Thank you for your interest !
Steps for contributing#
Master branch in the repository houses the code that has been completely tested and is bug free to the best of out knowledge. If you encounter a bug in the code, please raise an issue in the repository.
Addressing bug fix#
Fork the repository and clone it into your local machine
git clone https://github.com/kLabUM/pystorms cd pystorms
Create a new branch with your or just
For example, I am fixing a issue with the pollutant, I would create a new branch using this command.
git checkout -b abhiramm7_pollutantfix
Add you fixes and push the changes into your fork of the repository.
git add <your changed files> git push origin abhiramm7_pollutantfix
Once you confident on the changes, you can create a pull request on the benchmarking repository.
We can then work though the pull request.
Please create a unit test for the code addition or any contribution you
wish make to the library. This repository uses
pytest for testing.
Unit tests can be found in the
Details on where to include what#
This file provides access to the input files available in the network. So if you were to add a new network to the library, you would do the following.
Add your processed input file (refer to building scenario on how to process your input file) to the networks folder. Once you add your network to the library, it would be public. So please be carefull on what you upload
Once the file has been updated to the networks folder, add the reference to the name in the
... elif name="<your network>" path = os.path.join(HERE, 'networks/<your network>.inp')
Add test to the
network = benchmarking.networks.load_network("<your name>") assert("inp"= == network[-3:])
Any general function you might need in developing scenarios would be
For example, we use
append_rainfall function for adding rainfall
timeseries to input files. This can be used on any input file and is
not specific to a particular scenario. Hence, this function would be in
This contains the main scenarios used for testing control algorithms. Refer to building scenarios for more details on how to build a scenario.
Anything that is specific to a network or scenario would go here.
All the configuration files, like the input file, state and action space, and performance metrics are placed in this file. Create a new file for the scenario you are creating.
# Configuration file for scenario theta # swmm inp file swmm_input: theta # state definitions states: - !!python/tuple - P1 - depthN - !!python/tuple - P2 - depthN # Action space action_space: - "1" - "2" # Performance Targets performance_targets: - !!python/tuple - "8" - flow - !!python/tuple - P1 - flooding - !!python/tuple - P2 - flooding