jajapy 0.9

Baum-Welch for all kind of Markov model

Introduction

jajapy is a python library implementing the Baum-Welch algorithm on various kinds of Markov models. jajapy generates models which are compatible with the Stormpy model checker. Thus, jajapycan be use as a learning extension to the Storm model checker.

Main features

jajapy provides:

Markov Model	Learning Algorithm(s)
HMM	Baum-Welch for HMMs (ref)
MC	Baum-Welch for MCs Alergia (ref)
MDP	Baum-Welch for MDPs (ref) Active Baum-Welch (ref) IOAlergia (ref)
CTMC	Baum-Welch for CTMCs
GoHMM	Baum-Welch for GoHMMs (ref)
MGoHMM	Baum-Welch for MGoHMMs

jajapy generates by default Stormpy models (except for GoHMM and MGoHMM).

Installation

pip install jajapy

Requirements

• numpy
• scipy
• alive-progress
• stormpy (recommended: if stormpy is not installed, jajapy will generate models in jajapy format).

Documentation

Available on readthedoc