You can contribute to the Reflectivity Algorithms Toolbox (RAT) project by either opening an issue (please check that the issue has not been reported already) or submitting a pull request.
The MATLAB IDE is recommended for development, the following toolboxes are required for RAT:
- MATLAB Coder
- MATLAB Compiler
- Parallel Computing Toolbox
- Statistics and Machine Learning Toolbox (for DREAM Minimizer)
After installing the IDE, proceed by creating a fork of the RAT repo, then clone the fork
git clone --recurse-submodules https://github.com/<username>/RAT.git
cd RAT
And finally create a separate branch to begin work
git checkout -b new-feature
Commit changes with brief but clear commit messages and once feature is complete submit a pull request via GitHub. Ensure to rebase your branch to include the latest changes on your branch and resolve possible merge conflicts.
If you have cloned the repository previously, you may need to update the submodules to get the 3rdParty repos
git submodule update --init --recursive
Proper documentation and unit tests is highly recommended. To run unit tests and generate coverage report use TestRATScript.m. The code coverage report should be generated to a htmlcov folder after the tests are completed.
The documentation source code is in the RAT_docs repository but the built docs are deployed at https://rascalsoftware.github.io/RAT/