//--- Remember: noise Loops do not use any vector inputs ---//

let truncation_value = 0.7;

let frame_count = 24*3; // fps*seconds

let diameter = 1.0 // diameter and frame_count control how diverse the video is

let height = 1024;

let width = 1024;

let download_images = true;

let random_seed = 1

​

​

//--------- you can ignore below this line -------------//

​

let rainbow;

const a = [];

const n = [];

let angle = 0;

​

function setup() {

  randomSeed(random_seed)

  pixelDensity(1);

  createCanvas(height, width);

  for (let i = 0; i < 512; i++) {

    n[i] = new NoiseLoop(diameter, -1, 1);

  }

  generateRainbow();

​

}

​

​

function generateRainbow() {

  // httpPost(path, [datatype], [data], [callback], [errorCallback])

  const path = "http://localhost:8000/query";

  for (let i = 0; i < 512; i++) {

    a[i] = n[i].value(angle); //randomGaussian() / 50.0;

  }

  let da = TWO_PI / (frame_count);

  angle += da;

​

  const data = {

    z: a,

    truncation: truncation_value

  };

  httpPost(path, 'json', data, gotImage, gotError);

}

​

function gotError(error) {

  console.error(error);

}

​

​

function gotImage(result) {

  rainbow = createImg(result.image, imageReady);

  rainbow.hide();

}

​

let count = 0;

​

function imageReady() {

  image(rainbow, 0, 0);

  if (download_images) save(`step${nf(count, 4)}`);

  count++;

  if (angle <= TWO_PI) {

    setTimeout(generateRainbow, 100);

  }

}

​

const osn = new OpenSimplexNoise(Date.now());

​

​

class NoiseLoop {

  constructor(diameter, min, max) {

    this.diameter = diameter;

    this.min = min;

    this.max = max;

    this.cx = random(1000);

    this.cy = random(1000);

  }

​

  value(a) {

    let xoff = map(cos(a), -1, 1, this.cx, this.cx + this.diameter);

    let yoff = map(sin(a), -1, 1, this.cy, this.cy + this.diameter);

    let r = osn.noise2D(xoff, yoff);

    return map(r, -1, 1, this.min, this.max);

  }

}