Our workflow is set up to allow everyone to contribute "modules" in their preferred programming language (.. as long as that is either R or Python). A module can either be a dataset, a computational method, or an evaluation metric.
This repository contains some templates and examples of how to implement your module so that it interfaces seamlessly with other modules in the workflow. For example, if you want to implement a new method, you do not need to worry about input data or evaluation metrics as long as you follow the template for reading input and writing output - if you correctly adhere to the input and output guidelines, you should be able to interface with our default data modules and default evaluation metrics modules. The default modules are:
Module contribution will be managed via GitHub. The steps to contribute a module are:
data_...
, method_...
or metric_..
. You can create a new branch in several ways: (i) create a branch directly from the issue board and then git checkout
that branch, or (ii) via the command line:
# clone the template repository
git clone https://github.com/SpatialHackathon/SpaceHack2023.git
# create and switch to a new branch for your e.g. method "X"
git branch method_x_naveedishaque # try to make the branch name unique!
git checkout method_x_naveedishaque
# link the branch to the issue via the issue board: https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue
template/
, referring to the examples in the data
, method
, or metric
subfolder. If your method requires a specific type or preprocessing, please reach out to the organisers!Easy!
We have adopted the "MIT No Attribution" (MIT-0) License. It is currently attributed to the "SpaceHack organizers", but please also make sure to add your name to your contributions. More on MIT-0 here