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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>Elitism.ts
import { assert, assertAlmostEquals } from "jsr:@std/assert@^1.0.8"; import { Creature } from "../src/Creature.ts"; import type { CreatureInternal } from "../src/architecture/CreatureInterfaces.ts"; import { logVerbose, makeElitists, sortCreaturesByScore, } from "../src/architecture/ElitismUtils.ts"; import { addTag } from "jsr:@stsoftware/tags@^1.0.5"; import type { Approach } from "../src/NEAT/LogApproach.ts"; import { CreatureUtil } from "../mod.ts"; ((globalThis as unknown) as { DEBUG: boolean }).DEBUG = true; function make(population: CreatureInternal[]) { const networks: Creature[] = []; population.forEach((ni) => { if (ni.neurons.length == 0) { ni.neurons.push({ index: 1, type: "output", squash: "IDENTITY", }); ni.synapses.push({ from: 0, to: 1, weight: 1, }); } const network = Creature.fromJSON(ni); network.score = ni.score; addTag(network, "error", Math.abs(ni.score ?? 1).toString()); networks.push(network); }); return networks; } Deno.test("1make", () => { const population: CreatureInternal[] = [ { input: 1, output: 1, score: 1, neurons: [], synapses: [] }, { input: 1, output: 1, score: -1, neurons: [], synapses: [] }, { input: 1, output: 1, score: 3, neurons: [], synapses: [] }, { input: 1, output: 1, score: 1, neurons: [], synapses: [] }, { input: 1, output: 1, score: 2, neurons: [], synapses: [] }, ]; const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, "Undefined " + e); } assert( elitists.length == 1, "Should always find one " + JSON.stringify(elitists[0]?.exportJSON()), ); assert(elitists[0].score == 3, `Wrong elitism score ${elitists[0].score}`); }); Deno.test("3make", () => { const population: CreatureInternal[] = [ { input: 1, output: 1, score: 1, neurons: [], synapses: [] }, { input: 1, output: 1, score: -1, neurons: [], synapses: [] }, { input: 1, output: 1, score: 3, neurons: [], synapses: [] }, { input: 1, output: 1, score: 1, neurons: [], synapses: [] }, { input: 1, output: 1, score: 2, neurons: [], synapses: [] }, ]; const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation, 3).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, i + ") " + e); } assert(elitists.length == 3, `Wrong number ${elitists.length}`); assert(elitists[0].score == 3, `Wrong score ${elitists[0].score}`); assert(elitists[1].score == 2, `Wrong score ${elitists[1].score}`); assert(elitists[2].score == 1, `Wrong score ${elitists[2].score}`); }); Deno.test("3make2", () => { const population: CreatureInternal[] = [ { input: 1, output: 1, score: -3, neurons: [], synapses: [] }, { input: 1, output: 1, score: -2, neurons: [], synapses: [] }, { input: 1, output: 1, score: -1, neurons: [], synapses: [] }, ]; const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation, 3).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, "Undefined " + e); } assert(elitists.length == 3, `Wrong number ${elitists.length}`); assert(elitists[0].score == -1, `Wrong score ${elitists[0].score}`); assert(elitists[1].score == -2, `Wrong score ${elitists[1].score}`); assert(elitists[2].score == -3, `Wrong score ${elitists[2].score}`); }); Deno.test("short", () => { const population: CreatureInternal[] = [ { input: 1, output: 1, score: -2, neurons: [], synapses: [] }, { input: 1, output: 1, score: -1, neurons: [], synapses: [] }, ]; population.forEach((c, i) => { addTag(c, "trainID", "ID" + i); addTag(c, "approach", "fine" as Approach); }); const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation, 3, true).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, i + ") " + e); } assert(elitists.length == 2, `Wrong count ${elitists.length}`); assert(elitists[0].score == -1, `Wrong score ${elitists[0].score}`); assert(elitists[1].score == -2, `Wrong score ${elitists[1].score}`); }); Deno.test("backwards", () => { const population: CreatureInternal[] = []; for (let i = 0; i < 1000; i++) { population.push({ input: 1, output: 1, score: i, neurons: [], synapses: [], }); } const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation, 3).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, i + ") " + e); } assert(elitists.length == 3, `Wrong count ${elitists.length}`); assert(elitists[0].score == 999, `Wrong score ${elitists[0].score}`); assert(elitists[1].score == 998, `Wrong score ${elitists[1].score}`); assert(elitists[2].score == 997, `Wrong score ${elitists[2].score}`); }); Deno.test("forward", () => { const population: CreatureInternal[] = []; for (let i = 0; i < 1000; i++) { population.push({ input: 1, output: 1, score: 1000 - i, neurons: [], synapses: [], }); } const elitists = makeElitists(make(population), 3).elitists; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, 1 + ") " + e); } assert(elitists.length == 3, `Wrong count ${elitists.length}`); assert( elitists[0].score == 1000, `Wrong score ${elitists[0].score}`, ); assert(elitists[1].score == 999, `Wrong score ${elitists[1].score}`); assert(elitists[2].score == 998, `Wrong score ${elitists[2].score}`); }); Deno.test("performance", () => { const population: CreatureInternal[] = []; for (let i = 0; i < 100000; i++) { population.push({ input: 1, output: 1, score: Math.random(), neurons: [], synapses: [], }); } let totalMS = 0; let minMS = Infinity; for (let j = 10; j--;) { performance.mark("start"); const elitists = makeElitists(make(population), 3).elitists; performance.mark("end"); const ms = performance.measure("start", "end").duration; console.log("Duration: " + ms); totalMS += ms; if (ms < minMS) minMS = ms; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, i + ") " + e); } assert( elitists.length == 3, `Wrong count ${elitists.length}`, ); } console.log("Average", totalMS / 10, " Minimum", minMS); }); Deno.test("order", () => { const population: CreatureInternal[] = []; for (let i = 0; i < 1000; i++) { const v = Math.random(); if (i % 11 == 0) { population.push({ input: 1, output: 1, score: v, neurons: [], synapses: [], }); } const c: CreatureInternal = { input: 1, output: 1, score: v, neurons: [], synapses: [], }; population.push(c); } const sortedPopulationStart = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulationStart, 100).elitists; const sortedPopulation = population.slice().sort(function (a, b) { if (b.score == a.score) return 0; if (b.score == undefined) return 1; if (a.score == undefined) return -1; return b.score - a.score; }); let last = 1; for (let i = 0; i < elitists.length; i++) { const e = elitists[i]; assert(e, i + ") " + e); assert(e.score ? e.score : 1 <= last, i + ") " + e.score + " > " + last); last = e.score ? e.score : 0; assert(e.score == sortedPopulation[i].score, "not sorted"); } assert( elitists.length == 100, `Wrong count ${elitists.length}`, ); }); Deno.test("NaN", () => { const population: CreatureInternal[] = []; population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: undefined, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: -1, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: -Infinity, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: Infinity, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: 0, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: 1, neurons: [], synapses: [], }); population.push({ input: 1, output: 1, score: NaN, neurons: [], synapses: [], }); const sortedPopulation = sortCreaturesByScore(make(population)); const elitists = makeElitists(sortedPopulation, 3).elitists; assert( elitists.length == 3, `Wrong count ${elitists.length}`, ); assert( elitists[0].score == 1, "Highest score first " + elitists[0].score, ); assert( elitists[1].score == 0, "Zero next " + elitists[1].score, ); assert( elitists[2].score == -1, "Then negative 1 " + elitists[2].score, ); }); Deno.test("logVerbose", () => { const population: CreatureInternal[] = [ { input: 1, output: 1, score: -2, neurons: [], synapses: [] }, { input: 1, output: 1, score: -1, neurons: [], synapses: [] }, ]; population.forEach((c, i) => { addTag(c, "trainID", "ID" + i); addTag(c, "approach", "fine" as Approach); }); const creatures = make(population); const uuid = CreatureUtil.makeUUID(creatures[0]); addTag(creatures[1], "CRISPR-SOURCE", uuid); const average = logVerbose(creatures); assertAlmostEquals(average, -1.5, 0.1, `Wrong average ${average}`); const average2 = logVerbose(creatures); assertAlmostEquals(average2, -1.5, 0.1, `Wrong average ${average}`); });