SUNBIRD is a Python package that provides routines to train neural-network-based models for galaxy clustering. It also incorporates pre-trained models for different summary statistics, including:
- Galaxy two-point correlation function
- Density-split clustering statistics
- Void-galaxy cross-correlation function.
These models have been trained on mock galaxy catalogues based on the AbacusSummit simulations. The models are described in detail in Cuesta-Lazaro et al. (in preparation).
Documentation is hosted on Read the Docs, pysunbird.readthedocs.io.
Dependencies are listed in pyproject.toml, and installed automatically when installing the package.
Optional dependencies can be added for the inference routines, with the following command:
pip install sunbird[inference]To install sunbird, you can use pip:
pip install sunbird @ git+https://github.com/florpi/sunbird.gitIf you want to install the package from source, you can clone the repository and install it with:
git clone https://github.com/florpi/sunbird.git
cd sunbird
pip install .[inference]