Daft is a Python package that uses matplotlib to render pixel-perfect probabilistic graphical models for publication in a journal or on the internet. With a short Python script and an intuitive model-building syntax you can design directed (Bayesian Networks, directed acyclic graphs) and undirected (Markov random fields) models and save them in any formats that matplotlib supports (including PDF, PNG, EPS and SVG).
👉 Check out the Examples to get started.
Installing the most recent stable version of Daft should be pretty easy if you use pip:
python -m pip install daft
Otherwise, you can download the source and run:
python -m pip install -e .
in the root directory.
Daft only depends on matplotlib and
numpy. These are standard components of the
scientific Python stack but if you don’t already have them installed
will try to install them for you.
If you have any problems or questions, open an “issue” on Github.
Copyright 2012-2021 Daft Developers.
Daft is free software made available under the MIT License. For details see the LICENSE file.
If you use Daft in academic projects, acknowledgements are greatly appreciated.