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Overlaying speed traces of two laps¶
Compare two fastest laps by overlaying their speed traces.
import matplotlib.pyplot as plt
import fastf1.plotting
# Enable Matplotlib patches for plotting timedelta values and load
# FastF1's dark color scheme
fastf1.plotting.setup_mpl(mpl_timedelta_support=True, misc_mpl_mods=False,
color_scheme='fastf1')
# load a session and its telemetry data
session = fastf1.get_session(2021, 'Spanish Grand Prix', 'Q')
session.load()
First, we select the two laps that we want to compare
ver_lap = session.laps.pick_driver('VER').pick_fastest()
ham_lap = session.laps.pick_driver('HAM').pick_fastest()
Next we get the telemetry data for each lap. We also add a ‘Distance’ column to the telemetry dataframe as this makes it easier to compare the laps.
ver_tel = ver_lap.get_car_data().add_distance()
ham_tel = ham_lap.get_car_data().add_distance()
Finally, we create a plot and plot both speed traces. We color the individual lines with the driver’s team colors.
rbr_color = fastf1.plotting.get_team_color(ver_lap['Team'], session=session)
mer_color = fastf1.plotting.get_team_color(ham_lap['Team'], session=session)
fig, ax = plt.subplots()
ax.plot(ver_tel['Distance'], ver_tel['Speed'], color=rbr_color, label='VER')
ax.plot(ham_tel['Distance'], ham_tel['Speed'], color=mer_color, label='HAM')
ax.set_xlabel('Distance in m')
ax.set_ylabel('Speed in km/h')
ax.legend()
plt.suptitle(f"Fastest Lap Comparison \n "
f"{session.event['EventName']} {session.event.year} Qualifying")
plt.show()
![Fastest Lap Comparison Spanish Grand Prix 2021 Qualifying](../../_images/sphx_glr_plot_speed_traces_001.png)
Total running time of the script: (0 minutes 1.791 seconds)