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Contributing to AMBER

Thank you for your interest in contributing! The guidelines below keep the codebase consistent and the review process smooth.

Getting started

git clone https://github.com/albertonogales/AMBER.git
cd AMBER
pip install -e ".[dev]"   # installs runtime + dev dependencies

Run the test suite to make sure everything is green before you start:

pytest

Reporting bugs

Open a GitHub Issue and include:

  1. A minimal reproducible example.
  2. The full traceback.
  3. Your Python version and AMBER version (python -c "import AMBER; print(AMBER.__version__)").

Submitting changes

  1. Fork the repository and create a branch from main: 
    git checkout -b feat/my-feature
  2. Write your code. Keep changes focused — one feature or fix per pull request.
  3. Add or update tests in tests/. The coverage must not drop below 99 %.
  4. Run the full suite before pushing: 
    pytest --tb=short
  5. Open a Pull Request against main with a clear description of what changed and why.

Code style

  • Follow PEP 8.
  • Docstrings use the :param / :return: Sphinx style (see existing code).
  • No inline comments unless the why is non-obvious.
  • No emojis.

Adding a new distance metric

  1. Add the scalar function and the *_distance_matrix function in AMBER/distances.py.
  2. Register both in SIGNAL_DISTANCE_MATRIX and add the name to AVAILABLE_DISTANCES.
  3. Add tests in tests/test_distances.py following the existing pattern (identity, non-negativity, matrix shape, matrix-vs-scalar agreement).

Adding a new normalisation strategy

  1. Add a branch in Map.__normalize in AMBER/map.py.
  2. Add tests in tests/test_map.py under TestNormalization.

Contact

For questions, open a GitHub Discussion or e-mail alberto.nogales@uah.es.