File:Saudi Arabian Grand Prix-2021.png

Own work; In Python:

1. Setup the basics

import fastf1 from fastf1 import plotting

import matplotlib.pyplot as plt from matplotlib.collections import LineCollection from matplotlib import cm

import numpy as np

1. Setup plotting

plotting.setup_mpl()

1. enable the cache

fastf1.Cache.enable_cache('I:\Documents\F1_Cache')

1. Load Session Data

session = fastf1.get_session(2019, "United States Grand Prix", "R") laps = session.load_laps(with_telemetry=True)

lap = laps.pick_fastest() laptime = lap['LapTime'] tel = lap.get_telemetry()

1. Prepare the data for plotting by converting it to the appropriate numpy data types

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)

1. Create a line collection. Set a segmented colormap and normalize the plot to full integer values of the colormap

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)

1. Create the plot

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.weekend.name} {session.weekend.year} - {laptime}"

)

1. Add a colorbar to the plot. Shift the colorbar ticks by +0.5 so that they are centered for each color segment.

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.savefig(f"img\FastestLapGear\{session.weekend.name}-{session.weekend.year}-Gear.png", dpi=300)