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scarlet2

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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.

Installation

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.

Metadata

Release files for scarlet2 0.5.1

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Source distribution for scarlet2 0.5.1
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scarlet2-0.5.1-py3-none-any.whl Python 3 none any Details for scarlet2-0.5.1-py3-none-any.whl

Total release size: 726.6 kB

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