Track Speed Map

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

# Load qualifying session
session = tif1.get_session(2023, 'Monaco', 'Q')

# Get the fastest lap
fastest_lap = session.laps.pick_fastest()

# Get telemetry data
telemetry = fastest_lap.get_car_data()

# Extract position coordinates
x = telemetry['X']
y = telemetry['Y']
speed = telemetry['Speed']

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

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

# Create line collection with speed-based colors
norm = plt.Normalize(speed.min(), speed.max())
lc = LineCollection(segments, cmap='plasma', norm=norm, linewidth=4)
lc.set_array(speed)

# Add to plot
line = ax.add_collection(lc)

# Add colorbar
cbar = plt.colorbar(line, ax=ax, label='Speed (km/h)')

# Format plot
ax.set_aspect('equal')
ax.axis('off')

plt.suptitle(f"{session.event['EventName']} {session.event.year} - Fastest Lap Speed Map")
plt.tight_layout()
plt.show()

# Get circuit information
circuit_info = session.get_circuit_info()

# Add corner markers
for _, corner in circuit_info.corners.iterrows():
    ax.scatter(corner['X'], corner['Y'], color='white', s=100,
               edgecolors='black', linewidth=2, zorder=10)
    ax.text(corner['X'], corner['Y'], f"{corner['Number']}",
            ha='center', va='center', fontsize=8, fontweight='bold')

import tif1

# Custom colormap, saved straight to a file
fig, ax = tif1.plot_track_speed_map(
    2023, 'Monaco', 'Q',
    cmap='viridis',
    save_path='track_speed_map.png',
    dpi=300,
)
plt.show()

import tif1
import matplotlib.pyplot as plt

# One call: loads the session and draws the speed-colored track map
fig, ax = tif1.plot_track_speed_map(2023, 'Monaco', 'Q')
plt.show()

# Or save straight to a file
# tif1.plot_track_speed_map(2023, 'Monaco', 'Q', save_path='track_speed_map.png')