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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
100%
Published
4 months ago (0.121.0)

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Package root>test>InFocus.ts
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import { assert } from "jsr:@std/assert@^1.0.8";
import { Creature } from "../src/Creature.ts";
((globalThis as unknown) as { DEBUG: boolean }).DEBUG = true;

Deno.test("hidden", () => {
  const json = JSON.parse(Deno.readTextFileSync("./test/data/inFocus.json"));
  const network = Creature.fromJSON(json);

  let positiveCount = 0;
  let negativeCount = 0;

  const startPos = network.input;
  const endPos = network.neurons.length - network.output;

  for (let pos = startPos; pos < endPos; pos++) {
    const n = network.neurons[pos];

    if (network.inFocus(n.index ? n.index : 0, [1])) {
      positiveCount++;
    } else {
      negativeCount++;
    }
  }

  assert(positiveCount > 0, "No positives");
  assert(negativeCount > 0, "No negatives");
});

Deno.test("input", () => {
  const json = JSON.parse(Deno.readTextFileSync("./test/data/inFocus.json"));
  const network = Creature.fromJSON(json);

  let positiveCount = 0;
  let negativeCount = 0;

  const startPos = 0;
  const endPos = network.input;

  for (let pos = startPos; pos < endPos; pos++) {
    const n = network.neurons[pos];

    if (network.inFocus(n.index ? n.index : 0, [1])) {
      positiveCount++;
    } else {
      negativeCount++;
    }
  }

  assert(positiveCount > 0, "No positives");
  assert(negativeCount > 0, "No negatives");
});