Introduction to pyAgrum

aGrUM

pyAgrum is a scientific C++ and Python library dedicated to Bayesian networks (BN) and other Probabilistic Graphical Models. Based on the C++ aGrUM library, it provides a high-level interface to the C++ part of aGrUM allowing to create, manage and perform efficient computations with Bayesian networks and others probabilistic graphical models : Markov random fields (MRF), influence diagrams (ID) and LIMIDs, credal networks (CN), dynamic BN (dBN), probabilistic relational models (PRM).

_images/fastModelsWithPyAgrum.png

The module is generated using the SWIG interface generator. Custom-written code was added to make the interface more user friendly.

pyAgrum aims to allow to easily use (as well as to prototype new algorithms on) Bayesian network and other graphical models.

pyAgrum contains :

Reference manual

6- Customizing pyAgrum

Indices and tables