pyLEAFS is a Python port of LEAFS (Layered Environment with Agents Foraging Simulator), an agent-based model for studying how energy harvesting drives the development of sensors and information-processing behavior. The core is dimension-agnostic (2d or 3d) and built on a struct-of-arrays NumPy layout.
This first version is a single-species greedy forager on a replenishing Poisson resource field. Pheromone fields, predators, heterogeneous environments, and neuroevolution are later layers that attach to that core. This repository holds the Python port only; the original MATLAB classes are not included.
git clone https://github.com/EternalTime/LEAFS.git
cd LEAFS
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -e .Requires Python 3.8+ (tested on 3.8 through 3.14); numpy and matplotlib are
installed automatically. The virtual environment is what makes pip available
and keeps the install out of a system Python that may refuse it, so activate it
in every new terminal. The Getting Started
guide is the authority
on installation and carries the same steps.
from pyLEAFS import Simulation
# greedy forager world matching the LEAFS applet parameters
sim = Simulation.forager(seed=0)
sim.run(1000)
print(sim.populations[0].count, "agents alive")Watch it live (spacebar pauses; click empty space to add an agent; click an agent to inspect it):
from pyLEAFS import Viewer
sim = Simulation.forager(seed=0)
Viewer(sim).play()The viewer follows the world it is given, so a 3d simulation opens in a rotatable box with the same controls:
Viewer(Simulation.forager(seed=0, shape=(10, 10, 10))).play()In 3d, left-drag rotates the view and a click that does not move it picks: it selects the agent nearest the line of sight, or, if none is close enough, adds one on that line at the depth of the centre of the box.
The docs live at damiansowinski.com/LEAFS,
or run import pyLEAFS; pyLEAFS.docs() to open them.
source .venv/bin/activate
pip install -e '.[test]'
pytestMIT