import fastf1 as ff1
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib import cm
import numpy as np
import pandas as pd


ff1.Cache.enable_cache('.\cache')

session = ff1.get_session(2023, 'Austria', '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)

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))


plt.show()

lap_time = lap['LapTime']

def format_timedelta(td):
    delta_str= str(td)
    # Split the time delta string to extract hours, minutes, and seconds
    time_parts = delta_str.split(" ")[-1].split(":")
    hours, minutes, seconds = map(float, time_parts)

    # Convert the extracted values to the desired format
    formatted_time = "{:02d}:{:06.3f}".format(int(hours * 60 + minutes), seconds)

    return f"The lap time is: {formatted_time}"

print(format_timedelta(lap_time))