RIC Q1 Best vs TSU Q1 Best in Hugarian GP Qualify

[TNAKKK]

2023 Hungarian GP Qualify

Can you please tell me how & which part of these codes below need to be changed to see Tsunoda's Q1 best lap (TSU's Lap 5 in Q1 1:18.919) & Ricciardo's Q1 best lap (RIC's Lap 8 in Q1 1:18.906)

Since RIC made himself through to Q2 and TSU didn't, the codes below gets me RIC's Q2 best against TSU's Q1 best. Many thanks!

import fastf1 as ff1
from fastf1 import plotting
from fastf1 import utils

from matplotlib import pyplot as plt
from matplotlib.pyplot import figure

import numpy as np
import pandas as pd

# Enable the cache by providing the name of the cache folder
ff1.Cache.enable_cache('cache')

year, grand_prix, session = 2023, 'HUNGARIAN', 'Q'

quali = ff1.get_session(year, grand_prix, session)
quali.load()  # This is new with Fastf1 v.2.2

# This is how it used to be:
# laps = quali.load_laps(with_telemetry=True)

driver_1, driver_2 = 'RIC', 'TSU'

# Laps can now be accessed through the .laps object coming from the session
laps_driver_1 = quali.laps.pick_driver(driver_1)
laps_driver_2 = quali.laps.pick_driver(driver_2)

# Select the fastest lap
fastest_driver_1 = laps_driver_1.pick_fastest()
fastest_driver_2 = laps_driver_2.pick_fastest()

# Retrieve the telemetry and add the distance column
telemetry_driver_1 = fastest_driver_1.get_telemetry().add_distance()
telemetry_driver_2 = fastest_driver_2.get_telemetry().add_distance()

# Make sure we know the team name for coloring
team_driver_1 = fastest_driver_1['Team']
team_driver_2 = fastest_driver_2['Team']

# Extract the delta time
delta_time, ref_tel, compare_tel = utils.delta_time(fastest_driver_1, fastest_driver_2)

plot_size = [15, 15]
plot_title = f"{quali.event.year} {quali.event.EventName} - {quali.name} - {driver_1} VS {driver_2}"
plot_ratios = [1, 3, 2, 1, 1, 2, 1]
plot_filename = plot_title.replace(" ", "") + ".png"

# Make plot a bit bigger
plt.rcParams['figure.figsize'] = plot_size

# Create subplots with different sizes
fig, ax = plt.subplots(7, gridspec_kw={'height_ratios': plot_ratios})

# Set the plot title
ax[0].title.set_text(plot_title)

# Delta line
ax[0].plot(ref_tel['Distance'], delta_time)
ax[0].axhline(0)
ax[0].set(ylabel=f"Gap to {driver_2} (s)")

# Speed trace
ax[1].plot(telemetry_driver_1['Distance'], telemetry_driver_1['Speed'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[1].plot(telemetry_driver_2['Distance'], telemetry_driver_2['Speed'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[1].set(ylabel='Speed')
ax[1].legend(loc="lower right")

# Throttle trace
ax[2].plot(telemetry_driver_1['Distance'], telemetry_driver_1['Throttle'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[2].plot(telemetry_driver_2['Distance'], telemetry_driver_2['Throttle'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[2].set(ylabel='Throttle')

# Brake trace
ax[3].plot(telemetry_driver_1['Distance'], telemetry_driver_1['Brake'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[3].plot(telemetry_driver_2['Distance'], telemetry_driver_2['Brake'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[3].set(ylabel='Brake')

# Gear trace
ax[4].plot(telemetry_driver_1['Distance'], telemetry_driver_1['nGear'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[4].plot(telemetry_driver_2['Distance'], telemetry_driver_2['nGear'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[4].set(ylabel='Gear')

# RPM trace
ax[5].plot(telemetry_driver_1['Distance'], telemetry_driver_1['RPM'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[5].plot(telemetry_driver_2['Distance'], telemetry_driver_2['RPM'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[5].set(ylabel='RPM')

# DRS trace
ax[6].plot(telemetry_driver_1['Distance'], telemetry_driver_1['DRS'], label=driver_1,
           color=ff1.plotting.team_color(team_driver_1))
ax[6].plot(telemetry_driver_2['Distance'], telemetry_driver_2['DRS'], label=driver_2,
           color=ff1.plotting.team_color(team_driver_2))
ax[6].set(ylabel='DRS')
ax[6].set(xlabel='Lap distance (meters)')

# Hide x labels and tick labels for top plots and y ticks for right plots.
for a in ax.flat:
    a.label_outer()

# Store figure
plt.savefig(plot_filename, dpi=300)
plt.show()

[theOehrly]

If you just want to get the fastest lap, this is simple. You just need to change a small part of your code and use Laps.split_qualifying_sessions() (https://docs.fastf1.dev/core.html#fastf1.core.Laps.split_qualifying_sessions).

This way, you'll get three separate Laps objects. One for each part of qualifying. You can then pick the driver and fastest lap just like before but from Q1 specifically.

Here is what you need to change (only showing the relevant section of your code):

[...]
quali = ff1.get_session(year, grand_prix, session)
quali.load()  # This is new with Fastf1 v.2.2

driver_1, driver_2 = 'RIC', 'TSU'

q1_laps, q2_laps, q3_laps = quali.laps.split_qualifying_sessions()

laps_driver_1 = q1_laps.pick_driver(driver_1)
laps_driver_2 = q1_laps.pick_driver(driver_2)
[...]

[TNAKKK]

Superb! It worked. Thank you!