Skip to content

CONTRIBUTING.md

Latest commit

 

History

History
32 lines (21 loc) · 1.71 KB

CONTRIBUTING.md

File metadata and controls

32 lines (21 loc) · 1.71 KB

Contributing to Toroidal Dynamics Toolkit

Thanks for your interest in contributing! TDT is a modular Python toolkit for dynamic toroidal modulation in frequency-domain signal processing, with a multi-shot real tokamak benchmark suite.

Ways to Contribute

  • Bug reports — open an issue describing the problem, your Python version, and steps to reproduce.
  • Feature requests — open an issue with a clear description of the proposed feature and its relevance to toroidal dynamics or signal processing.
  • Code contributions — fork the repo, make your changes, and submit a pull request.
  • Benchmark data — if you have access to additional tokamak shot data and would like to contribute benchmarks, open an issue or discussion.

Guidelines

  1. Python code — keep dependencies minimal. NumPy and SciPy are acceptable; heavy frameworks should be justified.
  2. Reproducibility — all benchmarks should clearly document their data sources and be reproducible with the provided scripts.
  3. Test before submitting — verify your changes run cleanly with both toroidal_dynamics_toolkit.py and benchmark_multi_shot.py.
  4. Respect the framework — TDT extends the Ψ_universe Attractor Library for real experimental data. Keep that relationship clear in any documentation.

Pull Request Process

  1. Fork and create a feature branch (git checkout -b feature/my-feature).
  2. Make your changes.
  3. Test thoroughly.
  4. Submit a PR with a clear description of what changed and why.

License

By contributing, you agree that your contributions will be licensed under the existing license terms.

Contact

For questions, reach out to Nicolas B. Quiroz, MD via GitHub.