scarlet2 is an open-source python library for modeling astronomical sources from multi-band, multi-epoch, and multi-instrument data. It provides non-parametric and parametric models, can handle source overlap (aka blending), and can integrate neural network priors. It's designed to be modular, flexible, and powerful.
scarlet2 is implemented in jax, layered on top of the equinox library. It can be deployed to GPUs and TPUs and supports optimization and sampling approaches.
For performance reasons, you should first install jax with the suitable jaxlib for your platform. After that
pip install scarlet2
should do. If you want the latest development version, use
pip install git+https://github.com/pmelchior/scarlet2.git
This will allow you to evaluate source models and compute likelihoods of observed data, so you can run your own
optimizer/sampler. If you want a fully fledged library out of the box, you need to install optax, numpyro, and
h5py as well.