Metadata-Version: 2.4
Name: iwpc
Version: 0.11.0
Summary: A framework for divergence based inference and detector response modelling for experimental physics
Author-email: "Jeremy J. H. Wilkinson" <jero.wilkinson@gmail.com>
Project-URL: Homepage, https://github.com/jjhwilkinson/iwpc
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: torch
Requires-Dist: lightning
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: tensorboard
Requires-Dist: seaborn
Requires-Dist: bokeh
Dynamic: license-file

# IWPC #

A framework for divergence based inference and detector response modelling
for experimental physics. Implements the methods in [arXiv:2405.06397](https://arxiv.org/abs/2405.06397)
and frameworks for detector response modeling

Install using `pip install iwpc`

Please see the package [README](https://github.com/jjhwilkinson/iwpc) on
GitHub for more information and some examples.
