Wellcome to ✨SirModelShowCase✨. This repository was created for purpose of presentation "spreading in network" to the high school students. Example contains simple Python code that loads network, runs SIR model in multiple iterations and outputs of this iterations exports to images.
The SIR model was introduced in 1927 by Kermack [1].
In this model, during the course of an epidemics, a node is allowed to change its status from Susceptible (S) to Infected (I), then to Removed (R).
The model is instantiated on a graph having a non-empty set of infected nodes.
SIR assumes that if, during a generic iteration, a susceptible node comes into contact with an infected one, it becomes infected with probability beta, than it can be switch to removed with probability gamma (the only transition allowed are S→I→R).
We used ndlib implementation of SIR model. For more information follow doccumentation.
Requirements for running script localy
- Python 3.8 🐍
- Visual Studio Code (Highly recomended)
- Visit Jupyter website
- Open Try clasic notebook
- In top menu choose File -> Create new notebook -> Python3
- Install all required dependencies
pip install networkx matplotlib fa2l ndlib tqdm- Copy script from main.py file and run it
With VS Code you can open jupyter.ipnb whitch opens jupyter dashboard. In thin dashboard you can directly see output of plots. Jupyter provides much more then just terminal. For more informations check https://jupyter.org/
[1] Kermack and A. McKendrick, “A Contribution to the Mathematical Theory of Epidemics,” Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, vol. 115, no. 772, pp. 700–721, Aug. 1927