Modern and modular MATISSE interferometric data-reduction pipeline interface
Project description
Modern and modular MATISSE interferometric data-reduction pipeline python interface. Developed by the MATISSE Consortium. It provides a user-friendly command-line interface (matisse) as well as backward compatibility with the original consortium scripts located in legacy/.
🚀 Installation (Users)
Recommended for end-users who only need to use the pipeline.
This project uses uv to manage environments and dependencies.
It’s fully compatible with pip but much faster and simpler to use.
1️⃣ Install uv
On Linux / macOS:
curl -LsSf https://astral.sh/uv/install.sh | sh
2️⃣ Create and activate a virtual environment
uv venv
source .venv/bin/activate
3️⃣ Install the package
uv pip install matisse
🧑💻 Developer installation
For contributors or developers working on the pipeline codebase.
1️⃣ Clone the repository
git clone https://github.com/Matisse-Consortium/matisse-pipeline.git
cd matisse-pipeline
2️⃣ Install in editable mode with dev dependencies
uv pip install -e . --group test --group typecheck
This installs:
pytest,ruff, andpre-commitfor testing and lintingmypyandtypes-termcolorfor type checking
3️⃣ Run tests
uv run pytest
4️⃣ Lint and type check
uv run ruff check src/
uv run mypy src/
🧰 Legacy Scripts Compatibility
The original MATISSE reduction tools (mat_autoPipeline.py, etc.) are preserved in the legacy/ folder for full backward compatibility.
They can be accessed by adding the legacy path to your environment:
export PATH="$PATH:$(python -c 'import matisse, pathlib; print(pathlib.Path(matisse.__file__).parent / "legacy")')"
You can add this line to your ~/.zshrc or ~/.bashrc to make it persistent.
Once exported, the commands will be available globally, e.g.:
mat_autoPipeline.py --dirCalib=.
🧩 Repository Structure
matisse-pipeline/
├── src/matisse/
│ ├── cli/ # Main CLI entry point (`matisse`)
│ ├── legacy/ # Legacy MATISSE reduction scripts
│ ├── core/ # Core pipeline modules
│ └── viewer/ # Viewer interface
├── tests/ # Unit tests
├── pyproject.toml # Project configuration
├── CHANGELOG.md # Project follow-up and versioning
└── README.md
🧑🔬 Citation / Credits
If you use this pipeline in your research, please cite the MATISSE Consortium and the corresponding instrument papers.
Maintained by the MATISSE Consortium Contributions welcome via pull requests.
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