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 import matplotlib 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(src="https://html2canvas.hertzen.com/dist/html2canvas.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([ '\\n', '\\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); } async function downloadPNG() { const content = document.getElementById('capture-section'); try { // Create a wrapper div with margins const wrapper = document.createElement('div'); wrapper.style.padding = '20px'; wrapper.style.backgroundColor = 'white'; // Clone the content const clonedContent = content.cloneNode(true); wrapper.appendChild(clonedContent); // Add wrapper to document temporarily document.body.appendChild(wrapper); const canvas = await html2canvas(wrapper, { backgroundColor: 'white', scale: 2, useCORS: true, logging: false, width: content.offsetWidth + 40, // Add padding width height: content.offsetHeight + 40 // Add padding height }); // Remove temporary wrapper document.body.removeChild(wrapper); // Convert canvas to blob canvas.toBlob(function(blob) { const url = URL.createObjectURL(blob); const link = document.createElement('a'); link.href = url; link.download = 'plot_and_table.png'; document.body.appendChild(link); link.click(); document.body.removeChild(link); URL.revokeObjectURL(url); }, 'image/png'); } catch (error) { console.error('Error generating PNG:', error); } } $(document).on('click', '#capture_svg_btn', function() { downloadSVG(); }); $(document).on('click', '#capture_png_btn', function() { downloadPNG(); }); """) ), 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;" }, # 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.div( {"style": "display: flex; gap: 10px;"}, ui.input_action_button("capture_svg_btn", "Save as SVG", class_="btn-primary"), ui.input_action_button("capture_png_btn", "Save as PNG", class_="btn-success"), ), ) # ), # ) ) ) ) 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 = { "direction": 'xy', "delay": 60, "delay_type": "throttle", "clip": True, # This helps constrain the brush to the plot area "fill": "#00000033", # Optional: sets a semi-transparent fill "stroke": "#000000", # Resets brush when new data is loaded } 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...") # fig, ax = plt.subplots(figsize=(8, 8)) ploter.final_plot( df=df, pitcher_id=player_input, plot_picker='short_form_movement',#plot_picker, sport_id=sport_id) # # Adjust the plot layout after creation # plt.subplots_adjust( # top=0.95, # Reduce top margin # bottom=0.1, # Increase bottom margin # left=0.1, # Increase left margin # right=0.95 # Reduce right margin # ) # #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)