg')
-            
-            
-
+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
+# from functions.PitchPlotFunctions import *
+import functions.PitchPlotFunctions as ppf
+ploter = ppf.PitchPlotFunctions()
+from shiny.plotutils import brushed_points
+# from pytabulator import TableOptions, Tabulator, output_tabulator, render_tabulator, theme
+# theme.tabulator_site()
+
+colour_palette = ['#FFB000','#648FFF','#785EF0',
+                  '#DC267F','#FE6100','#3D1EB2','#894D80','#16AA02','#B5592B','#A3C1ED']
+cmap_sum = mcolors.LinearSegmentedColormap.from_list("", ['#648FFF', '#FFFFFF', '#FFB000'])
+
+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']}
+
+### PITCH COLOURS ###
+
+# Dictionary to map pitch types to their corresponding colors and names
+pitch_colours = {
+    ## Fastballs ##
+    'FF': {'colour': '#FF007D', 'name': '4-Seam Fastball'},
+    'FA': {'colour': '#FF007D', 'name': 'Fastball'},
+    'SI': {'colour': '#98165D', 'name': 'Sinker'},
+    'FC': {'colour': '#BE5FA0', 'name': 'Cutter'},
+
+    ## Offspeed ##
+    'CH': {'colour': '#F79E70', 'name': 'Changeup'},
+    'FS': {'colour': '#FE6100', 'name': 'Splitter'},
+    'SC': {'colour': '#F08223', 'name': 'Screwball'},
+    'FO': {'colour': '#FFB000', 'name': 'Forkball'},
+
+    ## Sliders ##
+    'SL': {'colour': '#67E18D', 'name': 'Slider'},
+    'ST': {'colour': '#1BB999', 'name': 'Sweeper'},
+    'SV': {'colour': '#376748', 'name': 'Slurve'},
+
+    ## Curveballs ##
+    'KC': {'colour': '#311D8B', 'name': 'Knuckle Curve'},
+    'CU': {'colour': '#3025CE', 'name': 'Curveball'},
+    'CS': {'colour': '#274BFC', 'name': 'Slow Curve'},
+    'EP': {'colour': '#648FFF', 'name': 'Eephus'},
+
+    ## Others ##
+    'KN': {'colour': '#867A08', 'name': 'Knuckleball'},
+    'KN': {'colour': '#867A08', 'name': 'Knuckle Ball'},
+    'PO': {'colour': '#472C30', 'name': 'Pitch Out'},
+    'UN': {'colour': '#9C8975', 'name': 'Unknown'},
+}
+
+# Create dictionaries for pitch types and their attributes
+dict_colour = {key: value['colour'] for key, value in pitch_colours.items()}
+dict_pitch = {key: value['name'] for key, value in pitch_colours.items()}
+dict_pitch_desc_type = {value['name']: key for key, value in pitch_colours.items()}
+dict_pitch_desc_type.update({'Four-Seam Fastball':'FF'})
+dict_pitch_desc_type.update({'All':'All'})
+dict_pitch_name = {value['name']: value['colour'] for key, value in pitch_colours.items()}
+dict_pitch_name.update({'Four-Seam Fastball':'#FF007D'})
+dict_pitch_name.update({'4-Seam':'#FF007D'})
+
+
+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(6, ui.input_select('year_input', 'Select Season', year_list, selected=2024)),
+                ui.column(6, ui.input_select('level_input', 'Select Level', level_dict))
+            ),
+            # 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'))),
+
+            ui.row(
+                ui.column(6, ui.input_select('split_id', 'Select Split', split_dict, multiple=False)),
+            ),
+            # Row for the action button to generate plot
+            ui.row(ui.input_action_button("generate_plot", "Generate Plot", class_="btn-primary")),
+            ui.row(ui.input_action_button("generate_table", "Generate Table", class_="btn-warning")),
+            
+        ),
+
+                
+        ui.panel_main(
+            # ui.navset_tab(
+                # Tab for game summary plot
+                # ui.nav(
+                    # "Pitching Summary",
+ui.card(
+    {"style": "width: 870px;"},
+    ui.head_content(
+        ui.tags.script(src="https://cdnjs.cloudflare.com/ajax/libs/d3/7.8.5/d3.min.js"),
+        ui.tags.script("""
+        async function downloadSVG() {
+            const content = document.getElementById('capture-section');
+            
+            // Create a new SVG element
+            const svg = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
+            const bbox = content.getBoundingClientRect();
+            
+            // Set SVG attributes
+            svg.setAttribute('width', bbox.width);
+            svg.setAttribute('height', bbox.height);
+            svg.setAttribute('viewBox', `0 0 ${bbox.width} ${bbox.height}`);
+            
+            // Create foreignObject to contain HTML content
+            const foreignObject = document.createElementNS('http://www.w3.org/2000/svg', 'foreignObject');
+            foreignObject.setAttribute('width', '100%');
+            foreignObject.setAttribute('height', '100%');
+            foreignObject.setAttribute('x', '0');
+            foreignObject.setAttribute('y', '0');
+            
+            // Clone the content and its styles
+            const clonedContent = content.cloneNode(true);
+            
+            // Add necessary style context
+            const style = document.createElement('style');
+            Array.from(document.styleSheets).forEach(sheet => {
+                try {
+                    Array.from(sheet.cssRules).forEach(rule => {
+                        style.innerHTML += rule.cssText + '\\n';
+                    });
+                } catch (e) {
+                    console.warn('Could not access stylesheet rules');
+                }
+            });
+            
+            // Create a wrapper div to hold styles and content
+            const wrapper = document.createElement('div');
+            wrapper.appendChild(style);
+            wrapper.appendChild(clonedContent);
+            
+            foreignObject.appendChild(wrapper);
+            svg.appendChild(foreignObject);
+            
+            // Convert to SVG string with XML declaration and DTD
+            const svgString = new XMLSerializer().serializeToString(svg);
+            const svgBlob = new Blob([
+                '<?xml version="1.0" standalone="no"?>\\n',
+                '<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">\\n',
+                svgString
+            ], {type: 'image/svg+xml;charset=utf-8'});
+            
+            // Create and trigger download
+            const url = URL.createObjectURL(svgBlob);
+            const link = document.createElement('a');
+            link.href = url;
+            link.download = 'plot_and_table.svg';
+            document.body.appendChild(link);
+            link.click();
+            document.body.removeChild(link);
+            URL.revokeObjectURL(url);
+        }
+        
+        $(document).on('click', '#capture_btn', function() {
+            downloadSVG();
+        });
+        """)
+    ),
+    ui.output_text("status"),
+    ui.div(
+        {
+            "id": "capture-section",
+            "style": "background-color: white; padding: 0; margin-left: 20px; margin-right: 20px; margin-top: 20px; margin-bottom: 20px;"  # Added margin-right
+        },
+        # Plot section with relative positioning for brush
+        ui.div(
+            {"style": "position: relative;"},
+            ui.output_ui("plot_ui")
+        ),
+        # Table section
+        ui.div(
+            {"style": "margin-top: 20px;"},
+            ui.row(ui.tags.b("Pitches in Selection"), ui.output_table("in_brush")),
+            
+
+        ),
+        ui.div({"style": "height: 20px;"}) 
+    ),
+    ui.input_action_button("capture_btn", "Save as SVG", class_="btn-primary"),
+)
+            #     ),
+            # )
+        )
+    )
+)
+
+
+def server(input, output, session):
+
+    @reactive.calc
+    @reactive.event(input.pitcher_id, input.date_id,input.split_id)
+    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)
+
+        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')
+            ))
+        
+        df = df.with_columns(
+            prop_percent=(pl.col('is_pitch') / pl.col('is_pitch').sum()).over("pitch_type"),
+            prop=pl.col('is_pitch').sum().over("pitch_type")
+        )
+
+        return df
+
+    @render.ui
+    @reactive.event(input.player_button, input.level_input,input.year_input, ignore_none=False)
+    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())).filter(
+            pl.col("position").is_in(['P'])).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)
+
+    @render.ui
+    @reactive.event(input.player_button,input.pitcher_id,input.year_input, ignore_none=False)
+    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())}-03-31",
+                                   min=f"{int(input.year_input())}-01-01",
+                                    max=f"{int(input.year_input())}-12-31")
+    @output
+    @render.text
+    def status():
+        # Only show status when generating
+        if input.generate == 0:
+            return ""
+        return ""   
+
+    @render.ui
+    @reactive.event(input.generate_plot)   
+    def plot_ui():
+        brush_opts_kwargs = {}
+        brush_opts_kwargs["direction"] = 'xy'
+        brush_opts_kwargs["delay"] = 60  # Optional: adds a small delay for better performance
+        brush_opts_kwargs["delay_type"] = "throttle"
+        
+    
+        return ui.output_plot('plot', 
+                            width='800px', 
+                            height='800px',
+                            brush=ui.brush_opts(**brush_opts_kwargs))
+
+    @render.table
+    @reactive.event(input.plot_brush, input.generate_table)  # Note: changed to match the brush ID
+    def in_brush():
+        # if input.plot_brush() is None:  # Note: changed to match the brush ID
+        #     return None
+        brushed_df = pl.DataFrame(brushed_points(
+            cached_data().to_pandas(),
+            input.plot_brush(),
+            xvar="hb",
+            yvar="ivb",
+            all_rows=False
+        ))
+
+    
+        brushed_df_final = (((brushed_df.group_by(['pitcher_id', 'pitch_description'])
+                .agg([
+                    pl.col('is_pitch').drop_nans().count().alias('pitches'),
+                    pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
+                    pl.col('vb').drop_nans().mean().round(1).alias('vb'),
+                    pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
+                    pl.col('hb').drop_nans().mean().round(1).alias('hb'),
+                    pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
+                    pl.col('x0').drop_nans().mean().round(1).alias('x0'),
+                    pl.col('z0').drop_nans().mean().round(1).alias('z0'),
+                    pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
+                ])
+                .with_columns(
+                    (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id'))
+                    # .round(1)
+                    # .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
+                    .alias('proportion')
+                )
+                )).sort('proportion', descending=True).
+                select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
+                                                                "spin_rate", "x0", "z0",'tj_stuff_plus'])
+                .with_columns(
+            pl.when(pl.col("pitch_description") == "Four-Seam Fastball")
+            .then(pl.lit("4-Seam"))
+            .otherwise(pl.col("pitch_description"))
+            .alias("pitch_description")
+        )
+                .rename({
+                    'pitch_description': 'Pitch Type',
+                    'pitches': 'Pitches',
+                    'proportion': 'Prop',
+                    'start_speed': 'Velo',
+                    'ivb': 'iVB',
+                    'hb': 'HB',
+                    'spin_rate': 'Spin',
+                    'x0': 'hRel',
+                    'z0': 'vRel',
+                    'tj_stuff_plus': 'tjStuff+'
+                }))
+        
+        # brushed_df_final = brushed_df_final
+        
+        # print(brushed_df_final)
+       
+        def change_font(val):
+            if val == "Cutter":
+                return "color: red; font-weight: bold;"
+            else:
+                ''
+                return "font-weight: bold;"
+        df_brush_style = (brushed_df_final.to_pandas().style.set_precision(1)
+                          
+                          .set_properties(**{'border': '3 px'},overwrite=False).set_table_styles([{
+            'selector': 'caption',
+            'props': [
+                ('color', ''),
+                ('fontname', 'Century Gothic'),
+                ('font-size', '16px'),
+                ('font-style', 'italic'),
+                ('font-weight', ''),
+                ('text-align', 'centre'),
+                ]
+
+                },{'selector' :'th', 'props':[('font-size', '16px'),('text-align', 'center'),('Height','px'),('color','black'),('border', '1px black solid !important')]},{'selector' :'td', 'props':[('text-align', 'center'),('font-size', '16px'),('color','black')]}],overwrite=False)
+                .set_properties(**{'background-color':'White','index':'White','min-width':'72px'},overwrite=False)
+                .set_table_styles([{'selector': 'th:first-child', 'props': [('background-color', 'white')]}],overwrite=False)
+                .set_table_styles([{'selector': 'tr:first-child', 'props': [('background-color', 'white')]}],overwrite=False)
+                .set_table_styles([{'selector': 'tr', 'props': [('line-height', '20px')]}],overwrite=False)
+                .set_properties(**{'Height': '8px'},**{'text-align': 'center'},overwrite=False)
+                .hide_index()
+                .set_properties(**{'border': '1px black solid !important'})
+                .format('{:.0%}',subset=(brushed_df_final.columns[2]))
+                .format('{:.0f}',subset=(brushed_df_final.columns[6]))
+                .format('{:.0f}',subset=(brushed_df_final.columns[-1]))
+                .set_properties(subset=brushed_df_final.columns, **{'height': '30px'})
+                .set_table_styles([{'selector': 'thead th', 'props': [('height', '30px')]}], overwrite=False)
+                # .set_table_styles([{'selector': 'table', 'props': [('width', '100px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(1)', 'props': [('min-width', '125px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(2)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(3)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(4)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(5)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(6)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(7)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .set_table_styles([{'selector': 'thead th:nth-child(8)', 'props': [('min-width', '40px')]}], overwrite=False)
+                .background_gradient(cmap=cmap_sum,subset = (brushed_df_final.columns[-1]),vmin=80,vmax=120)
+                .applymap(lambda x: f'background-color: {dict_pitch_name.get(x, "")}', subset=['Pitch Type'])
+                
+                                                
+    )
+
+        return df_brush_style
+
+        # return Tabulator(
+        #     brushed_df.to_pandas(),
+        #     table_options=TableOptions(
+        #         height=800,
+        #         resizable_column_fit=True,
+        #     )
+        # )
+        # return brushed_points(
+        #     ((brushed_df.group_by(['pitcher_id', 'pitch_description'])
+        #             .agg([
+        #                 pl.col('is_pitch').drop_nans().count().alias('pitches'),
+        #                 pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
+        #                 pl.col('vb').drop_nans().mean().round(1).alias('vb'),
+        #                 pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
+        #                 pl.col('hb').drop_nans().mean().round(1).alias('hb'),
+        #                 pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
+        #                 pl.col('x0').drop_nans().mean().round(1).alias('x0'),
+        #                 pl.col('z0').drop_nans().mean().round(1).alias('z0'),
+        #                 pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
+        #             ])
+        #             .with_columns(
+        #                 (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id') * 100)
+        #                 .round(1)
+        #                 .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
+        #                 .alias('proportion')
+        #             )
+        #             )).sort('proportion', descending=True).
+        #             select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
+        #                                                            "spin_rate", "x0", "z0",'tj_stuff_plus'])
+        #             .rename({
+        #                 'pitch_description': 'Pitch Type',
+        #                 'pitches': 'Pitches',
+        #                 'proportion': 'Proportion',
+        #                 'start_speed': 'Velocity',
+        #                 'ivb': 'iVB',
+        #                 'hb': 'HB',
+        #                 'spin_rate': 'Spin Rate',
+        #                 'x0': 'hRel',
+        #                 'z0': 'vRel',
+        #                 'tj_stuff_plus': 'tjStuff+'
+        #             }).to_pandas(),
+        #             input.plot_brush(),  # Note: changed to match the brush ID
+        #             xvar="HB",  # Replace "x" with your actual x-axis column name
+        #             yvar="iVB",  # Replace "y" with your actual y-axis column name
+        #             all_rows=False
+        # )
+       
+        
+
+        # return brushed_points(
+        #     ((cached_data().group_by(['pitcher_id', 'pitch_description'])
+        #             .agg([
+        #                 pl.col('is_pitch').drop_nans().count().alias('pitches'),
+        #                 pl.col('start_speed').drop_nans().mean().round(1).alias('start_speed'),
+        #                 pl.col('vb').drop_nans().mean().round(1).alias('vb'),
+        #                 pl.col('ivb').drop_nans().mean().round(1).alias('ivb'),
+        #                 pl.col('hb').drop_nans().mean().round(1).alias('hb'),
+        #                 pl.col('spin_rate').drop_nans().mean().round(0).alias('spin_rate'),
+        #                 pl.col('x0').drop_nans().mean().round(1).alias('x0'),
+        #                 pl.col('z0').drop_nans().mean().round(1).alias('z0'),
+        #                 pl.col('tj_stuff_plus').drop_nans().mean().round(0).alias('tj_stuff_plus'),
+        #             ])
+        #             .with_columns(
+        #                 (pl.col('pitches') / pl.col('pitches').sum().over('pitcher_id') * 100)
+        #                 .round(1)
+        #                 .map_elements(lambda x: f"{x}%", return_dtype=pl.Utf8)  # Properly append "%"
+        #                 .alias('proportion')
+        #             )
+        #             )).sort('proportion', descending=True).
+        #             select(["pitch_description", "pitches", "proportion", "start_speed", "ivb", "hb",
+        #                                                            "spin_rate", "x0", "z0",'tj_stuff_plus'])
+        #             .rename({
+        #                 'pitch_description': 'Pitch Type',
+        #                 'pitches': 'Pitches',
+        #                 'proportion': 'Prop',
+        #                 'start_speed': 'Velocity',
+        #                 'ivb': 'iVB',
+        #                 'hb': 'HB',
+        #                 'spin_rate': 'Spin Rate',
+        #                 'x0': 'hRel',
+        #                 'z0': 'vRel',
+        #                 'tj_stuff_plus': 'tjStuff+'
+        #             }).to_pandas(),
+        #             input.plot_brush(),  # Note: changed to match the brush ID
+        #             xvar="HB",  # Replace "x" with your actual x-axis column name
+        #             yvar="iVB",  # Replace "y" with your actual y-axis column name
+        #             all_rows=False
+        # )
+    # @output
+    @render.plot
+    @reactive.event(input.generate_plot)   
+    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...")
+
+
+            ploter.final_plot(
+                df=df,
+                pitcher_id=player_input,
+                plot_picker='short_form_movement',#plot_picker,
+                sport_id=sport_id)
+
+  
+            # #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)
+
+            # # 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)
+
+            # fig.savefig('test.svg')
+            
+            
+
 app = App(app_ui, server)