pywhy-graphs is a Python graph library that extends MixedEdgeGraph in networkx to implement a light-weight API for causal graphical structures.
Note: The API is subject to change without deprecation cycles due to the current work-in-progress MixedEdgeGraph class in networkx. For more information, follow the PR at networkx/networkx#5947
Representation of causal graphical models in Python are severely lacking.
PyWhy-Graphs implements a graphical API layer for ADMG, CPDAG and PAG. For causal DAGs, we recommend using the networkx.DiGraph class and
ensuring acylicity via networkx.is_directed_acyclic_graph function.
Existing packages that aim to represent causal graphs either break from the networkX API, or only implement a subset of the relevant causal graphs. By keeping in-line with the robust NetworkX API, we aim to ensure a consistent user experience and a gentle introduction to causal graphical models.
Moreover, sampling from causal models is non-trivial, but a requirement for benchmarking many causal algorithms in discovery, ID, estimation and more. We aim to provide simulation modules that are easily connected with causal graphs to provide a simple robust API for modeling causal graphs and then simulating data.
See the development version documentation.
Or see stable version documentation
Installation is best done via pip or conda. For developers, they can also install from source using pip. See installation page for full details.
Minimally, pywhy-graphs requires:
* Python (>=3.8)
* numpy
* scipy
* networkx
If you already have a working installation of numpy, scipy and networkx, the easiest way to install pywhy-graphs is using pip:
# doesn't work until we make an official release :p
pip install -U pywhy-graphs
To install the package from github, clone the repository and then cd into the directory. You can then use poetry to install:
poetry install
# for vizualizing graph functionality
poetry install --extras viz
# if you would like an editable install of dodiscover for dev purposes
pip install -e .
pip install https://api.github.com/repos/py-why/pywhy-graphs/zipball/main