Eventgraphs
A Python library for analysing sequences of event-based data and temporal networks.
Features
- Build EventGraphs (static representation of a temporal network) using arbitrary joining rules.
- Calculate inter-event time distributions (including motif-dependent inter-event times).
- Calculate temporal motif distributions.
- Network decomposition into temporal components.
- Calculate event centralities.
- Dimension-reduction and component clustering.
- Plot network components and EventGraphs.
- IO functionality (saving as JSON).
Installation
For the latest version, installation from Github is recommended. S The PyPI package is updated periodically.
Install from Github (latest version, recommended)
pip install git+https://github.com/empiricalstateofmind/eventgraphs
Install from PyPI
pip install eventgraphs
Getting Started
The best place to get started using EventGraphs is with the tutorial here.
References
Event Graphs: Advances and Applications of Second-Order Time-Unfolded Temporal Network Models. Andrew Mellor (2018) [ArXiv]
Analysing Collective Behaviour in Temporal Networks Using Event Graphs and Temporal Motifs. Andrew Mellor (2018) [ArXiv]
The Temporal Event Graph. Andrew Mellor (2017) [Journal of Complex Networks] [ArXiv]
Please consider citing these papers if you use this code for further research.