Skip to main content
Home
Browse packagesDocsSign in
This release is 125 versions behind 0.165.7 — the latest version of @stsoftware/neat-ai. Jump to latest

@stsoftware/neat-ai@0.121.0
Built and signed on GitHub Actions

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)

New Ticket: Report package

Please provide a reason for reporting this package. We will review your report and take appropriate action.

Please review the JSR usage policy before submitting a report.

Package root>test>TraceStore.ts
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105
import { assert } from "jsr:@std/assert@^1.0.8";
import { emptyDirSync, ensureDirSync } from "jsr:@std/fs@^1.0.6";
import { Creature } from "../src/Creature.ts";
import type { CreatureInternal } from "../src/architecture/CreatureInterfaces.ts";
import type { SynapseTrace } from "../src/architecture/SynapseInterfaces.ts";
import type { NeatOptions } from "../src/config/NeatOptions.ts";

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

Deno.test("storeTrace", async () => {
  const json: CreatureInternal = {
    neurons: [
      { type: "input", index: 0 },
      { type: "input", index: 1 },
      { type: "input", index: 2 },
      {
        type: "output",
        squash: "IF",
        index: 3,
        bias: 0,
      },
    ],
    synapses: [
      { from: 0, to: 3, weight: 0.9, type: "condition" },
      { from: 1, to: 3, weight: 1.1, type: "positive" },
      { from: 2, to: 3, weight: 0.95, type: "negative" },
    ],
    input: 3,
    output: 1,
  };

  const ts = [];
  for (let i = 100; i--;) {
    for (let j = 100; j--;) {
      if (i == 50) continue;
      const condition = Math.random() * 2 - 1;
      const positive = Math.random();
      const negative = Math.random();
      const item = {
        input: [condition, positive, negative],
        output: [condition > 0 ? positive : negative],
      };

      ts.push(item);
    }
  }

  const traceDir = ".trace";
  ensureDirSync(traceDir);
  const creaturesDir = ".creatures";
  emptyDirSync(creaturesDir);

  let foundUsed = false;
  let totalCount = 0;

  for (let counter = 10; counter--;) {
    const options: NeatOptions = {
      iterations: 10,
      traceStore: traceDir,
      creatureStore: creaturesDir,
      threads: 1,
      targetError: 0,
    };
    const network = Creature.fromJSON(json);

    await network.evolveDataSet(ts, options);

    for (const dirEntry of Deno.readDirSync(traceDir)) {
      if (dirEntry.name.endsWith(".json")) {
        const json = JSON.parse(
          Deno.readTextFileSync(`${traceDir}/${dirEntry.name}`),
        );
        let usedCount = 0;
        if (json.synapses == undefined) continue;
        json.synapses.forEach((c: SynapseTrace) => {
          if (c.trace && c.trace.used) {
            usedCount++;
          }

          if (
            Number.isFinite(c.trace?.count) &&
            c.trace.count != 0
          ) {
            totalCount++;
          }
        });

        if (usedCount > 1) {
          foundUsed = true;
        }
      }
    }

    if (foundUsed) break;
  }
  assert(
    foundUsed,
    "Should have traced usage",
  );

  assert(
    totalCount > 0,
    "Should have totalCount",
  );
});