Overview
DyNSimF
is a Python package that serves as a framework to simulate dynamic networks.
Any network that has nodes with states that are updated, can be simulated using this framework. Furthermore, interactions between nodes, e.g: removal and addition of edges, can be specified.
Why would you use DyNSimF?
DyNSimF allows users to easily implement custom static or dynamic network models, without having to write enormous amounts of boilerplate code just to get simulation or visualization logic working. This means that more time can be spent on modeling and analysing results. Furthermore, by having clear structure in how models are created, it becomes easier to share models with others, as everyone is using the same framework.
Who is DyNSimF intended for?
This framework can be used by people of all branches who have minor python programming skills and are interested in simulating networks. This means that mathematicians, physicists, biologists, chemists, computer scientists, and social scientists are all able to create their models using DyNSimF.
Aim
Maintainability: One single framework to create and analyse any dynamic network model
Focus: Spending less time on boilerplate code and more on modeling
Readability: Transparent interfaces to share models with others without unnecessary complexity
Framework functionalities/options
Network node state initialization
Node state calculations
Utility/cost optimization per node
Sensitivity analysis
Dynamic network visualization
State saving and importing
Free software
DyNSimF
is free software; you can redistribute it and/or modify it under the terms of the BSD-2 License.