Using the toolbox as a Python dependency

Pin a version

# pyproject.toml of your project
dependencies = ["neurogenesis-sim @ git+https://github.com/jobellet/neurogenesis-sim.git@<commit-or-tag>"]

Pin a commit or a tag: development results depend on the exact code that grew the networks.

Freeze network fingerprints

Your results come from specific networks. Freeze a fingerprint of each (plan + genome + seed → network) and test it, so that an upgrade of the toolbox that changes your networks fails your tests instead of silently changing results.

import hashlib, json

def fingerprint(net):
    d = net.to_dict()
    return hashlib.sha256(json.dumps(d, sort_keys=True).encode()).hexdigest()

# tests/test_fingerprints.py
def test_networks_unchanged():
    expected = json.load(open("tests/fixtures/network_fingerprints.json"))
    for name, (plan, genome, seed) in my_networks().items():
        assert fingerprint(grow(plan, genome, seed)) == expected[name]

Keep your project’s content out of the toolbox

Region names, stimuli, tasks and environments belong to your project. If you need a new mechanism, write it as a plugin in your package; if it is general, propose it upstream (see Contributing).

Determinism checklist

Pass explicit seeds everywhere (grow(..., seed=), simulate_counts kernel seed, evolution island).
Never use global NumPy random state in code that feeds the toolbox.
Record the toolbox commit, the JAX version and the device in your result files.