Track Brake Zones

import tif1
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np

# Load session
session = tif1.get_session(2023, 'Monza', 'Q')
fastest_lap = session.laps.pick_fastest()

# Get telemetry
telemetry = fastest_lap.get_car_data()

# Extract position and brake
x = telemetry['X']
y = telemetry['Y']
brake = telemetry['Brake']

# Prepare segments
points = np.array([x, y]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)

# Create plot
fig, ax = plt.subplots(figsize=(12, 10))

# Color-coded by brake (binary)
norm = plt.Normalize(0, 1)
lc = LineCollection(segments, cmap='RdYlGn_r', norm=norm, linewidth=4)
lc.set_array(brake)
line = ax.add_collection(lc)

# Colorbar
cbar = plt.colorbar(line, ax=ax, label='Brake', ticks=[0, 1])
cbar.ax.set_yticklabels(['Off', 'On'])

# Format
ax.set_aspect('equal')
ax.axis('off')
plt.suptitle(f"{session.event['EventName']} {session.event.year} - Brake Zones")
plt.tight_layout()
plt.show()

import tif1

# Custom colormap, saved directly to a file
fig, ax = tif1.plot_track_brake_zones(
    2023, 'Monza', 'Q',
    cmap='coolwarm',
    save_path='track_brake_zones.png',
    dpi=300,
)
plt.show()

import tif1
import matplotlib.pyplot as plt

# One call: loads the session and highlights the braking zones
fig, ax = tif1.plot_track_brake_zones(2023, 'Monza', 'Q')
plt.show()

# Or save straight to a file
# tif1.plot_track_brake_zones(2023, 'Monza', 'Q', save_path='track_brake_zones.png')

import tif1

# Compare the fastest laps of several drivers
fig, ax = tif1.plot_speed_traces(2023, 'Spanish Grand Prix', 'Q', drivers=['VER', 'HAM'])
plt.show()