Tutorial 7 — Your own rules, stages and models

The toolbox is extended through registries. Your code lives in your package (a plugin); projects and modules list the plugin, and it is imported whenever they are loaded.

A developmental rule

Rules modify the fixed growth procedure in five phases: placement, shift, target, probability, weight.

# my_project/rules.py
import numpy as np
from neurogenesis.development import register

@register("weight", "saturating_receptor")
def saturating_receptor(ctx):
    """gd["w_max"]: receptors saturate; weights above w_max are compressed."""
    if "w_max" in ctx.gd:                      # inactive unless its gene is present
        m = ctx.gd["w_max"]
        ctx.w = np.sign(ctx.w) * m * np.tanh(np.abs(ctx.w) / m)

plan = BodyPlan(..., plugins=["my_project.rules"])
plan.rules["weight"] += ("saturating_receptor",)
genome["guidance"][("a", "b")]["w_max"] = 300.0

Rules must (1) act only when their genes are present, (2) draw no random numbers, (3) be listed in the plan. The built-in rules are listed in Extending neurogenesis-sim and building module projects.

A developmental stage

# my_project/stages.py
import numpy as np
from neurogenesis.stages.base import register_stage
from neurogenesis.params import Const, resolve

@register_stage("shrink")
class Shrink:
    """Scales positions towards the origin by `factor` (1 = no change)."""

    def run(self, tissue, params, genome, fields, rng):
        f = resolve(params.get("factor", Const(1.0)), genome, fields, tissue.positions)
        tissue.positions = tissue.positions * f
        return tissue

    @staticmethod
    def cost(N, E, params):
        return 3 * 8 * N, 3 * N          # bytes, operations

A stage must: read every parameter through a Param, use only the rng it is given, be a no-op with neutral parameters, declare its cost, and come with a test on a toy tissue (see AGENTS.md).

A neuron model

Register a module with name, description, substeps, state_bytes, flops, init_state(net, seed) and tick(net, state, ext), using models.base.drivers and models.base.transmit so that drivers and delays behave as in every other model:

from neurogenesis.spiking.models import register_model
import my_project.izhikevich as izh
register_model(izh)

Details: Neuron models and their cost.

A geometry or field type

from neurogenesis.geometry import register_geometry
from neurogenesis.geometry.primitives import Geometry

@register_geometry("torus")
class Torus(Geometry):
    ...   # contains, sample, bounding_box, local_coordinates, to_dict, from_dict

PLACEHOLDER

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