Metadata-Version: 2.1
Name: BayNet
Version: 0.1.2
Summary: (another) Python Bayesian Network library
Home-page: https://github.com/Stoffle/BayNet
Author: Chris Robinson
Author-email: c.f.robinson@sussex.ac.uk
License: UNKNOWN
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: python-igraph (<0.8.0)
Requires-Dist: numpy (>=1.17.2)
Requires-Dist: pandas (>=0.25)
Requires-Dist: pyyaml
Provides-Extra: ci
Requires-Dist: pytest (>=3.3.2) ; extra == 'ci'
Requires-Dist: pytest-cov (>=2.6.0) ; extra == 'ci'
Requires-Dist: networkx ; extra == 'ci'
Provides-Extra: dev
Requires-Dist: black ; extra == 'dev'
Requires-Dist: mypy (>=0.720) ; extra == 'dev'
Requires-Dist: pylint (>=2.0) ; extra == 'dev'
Requires-Dist: pytest (>=3.3.2) ; extra == 'dev'
Requires-Dist: pytest-cov (>=2.6.0) ; extra == 'dev'
Requires-Dist: pre-commit ; extra == 'dev'
Requires-Dist: pydocstyle ; extra == 'dev'
Requires-Dist: networkx ; extra == 'dev'

# BayNet

Wrapper around python-igraph's `Graph` class specifically for Bayesian Networks.

Current features:
- Conditional probability tables (parameters for discrete variable networks)
- Discrete network sampling

Future features:
- CPT learning (maximum likelihood)
- Dag <-> CPDAG methods


