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.
The following packages are required to run the code:
- black
- pytorch
- pandas
- numpy
- matplotlib
- xarray
- pytorch-lightning
- optuna
- joblib
First
git clone https://github.com/florpi/sunbird.git
To install the code
python setup.py install --user
Or in development mode (any change to Python code will take place immediately)
python setup.py develop --user
