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from shiny import App, ui, render, reactive
from shinywidgets import output_widget, render_widget
import fastf1 as ff1
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib import cm
import numpy as np
ff1.Cache.enable_cache('./cache')
app_ui = ui.page_fluid(
ui.div(
ui.input_select(
"track", label="Track",
choices=["Austria", "Hungary"]
),
class_="d-flex gap-3"
),
ui.output_plot("gear")
)
def server(input, output, session):
@reactive.Calc
def get_data():
session = ff1.get_session(2023, input.track, 'R')
session.load()
lap = session.laps.pick_fastest()
tel = lap.get_telemetry()
#converting data to numpy data tables
x = np.array(tel['X'].values)
y = np.array(tel['Y'].values)
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
gear = tel['nGear'].to_numpy().astype(float)
return lap, tel, x, y, points, segments, gear
@output
@render.plot
def gear():
lap = get_data().lap
tel = get_data().tel
points = get_data().points
segments = get_data().segments
cmap = cm.get_cmap('Paired')
lc_comp = LineCollection(segments, norm=plt.Normalize(1, cmap.N+1), cmap=cmap)
lc_comp.set_array(gear)
lc_comp.set_linewidth(4)
plt.gca().add_collection(lc_comp)
plt.axis('equal')
plt.tick_params(labelleft=False, left=False, labelbottom=False, bottom=False)
##title = plt.suptitle(
## f"Fastest Lap Gear Shift Visualization\n"
## f"{lap['Driver']} - {session.event['EventName']} {session.event.year}"
## )
cbar = plt.colorbar(mappable=lc_comp, label="Gear", boundaries=np.arange(1, 10))
cbar.set_ticks(np.arange(1.5, 9.5))
cbar.set_ticklabels(np.arange(1, 9))
return plt
app = App(app_ui, server) |