Welcome to the biolgca Documentation!¶

biolgca is a Python package for simulating lattice-gas cellular automata (LGCA) in biological contexts.

LGCA¶

LGCA are cellular automata with an extended channel state space. Particles or cells occupy velocity channels, so the lattice state records both the number of cells at each node and their movement directions. The package supports classical, identity-based, volume-exclusion-free and multi-species LGCA models.

For a broader modelling introduction, see the BIO-LGCA Wikipedia article and the BIO-LGCA method paper: Deutsch et al. 2021.

Supported models¶

The lgca.get_lgca() factory selects a simulator class from these axes:

classical LGCA with volume exclusion
identity-based LGCA with volume exclusion
classical LGCA without volume exclusion
identity-based LGCA without volume exclusion
classical multi-species LGCA with or without volume exclusion

Supported geometries are 1D linear, 2D square, 2D hexagonal, 3D cubic and 3D Moore lattices. Multi-species identity-based LGCA are not implemented yet.

Current analysis helpers include density, flux, flow, state-space, scalar-field, vector-field, property and family-population plots. Plotting features require the optional plotting dependencies.

Quick example¶

from lgca import get_lgca

lgca = get_lgca(geometry="hex", interaction="alignment", bc="refl", seed=1)
lgca.timeevo(timesteps=132, record=True)
lgca.plot_flux()