This project implements calculation of frustration index, which determines the distance of a signed graph from structural/social balance, using the programming model defined in A modelling and computational study of the frustration index in signed networks, a paper by Samin Aref, Andrew J. Mason, Mark C. Wilson.
As in the paper, Gurobi is used for solving the optimization problem.
This repository contains a simple main.py using the functions defined to
solve the problem for sample graph. It is library agnostic, so any graph
library can be used.
To run/use this project you need to install the Gurobi Optimizer and its python bindings (the easiest way being python -m pip install -i https://pypi.gurobi.com gurobipy), which can also be done for conda environments (see Gurobi guide for details). You also need at least Python 3.9 to run this code.
Also numpy is needed.
To run the examples
$ python main.pyThe best way of using this code in your project is just copying social-balance.py into your folder and importing it (if you do it then please star this repository, it will help other people finding it).
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Distributed under the MIT License. See LICENSE for more information.