This branch of Retro-GTFS application is designed to process real-time transit data from an archived GTFS-Realtime data set into a "retrospective" or "retroactive" GTFS package. Schedule-based GTFS data describes how transit is expected to operate. This produces GTFS that describes how it did operate. The output is not useful for routing actual people on a network, but can be used for a variety of analytical purposes such as comparing routing/accessibility outcomes on the schedule-based vs the retrospective GTFS datasets. Measures can be derived showing the differences between the schedule and the actual operations and these could be interpreted as a measure of performance either for the GTFS package (does it accurately describe reality?) or for the agency in question (do they adhere to their schedules?).
In short, the main difference between the main branch and this branch is that the former collects and processes data from the NextBus API while the later processes data from archived GTFS-Realtime data. An example of an archived database of GTFS-Realtime data can be found here.
trip_id for all trips and using calendar_dates.txt with exception_type=1. (More details coming)NOTE: the wiki page contains instructions for the main branch. Here are instructions for this branch.
Python3
Python modules described in the requirements.txt file. You can simply run pip install -r requirements.txt
An OSRM-backend server, local or otherwise.
A server of archived GTFS-Realtime data that can be queried through HTTP request. An example of such a server is the Transi project. The API calls are currently hard-coded, so this program is only compatible with the Transi project. However, you can also modify the code so that the program works with your own archived data system, such as a collection of GTFS-Realtime files on disk. Instruction to modify the code is [below](#Modifying the Code).
If you would like to access our data or need help setting up the server, please feel free to contact us.
Change the file name of [sample conf.py](./sample conf.py) into conf.py, then go through the conf.py file and save information for your Postgres database, OSRM server, and API URL.
python main.py "<from date>" "<to date>" where dates have format "mm/dd/yyyy"
For example, python main.py "05/16/2018" "06/16/2018"
Output: ./output/individuals would contain daily retro-GTFS files, ./output/aggregated would contain aggregated retro-GTFS bundle.
If you would like to use a different data system other than the Transi project, such as a server with different API syntaxes or a collection of files on disk, you will need to modify the two script files GetGTFS.py and GetGTFSRT.py scripts. The purposes for these two files are to load GTFS and GTFS-Realtime data respectively. For each file, you can find the instructions in the description of the execute function (first function in each file).
If you need help, please feel free to contact us.
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