F1-lap-time-telementary 0.2.0

Plot F1 telemetry data using FastF1

F1_lap_time_telementary

This module is created to easily visualize telementary data of the fastest lap from a session. It heavily uses the great FastF1 API below - https://github.com/theOehrly/Fast-F1/tree/master

This document goes through all available API functions, if you just want a quick way to plot then review the plot_comparison function

Installation

pip install F1-lap-time-telementary

API Functions

plot_comparison

Creates a telementary for two drivers in any session

Inputs

year - Year of the race as an integer gp - The full name of the gp as a string session_type - Abbreviated session names, mapped as the following:

session_type	Session
'FP1'	Free Practice 1
'FP2'	Free Practice 2
'FP3'	Free Practice 3
'SQ'	Sprint Qualifying
'SS'	Sprint Shootout
'Q'	Qualifying
'S'	Sprint
'R'	Race

drivers - A list of two drivers with their 3 letter abbreviation. E.g. ['ALO', 'STR']

Outputs

A matplotlib plot of the telementary data of two drivers

Usage

from F1_lap_time_telementary import plot_comparison
plot_comparison(
    year=2025,
    grand_prix='Chinese Grand Prix',
    session_type='Q',
    drivers=['ALO', 'STR']
)

setup_plotting

Calls fastf1.plotting.setup_mpl from FastF1 to configure the plot

Inputs

No inputs

Output

Setup matplotlib for use with fastf1 - Nothing returned from the function

Usage

from F1_lap_time_telementary import setup_plotting

setup_plotting()

get_session_data

Gets the session data from FastF1

Inputs

year - Year of the race as an integer gp - The full name of the gp as a string session_type - Abbreviated session names, mapped as the following:

session_type	Session
'FP1'	Free Practice 1
'FP2'	Free Practice 2
'FP3'	Free Practice 3
'SQ'	Sprint Qualifying
'SS'	Sprint Shootout
'Q'	Qualifying
'S'	Sprint
'R'	Race

Note Sprint Shootout is for 2023 only

Outputs

session - Returns a session object

Usage

from F1_lap_time_telementary import get_session_data

year = 2025
grand_prix = 'Chinese Grand Prix'
session_type='Q'
session = get_session_data(year, grand_prix, session_type)

get_driver_data

Returns the telementary data from the driver's fastest lap

Inputs

session - A session object (which can be obtained by running get_session_data) driver - Three letter abbreviation for a driver. E.g. 'BOT' for Bottas

Output

lap - The fastest lap set by the driver in that session car_data - telementary data from the fastest lap

Usage

from F1_lap_time_telementary import get_driver_data

session = get_session_data(2025, 'Chinese Grand Prix', 'Q')
driver = 'ALO'
lap, car_data = get_driver_data(session, driver)

get_min_max_speed

Gets the minimum and maximum speed by the driver

Inputs

car_data - Telementary Data from the car (which can be obtained by running get_driver_data)

Outputs

min_speed - Slowest speed of the car in a lap max_speed - Top speed of the car in a lap

Usage

from F1_lap_time_telementary import get_min_max_speed

min_speed, max_speed = get_min_max_speed(car_data)

plot_corners

Plots corner lines in a speed-distance plot

Inputs

ax - Axes circuit_data - Circuit Data (Obtained by session.get_circuit_info) car_data - Telementary Data from the car (which can be obtained by running get_driver_data)

Outputs

No output - Adds vertical dashed lines on a speed-distance plot

Usage

from F1_lap_time_telementary import get_min_max_speed

plot_corners(axs[0], circuit_data, car_data)

plot_telemetry

Plots telementry data 4 subplots -

1. Speed-Distance
2. Throttle-Distance
3. Brake-Distance
4. Gear-Distance

Inputs

axs - The axes you are plotting on car_data - Telementary Data from the car (which can be obtained by running get_driver_data) label - The driver's trace that is being plotted

Outputs

Nothing returned - plots a (4,1) subplot

Usage

from F1_lap_time_telementary import plot_telemetry
lap, car_data = get_driver_data('Q', 'ALO')
plot_telemetry(axs, car_data, lap)

label_axes

Labels the axes

Inputs

axs - The axes to label labels - The y axes labels for the subplots

Outputs

No output - Axes labelled

Usage

from F1_lap_time_telementary import label_axes
labels = ['Speed [km/h]', 'Throttle [%]', 'Brake [%]', 'Gear']
label_axes(axs,labels)

add_legends

Adds legend to each subplot

Inputs

axs - The axes to add legends

Outputs

No output - Each subplot has a legend

Usage

from F1_lap_time_telementary import add_legends
add_legends(axs)

set_title

Adds title to the plot

Inputs

axs - The axes to add a title title - The title you want to add

Outputs

No output - Title added to the plot

Usage

from F1_lap_time_telementary import set_title
set_title(axs, "Qualifying Comparison")