Getting Started

Systems Requirements

In order to use the petritub toolbox, you need to install

and the following libraries

The easiest way to install the toolbox is via pip:

pip install petritub

Alternatively, you can download the latest version of the toolbox from its GitLab repository.

The toolbox is divided into three modules. For more information see Functions.

Import the desired module using from petritub.module_name import *. E.g., from petritub.untimed_pn import *

The repository is structured as follows:

petritub: contains the toolbox. Import the individual modules from petritub.module_name import * to use the toolbox.
doc: contains the Sphinx source documentation of the toolbox.
two jupyter notebook tutorials (tutorial_max_plus.ipynb and tutorial_untimed_pn.ipynb) demonstrating the usage of the toolbox are in the root folder.

In the section Functions the Python functions present in the package are described. They are divided in the following subsections:

Untimed Petri nets:
- untimed_pn toolbox (for untimed Petri nets): contains the classes and functions related to untimed Petri nets, e.g., for drawing the coverability tree, computing the state base control, and analyzing further properties of a Petri net;
Timed event graphs:
- max_plus toolbox: contains classes and functions for max-plus operations (e.g. addition, multiplication, Kleene star), the max-plus eigenvalue problem, visual representation and analysis of precedence graphs and visual representation of resource occupancy in Gantt charts.
- min_plus toolbox: analogously to the max-plus toolbox, this section contains classes and functions to handle min-plus matrices and precedence graphs.

In the section Tutorials you can see the functions of this library being used on a practical example of a manufacturing system.