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@stsoftware/neat-ai@0.121.0
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stSoftwareAU/NEAT-AI

NEAT Neural Network. This project is a unique implementation of a neural network based on the NEAT (NeuroEvolution of Augmenting Topologies) algorithm, written in DenoJS using TypeScript.

This package works with Deno
This package works with Deno
JSR Score
94%
Published
5 months ago (0.121.0)
Package root>test>makeActivation.ts
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import { assertAlmostEquals } from "jsr:@std/assert@^1.0.8";
import { Creature } from "../src/Creature.ts";
import { CreatureState } from "../src/architecture/CreatureState.ts";

((globalThis as unknown) as { DEBUG: boolean }).DEBUG = true;

Deno.test("makeActivation", () => {
  const creature = Creature.fromJSON({
    "neurons": [{
      "bias": 0,
      "type": "hidden",
      "squash": "LOGISTIC",
      "index": 2,
    }, {
      "bias": 0,
      "type": "hidden",
      "squash": "LOGISTIC",
      "index": 3,
    }, {
      "bias": -0.49135010426905,
      "type": "output",
      "squash": "BIPOLAR_SIGMOID",
      "index": 4,
    }],
    "synapses": [{
      "weight": 0.9967556172986067,
      "from": 1,
      "to": 2,
    }, {
      "weight": -0.067,
      "from": 2,
      "to": 3,
    }, { "weight": 0.96864643541, "from": 3, "to": 4 }],
    "input": 2,
    "output": 1,
    tags: [
      { name: "error", value: "0.5" },
    ],
  });

  creature.validate();
  const ns = new CreatureState(creature);

  ns.makeActivation(new Float32Array([-0.1, -0.2]), false);

  assertAlmostEquals(ns.activations[0], -0.1, 0.0000001);
  assertAlmostEquals(ns.activations[1], -0.2, 0.0000001);
  assertAlmostEquals(ns.activations[2], 0, 0.0000001);
  assertAlmostEquals(ns.activations[3], 0, 0.0000001);
  assertAlmostEquals(ns.activations[4], 0, 0.0000001);

  ns.activations[2] = 0.1;
  ns.activations[3] = 0.2;
  ns.activations[4] = 0.3;
  ns.makeActivation(new Float32Array([-0.3, -0.4]), true);

  assertAlmostEquals(ns.activations[0], -0.3, 0.0000001);
  assertAlmostEquals(ns.activations[1], -0.4, 0.0000001);
  assertAlmostEquals(ns.activations[2], 0.1, 0.0000001);
  assertAlmostEquals(ns.activations[3], 0.2, 0.0000001);
  assertAlmostEquals(ns.activations[4], 0.3, 0.0000001);

  ns.makeActivation(new Float32Array([-0.5, -0.6]), false);

  assertAlmostEquals(ns.activations[0], -0.5, 0.0000001);
  assertAlmostEquals(ns.activations[1], -0.6, 0.0000001);
  assertAlmostEquals(ns.activations[2], 0, 0.0000001);
  assertAlmostEquals(ns.activations[3], 0, 0.0000001);
  assertAlmostEquals(ns.activations[4], 0, 0.0000001);
});