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Contributing to Scyan

Contributions are welcome as we aim to continue improving the library. For instance, you can contribute by:

  • Reporting a bug
  • Reporting some difficulties in using the library
  • Discussing the current state of the code
  • Submitting a fix
  • Proposing new features

Opening an issue

If you have difficulty installing the library, if you discovered a bug, or need a new feature, then you can open an issue. We will try to discuss it with you and resolve your issue as soon as possible. Especially if you have any questions about the usage of the library or difficulties having satisfying results, don't hesitate to ask.

Contributing to the code

  1. Install the library in editable mode (see Getting Started). Using poetry is recommended.
  2. Create your personal branch from dev.
  3. Make sure you read the coding guidelines below.
  4. Implement your changes.
  5. Run the tests via pytest (or poetry run pytest).
  6. If needed, you can update the documentation. To do so, update the files in ./docs/ and run mkdocs serve (or poetry run mkdocs serve) to see your changes.
  7. Create a pull request with explanations about your developed features. Then, wait for discussion and validation of your pull request.

Coding guidelines

  • Use the black formatter and isort. Their usage should be automatic as they are in the pyproject.toml file. Depending on your IDE, you can choose to format your code on save.
  • Follow the PEP8 style guide. In particular, use snake_case notations (and PascalCase for classes).
  • Provide meaningful names to all your variables and functions.
  • Use relative imports to scyan.
  • Document your functions and type your function inputs/outputs.
  • Create your functions in the intended file, or create one if needed. See the project layout.
  • Try as much as possible to follow the same coding style as the rest of the library.

Project layout

This layout helps understanding the structure of the repository.

.github/      # Github CI and templates
config/       # Hydra configuration folder (optional use)
data/         # Data folder containing adata files and csv tables
docs/         # The folder used to build the documentation
scripts/      # Scripts to reproduce the results from the article
tests/        # Folder containing tests
scyan/                    # Library source code
    data/                 # Folder with data-related functions and classes
        datasets.py       # Load and save datasets
        tensors.py        # Pytorch data-related classes for training
    module/               # Folder containing neural network modules
        coupling_layer.py # Coupling layer
        distribution.py   # Prior distribution (called U in the article)
        real_nvp.py       # Normalizing Flow
        scyan_module      # Core module
    plot/                 # Plots
        ...
    tools/
        ...               # Tools (umap, subclustering, ...)
    model.py              # Scyan model class
    _io.py                # Input / output functions
    preprocess.py         # Preprocessing functions
    utils.py              # Misc functions
.gitattributes
.gitignore
CONTRIBUTING.md   # To read before contributing
LICENSE
mkdocs.yml        # The docs configuration file
poetry.lock
pyproject.toml    # Dependencies, project metadata, and more
README.md
setup.py          # Setup file, see `pyproject.toml`