Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How to interpret the data. #2

Open
cike0cop opened this issue Apr 13, 2017 · 1 comment
Open

How to interpret the data. #2

cike0cop opened this issue Apr 13, 2017 · 1 comment

Comments

@cike0cop
Copy link

Hi.I don't know how to organization the data of mine.How to interpret your data field?

my data example.
RCStation Start_Time Direction Lane Count
3703 10/04/2015 00:00 1 1 2
3703 10/04/2015 00:01 1 1 6
3703 10/04/2015 00:02 1 1 0
3703 10/04/2015 00:03 1 1 3
3703 10/04/2015 00:04 1 1 3

timestamp,16,17,18,19,20,21
2011-12-31 23:55:00,4,6,8,13,3,0
2012-01-01 00:00:00,5,7,8,10,3,2
2012-01-01 00:05:00,3,3,7,15,1,2
2012-01-01 00:10:00,9,3,3,7,1,1
2012-01-01 00:15:00,3,4,12,15,2,0
2012-01-01 00:20:00,7,5,11,19,2,2

Is the traffic flow?

@JonnoFTW
Copy link
Owner

This project isn't really for general use, you can see how the data is interpreted in this function here:

https://github.com/JonnoFTW/traffic-prediction/blob/master/utils.py#L55

My data format has timestamp followed by vehicle counts for each lane, the lanes are identified by 16,17,18 etc.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants