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Tom Hohler committed Apr 27, 2018
1 parent 8a17699 commit fcbc106
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5 changes: 0 additions & 5 deletions src/demos/genetic/salesman.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -102,11 +102,6 @@ function drawSolution(towns: Position[], genes: number[], color?: string) {
ctx.arc(c.width / 11 * town.x, c.height - (c.height / 11 * town.y), 5, 0, 2 * Math.PI);
ctx.fill();
}
// ctx.strokeStyle = `rgb(
// ${Math.floor(Math.random() * 255)},
// ${Math.floor(Math.random() * 255)},
// ${Math.floor(Math.random() * 255)}
// )`;
ctx.moveTo(towns[genesCopy[0]].x, towns[genesCopy[0]].y);
ctx.beginPath();
if (color) {
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154 changes: 0 additions & 154 deletions src/demos/neat/racing/race.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -4,157 +4,3 @@ export async function race() {
await gameService.init();
gameService.start();
}

// import { Selection } from "../../../genetic/methods";
// import { Population } from "../../../genetic/model";
// import { Activation } from "../../../neural-network/methods";
// import { Network } from "../../../neural-network/model/network";
// import { Car } from "./car";
// import { CheckPoint } from "./checkPoint";
// import * as checkPoints from "./checkPoints.json";
// import { Map } from "./map";
// import { Position } from "./position";
// import { Vector2 } from "./vector2";

// const dt = 1000 / 60;

// export function race() {
// const c = document.getElementById("canvas") as HTMLCanvasElement;
// const ctx = c.getContext("2d")!;

// const carImage = new Image();
// carImage.src = "/assets/car.png";
// const mapImage = new Image();
// mapImage.src = "/assets/raceMap.png";

// const loadImage = (image: HTMLImageElement) => new Promise<HTMLImageElement>((resolve, reject) => {
// image.onload = () => {
// console.log("resolved", image.src);
// resolve(image);
// };
// if (image.complete) {
// resolve(image);
// }
// });

// const mutate = (genes: number[]) => {
// const genesCopy = genes.slice(0);
// const randomIndex = Math.floor(Math.random() * genes.length);
// genesCopy[randomIndex] = Math.random() * 2 - 1;
// return genesCopy;
// };

// run();

// async function run() {
// try {
// await loadImage(carImage);
// await loadImage(mapImage);
// } catch {
// console.log("oups");
// throw Error("failed to load images");
// }
// let carsPop = createPopulation();
// let cars = carsPop.candidates.map(it => new Car(new Position(200, 50), Network.fromWeights(it.genes, [3, 4, 4, 2])));
// for (let i = 0; i < cars.length; i++) {
// carsPop.candidates[i].fitness = () => {
// return cars[i].checkPoints * 1000;
// // return cars[i].pos.distanceTo(new Position(200, 50));
// // return 1 - (cars[i].pos.x + cars[i].pos.y);
// };
// }
// let raceTime = 0;
// ctx.drawImage(mapImage, 0, 0);
// const map = loadMap(mapImage, checkPoints);
// let generation = 0;

// while (generation < 30) {
// if (raceTime > 10000 ) {
// console.log(generation);
// generation++;
// raceTime = 0;
// carsPop = carsPop.createNextGeneration();
// cars = carsPop.candidates.map(
// it => new Car(new Position(200, 50), Network.fromWeights(it.genes, [3, 4, 4, 2]))
// );
// for (let i = 0; i < cars.length; i++) {
// carsPop.candidates[i].fitness = () => {
// return cars[i].checkPoints * 1000;
// };
// }
// }
// cars.map(it => {
// it.update(map, dt / 1000);
// });
// // cars[0].draw(ctx, carImage);
// raceTime = raceTime + dt;
// }
// requestAnimationFrame(loop);

// let t0 = Date.now();
// function loop() {
// if (raceTime > 60000) {
// generation++;
// console.log("generation", generation, Date.now() - t0, raceTime);
// t0 = Date.now();
// raceTime = 0;
// console.table(carsPop.candidates.sort((a, b) => b.fitness([]) - a.fitness([])).slice(0, 10).map(it => it.fitness([])));
// carsPop = carsPop.createNextGeneration();
// cars = carsPop.candidates.map(
// it => new Car(new Position(200, 50), Network.fromWeights(it.genes, [3, 4, 4, 2]))
// );
// for (let i = 0; i < cars.length; i++) {
// carsPop.candidates[i].fitness = () => {
// return cars[i].checkPoints * 1000;
// };
// }
// }
// ctx.clearRect(0, 0, c.width, c.height);
// drawCheckPoints(map.checkPoints);
// ctx.drawImage(mapImage, 0, 0);
// cars.map(it => {
// it.update(map, dt / 1000);
// it.draw(ctx, carImage);
// });
// // cars[0].draw(ctx, carImage);
// raceTime = raceTime + dt;
// // const waitTime = Math.max(0, (1000 / 60) - dt);
// // const waitTime = dt;
// requestAnimationFrame(loop);
// }
// }

// function createPopulation() {
// return Population.generatePopulation(
// 100,
// () => Network.perceptron([3, 4, 4, 2]).weights,
// {
// mutate,
// mutationProbability: 0.4
// }
// );
// }

// function loadMap(image: HTMLImageElement, checkPointsJson: any) {
// const collisionMap: number[][] = [];
// for (let x = 0; x < image.width; x ++) {
// const row = [];
// for (let y = 0; y < image.height; y ++) {
// row.push(ctx.getImageData(x, y, 1, 1).data[3] === 0 ? 1 : 0);
// }
// collisionMap.push(row);
// }
// const checkPointArray: CheckPoint[] = checkPointsJson.map((it: any) => CheckPoint.fromJson(it));
// return new Map(collisionMap, checkPointArray);
// }

// function drawCheckPoints(checkPointArray: CheckPoint[]) {
// checkPointArray.map(it => {
// ctx.beginPath();
// ctx.strokeStyle = "green";
// ctx.moveTo(it.pos1.x, it.pos1.y);
// ctx.lineTo(it.pos2.x, it.pos2.y);
// ctx.stroke();
// });
// }
// }
1 change: 0 additions & 1 deletion src/genetic/model/population.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,6 @@ export class Population<T> {
/**
* Add the children to the population
*/
// const newGeneration = this.candidates.concat(newCandidates);

/**
* Keep the stronger candidates
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