[Question and Suggestion]

[TempBet]

Hi, how can I make a Boxplot of the times with a type of rubber? I tried, but he tells me he doesn't accept timedelta

Also, is it possible to implement a function for the SpeedDelta?

[theOehrly]

Try to convert the timedelta values to seconds maybe. I think timedelta.dt.total_seconds() should do that.

Matplotlib doesn't like the timedelta data type.

What exactly do you mean with speed delta?

[TempBet]

Thanks for the reply. I mean a function similar to Timedelta, only that it traces the line of the difference between the speeds of two drivers.

I don't know if I explained myself well

[theOehrly]

I am planning to implement something like that, yes. In theory, you only need to "subtract" the two laps. But it is not actually that easy. To do this properly, you need to compare the time difference in relation to the on-track position. This means a relation between time and covered lap distance needs to be made first. Furthermore, this needs to be very exact if we want the data to be meaningful.

[TempBet]

Another question: is it possible to put an example on the documentation of how the Track class works, and what can you actually do with it?

[theOehrly]

Currently, there is "Distance to Driver Ahead" available as a calculated additional info. It is somewhat complicated to calculate this.

The track class is intended to serve as a more universal interface for calculating things like this.

There should be a better documentation, yes. But due to some changes to the position data by F1, it does not work with the 2020 season. Some major changes are necessary to make it work again. And I'm not motivated to write documentation for something that doesn't work anymore and needs to be changed anyways.

Maybe I'll add a more obvious notice about the fact that it doesn't work anymore.

[theOehrly]

Thanks for the reply. I mean a function similar to Timedelta, only that it traces the line of the difference between the speeds of two drivers.

I don't know if I explained myself well

Maybe you are interested in this:

https://theoehrly.github.io/Fast-F1/utils.html#fastf1.utils.delta_time

It's the delta time not the delta speed though.

I merged this while integrating a newer version of the original codebase. I have not tried or tested it really so I can not speak to the accuracy of the result.

[TempBet]

ahhh ok. I don't see it on the documentation.

another question. Is it possible to add (always if not already there) the possibility to plot the circuit and highlight the microsectors?

I am attaching an image that is perhaps self-explanatory.

Is it also possible to add the difference in speed between two cars at a point in the plot?

[theOehrly]

Both of these things should be possible. But there's currently no easy way to do this. I very much want to add functionality to do this. But I probably won't get to it very soon.

[TerminatorPlati]

Hello. I use this issue to ask a question without opening another one.is it possible to do the plotting of all the telemetry for all the laps of the race for example? let me explain if I want to see the graph of the speed of the car for the whole length of the race, how can I do?

[theOehrly]

If I understand you right, this is what you are looking for:

import fastf1 as ff1
import matplotlib.pyplot as plt

session = ff1.get_session(2020, 5, 'R')
session.load_laps()

lec = session.car_data['16']

plt.figure()
plt.plot(lec['Time'], lec['Speed'])
plt.show()

And the 'Space' data is not available here. You can only use 'Time' as a reference.

This is not documented but should be. I'll add it to the ToDo list.

[TerminatorPlati]

If I understand you right, this is what you are looking for:

import fastf1 as ff1
import matplotlib.pyplot as plt

session = ff1.get_session(2020, 5, 'R')
session.load_laps()

lec = session.car_data['16']

plt.figure()
plt.plot(lec['Time'], lec['Speed'])
plt.show()

And the 'Space' data is not available here. You can only use 'Time' as a reference.

This is not documented but should be. I'll add it to the ToDo list.

Uhm, me it doesn't work.

[theOehrly]

If I understand you right, this is what you are looking for:

import fastf1 as ff1
import matplotlib.pyplot as plt

session = ff1.get_session(2020, 5, 'R')
session.load_laps()

lec = session.car_data['16']

plt.figure()
plt.plot(lec['Time'], lec['Speed'])
plt.show()

And the 'Space' data is not available here. You can only use 'Time' as a reference.
This is not documented but should be. I'll add it to the ToDo list.

Uhm, me it doesn't work.

This really should work. Did you run exactly the example code for a test? You need to call load_laps() else you will get the error that you are getting.
I just tested it again in a fresh venv with a fresh install from master and it did work.

[TerminatorPlati]

This really should work. Did you run exactly the example code for a test? You need to call load_laps() else you will get the error that you are getting.
I just tested it again in a fresh venv with a fresh install from master and it did work.

ok, found why it didn't work. if it has enabled fast-f1 cache, the program breaks. (I already had the data of the race in question in the cache folder)

[theOehrly]

Yes, that makes sense. The cache is not very intelligent currently in that regard and does not get updated.

[TerminatorPlati]

Hi, why are there no telemetric data and LapTime of the first lap of each race? API problem? Or FastF1 problem?

[theOehrly]

@theOllieS that looks really nice. Were you able to somehow verify the accuracy of your results?

[theOllieS]

@theOllieS that looks really nice. Were you able to somehow verify the accuracy of your results?

This is not corresponding to the minisectors that may show on the F1 app, this simply divides the circuit up into equal distance sectors and shows the driver with the highest average speed within that sector. At the moment I am only taking the drivers' best laptime from the session.

I'm not sure how to accurately verify this.

[theOllieS]

@hash55 @siddharth-tewari I am thinking of posting a repository on my profile, maybe that will work.

[siddharth-tewari]

@theOllieS Ok, Thank You

[hash55]

@theOllieS Yup, thanks!

[theOehrly]

This is not corresponding to the minisectors that may show on the F1 app, this simply divides the circuit up into equal distance sectors and shows the driver with the highest average speed within that sector. At the moment I am only taking the drivers' best laptime from the session.

I'm not sure how to accurately verify this.

@theOllieS I like the idea of basing this on the highest average speed. I think it might actually yield a pretty good result. But, from experience, I have learned that you should never trust your results without verifying them somehow. I've created good-looking plots that were absolutely wrong in the past. Although, I don't have a good idea right away on how you could verify this.

[hash55]

Here is what I would do. (It's not the best option but an initial estimation.) Instead of loading data of all drivers, it would be nice to load just two of them, specifically the fastest lap of Q3. By doing that, you can compare it with the analysis the official F1 Youtube channel sometimes upload.
For example:
Bottas vs Russell Sakhir 2020

Hamilton vs Vettel USA 2018
At the end of the video, you can see the actual lap with fastest minisectors. As I said before, this is not the best method, because there are only a few comparisons uploaded to YT, but can give you an idea of it.

[theOllieS]

@theOllieS I like the idea of basing this on the highest average speed. I think it might actually yield a pretty good result. But, from experience, I have learned that you should never trust your results without verifying them somehow. I've created good-looking plots that were absolutely wrong in the past. Although, I don't have a good idea right away on how you could verify this.

Agreed, generally I just apply the sanity check of which cars are typically fast in certain mini sector types. For example, Alfa Romeo are normally very fast at the end of straights, Ferrari are strong in slow corners and the acceleration zones out of them, Merc are good on high speed corners etc. The results tend to agree with this.

[theOllieS]

@hash55 thank you for this, I like this idea. I have found some more examples of these on scuderiafans.com from various sessions. I will try and compare my results to these and show you guys where the differences are.

[theOllieS]

@hash55 @theOehrly I have uploaded some of my results and findings from comparing my minisector head to head results to the official F1 data onto my profile https://github.com/theOllieS/F1-Minisectors-Verification/issues/1 if you are interested. There were so many attachments that I didn't want to clog up this discussion thread so I thought my profile might be a better place.

[siddharth-tewari]

@theOehrly Hello, I have a question that when is Young Drivers Test and will it be available to view on TV and will telemetry, lap times etc. be available from Fast-F1?

[theOehrly]

I don't know if it is broadcasted. I wouldn't think so.
The event is not in the official event schedule. Therefore, I assume that there won't be any timing data and telemetry for it.

[theOehrly]

@JSEHV By the way, in case you're reading this, I have finally added one of your cool looking example plots to the examples gallery. Sorry that it took so long. I appreciate the effort that you put into it.

[siddharth-tewari]

@theOehrly Hello, can you fix this if possible?

import fastf1
import fastf1 as ff1

year = input("Enter the Year: ")
race = input("Enter the Race Number/Name: ")

if type(race) == int:
    raceName = race
    
elif type(race) == float:
    raceName = race

elif type(race) == str:
    raceName = "'" + race + "'"

weekend = ff1.get_session(year, raceName)

lap = fastf1.core.Session(weekend, 'Race')
options = fastf1.api.pages= { 'race_control_messages': 'RaceControlMessages.json', 'team_radio': 'TeamRadio.jsonStream'}

link = fastf1.api.fetch_page(lap, 'team_radio')
print(link)

[theOehrly]

You don't need to modify the pages dictionary.
Also, api.fetch_page requires Session.api_path as first argument. You're passing the whole Session object.

[theOehrly]

I have created a discussion now from this very general question and suggestions 'issue' thread.
For any upcoming questions, you should just use the discussion section and open a new discussion for each specific topic.
This discussion will be locked now. Separate topics provide a way better overview.