causal-networkx#
Causal-Networkx is a Python package for representing causal graphs, such as Acyclic
Directed Mixed Graphs (ADMG), also known as causal DAGs and Partial Ancestral Graphs (PAGs).
We loosely build on top of networkx such that we maintain all the well-tested and efficient
algorithms and data structures of networkx, and implement causal-specific graph algorithms.
We implement basic causal discovery algorithms, causal ID algorithms (coming soon) and causal
estimation algorithms (coming soon). It comes with causal graph traversal algorithms,
such as m-separation.
We encourage you to use the package for your causal inference research and also build on top with relevant Pull Requests.
See our examples for walk-throughs of how to use the package.
Contents#
Getting started:
Team#
causal-networkx is developed and maintained by adam2392. To learn more about who specifically contributed to this codebase, see our contributors page.
License#
causal-networkx is licensed under BSD 3.0. A full copy of the license can be found on GitHub.