Spreading Processes on Networks (SPoNet)

This package provides an efficient implementation of popular discrete-state spreading processes on networks of interacting agents. They can be used to simulate how opinions about certain issues develop over time within a population, or how an infectious disease spreads. The simulation loop is just-in-time compiled using numba, which makes performance comparable with compiled languages like C++.

Installation

The package requires a Python version between 3.10 and 3.14. Install from the PyPI repository:

pip install sponet

or get the latest version directly from GitHub:

pip install git+https://github.com/lueckem/SPoNet

Available models

• Continuous-time noisy voter model (CNVM)
• Continuous-time noisy threshold model (CNTM)

Examples

Check out the examples in the repository. They are marimo notebooks. You can install marimo on your machine (pip install marimo), clone the repository, and launch via marimo edit. Alternatively, you can also view the notebooks in your browser using the molab web interface by following these links:

• Notebook CNVM tutorial
• Notebook SIS model

Reference

• CNVM
• CNTM
• Network generators: generate (random) networks
• Collective variables: aggregate state information
• Sampling states: sample system states (e.g., as initial states for simulations)
• Multiprocessing: run many simulations in parallel