Metadata-Version: 2.4
Name: gemlib
Version: 0.14.0
Summary: GEMlib scientific compute library for epidemic modelling
Project-URL: homepage, https://gem-epidemics.gitlab.io/gemlib
Project-URL: documentation, https://gem-epidemics.gitlab.io/gemlib
Project-URL: repository, https://gitlab.com/gem-epidemics/gemlib
Author-email: Chris Jewell <c.jewell@lancaster.ac.uk>, Alison Hale <haleac@lancaster.ac.uk>, Jessica Bridgen <j.bridgen@lancaster.ac.uk>, Alin Morariu <a.morariu@lancaster.ac.uk>
Maintainer-email: Chris Jewell <c.jewell@lancaster.ac.uk>
License-Expression: MIT
License-File: LICENSE
Keywords: Bayesian,epidemic,infectious disease model,inference,probabilistic programming
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: <3.14.0,>=3.11.0
Requires-Dist: h5py<4.0.0,>=3.14.0
Requires-Dist: jax<0.8.0,>=0.7.0
Requires-Dist: jaxlib<0.8.0,>=0.7.0
Requires-Dist: scipy>=1.16.0
Requires-Dist: tfp-nightly==0.26.0.dev20250815
Requires-Dist: tqdm<5.0.0,>=4.67.1
Provides-Extra: gpu
Requires-Dist: jax[cuda12]<0.8.0,>=0.7.0; extra == 'gpu'
Description-Content-Type: text/markdown

`gemlib` scientific compute library
===========================================

Documentation: https://gem-epidemics.gitlab.io/gemlib

`gemlib` is a scientific compute library build for epidemic 
analysis.  It forms a component of the [GEM](http://fhm-chicas-code.lancs.ac.uk/GEM/gem)
project aimed at developing a reusable domain-specific modelling
language for epidemic inference and simulation.

`gemlib` is heavily based on [Tensorflow Probability](https://www.tensorflow.org/probability), a 
probabilistic library for the [Tensorflow](https://www.tensorflow.org)
machine learning platform.  This package provide extensions for Tensorflow
Probability related to epidemic analysis.  
