pyafv 0.3.2

Python implementation of the active-finite-Voronoi (AFV) model

Python code that implements the active-finite-Voronoi (AFV) model. The AFV framework was introduced and developed in, for example, Refs. [1–3].

Installation

PyAFV is now available on PyPI, so you should be able to install it through pip:

pip install pyafv

Python 3.11+ is set as the minimum requirement.

Usage

The following example demonstrates how to construct a finite-Voronoi diagram:

import numpy as np
import pyafv as afv

N = 100                                          # number of cells
pts = np.random.rand(N, 2) * 10                  # initial positions
params = afv.PhysicalParams()                    # use default parameter values
sim = afv.FiniteVoronoiSimulator(pts, params)    # initialize the simulator
sim.plot_2d(show=True)                           # visualize the Voronoi diagram

To compute the conservative forces and extract detailed geometric information (e.g., cell areas, vertices, and edges), call:

diag = sim.build()

The returned object diag is a Python dict containing these quantities.

More information

GitHub: https://github.com/wwang721/pyafv

See important issues for additional context, such as:

• QhullError when 3+ points are collinear #1 [Closed - see comments]
• Add customized plotting to examples illustrating access to vertices and edges #5 [Completed in PR #7]
• Time step dependence of intercellular adhesion in simulations #8 [Closed in PR #9]

References

[1]	J. Huang, H. Levine, and D. Bi, Bridging the gap between collective motility and epithelial-mesenchymal transitions through the active finite Voronoi model, Soft Matter 19, 9389 (2023).
[2]	E. Teomy, D. A. Kessler, and H. Levine, Confluent and nonconfluent phases in a model of cell tissue, Phys. Rev. E 98, 042418 (2018).
[3]	W. Wang (汪巍) and B. A. Camley, Divergence of detachment forces in the finite-Voronoi model, manuscript in preparation (2026).