Metadata-Version: 2.4
Name: epsf
Version: 0.1.0
Summary: Bayesian effective PSF modelling
Project-URL: Homepage, https://epsf.readthedocs.io
Project-URL: Repository, https://github.com/vandalt/epsf
Project-URL: Bug Tracker, https://github.com/vandalt/epsf/issues
Author-email: Thomas Vandal <thomas.vandal@umontreal.ca>
License-Expression: MIT
License-File: LICENSE
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.10
Requires-Dist: astropy
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: photutils
Requires-Dist: scipy
Requires-Dist: simpple
Provides-Extra: docs
Requires-Dist: astroquery; extra == 'docs'
Requires-Dist: ipywidgets; extra == 'docs'
Requires-Dist: myst-nb; extra == 'docs'
Requires-Dist: myst-parser; extra == 'docs'
Requires-Dist: sphinx; extra == 'docs'
Requires-Dist: sphinx-book-theme; extra == 'docs'
Requires-Dist: ultranest; extra == 'docs'
Provides-Extra: test
Requires-Dist: pytest; extra == 'test'
Description-Content-Type: text/markdown

# epsf: Bayesian Effective PSF Modelling

`epsf` is a framework to easily build and model effective PSFs with Python.
It uses PSF models from [`JWST1PASS`](https://www.stsci.edu/~jayander/JWST1PASS/) and the [`simpple`](https://simpple.readthedocs.io) to build PSF models for JWST observations.

Take a look at the documentation for more information: <https://epsf.readthedocs.io>
