// Based on https://editor.p5js.org/codingtrain/sketches/govdEW5aE

// Speed up processing thanks to Tensorflow (still really slow 🐢)

// By juancer (github/ajuancer) on 22 jun 21'

​

var grid, next, grid_buffer, next_buffer;

​

var dA = 1;

var dB = 0.5;

var feed = 0.055;

var k = 0.062;

​

var laplace_filter = tf.tensor2d(

  [0.05, 0.2, 0.05, 0.2, -1, 0.2, 0.05, 0.2, 0.05],

  [3, 3]

);

​

function setup() {

  createCanvas(200, 200);

  pixelDensity(1);

  grid = tf.stack(

    [tf.fill([width, height], 1), tf.fill([width, height], 0)],

    2

  );

  next = grid.clone();

​

  // Make b dot

  grid_buffer = tf.buffer(grid.shape, grid.dtype, grid.dataSync());

  for (var i = 100; i < 110; i++) {

    for (var j = 100; j < 110; j++) {

      grid_buffer.set(1, i, j, 1);

    }

  }

  grid = grid_buffer.toTensor();

  // console.log(`${laplace_a.get(105, 105)} ${laplace(105, 105, "a")}`);

}

​

function draw() {

  background(51);

​

  // Generate laplace matrix using tensorflow

  // https://stackoverflow.com/a/55599631/11688263

  laplace_a = tf.split(grid, 2, (axis = 2))[0];

  laplace_b = tf.split(grid, 2, (axis = 2))[1];

  laplace_a = laplace_a.squeeze();

  laplace_b = laplace_b.squeeze();

  laplace_a = laplace_a

    .reshape([1, ...laplace_a.shape, 1])

    .conv2d(laplace_filter.reshape([...laplace_filter.shape, 1, 1]), 1, "same")

    .squeeze();

  laplace_b = laplace_b

    .reshape([1, ...laplace_b.shape, 1])

    .conv2d(laplace_filter.reshape([...laplace_filter.shape, 1, 1]), 1, "same")

    .squeeze();

​

  next_buffer = tf.buffer(next.shape, next.dtype, next.dataSync());

  // Timeconsuming iteration

  for (var x = 1; x < width - 1; x++) {

    for (var y = 1; y < height - 1; y++) {

      var a = grid.get(x, y, 0);

      var b = grid.get(x, y, 1);

      temp_a = a + dA * laplace_a.get(x, y) - a * b * b + feed * (1 - a)

      temp_b = b + dB * laplace_b.get(x, y) + a * b * b - (k + feed) * b

      next_buffer.set(constrain(temp_a, 0, 1), x, y, 0);

      next_buffer.set(constrain(temp_b, 0, 1), x, y, 1);

    }

    next = next_buffer.toTensor();

  }

​

  // Timeconsuming iteration

  loadPixels();

  for (var x = 0; x < width; x++) {

    for (var y = 0; y < height; y++) {

      var pix = (x + y * width) * 4;

      var a = next.get(x, y, 0);

      var b = next.get(x, y, 1);

      var c = floor((a - b) * 255);

      c = constrain(c, 0, 255);

      pixels[pix + 0] = c;

      pixels[pix + 1] = c;

      pixels[pix + 2] = c;

      pixels[pix + 3] = 255;

    }

  }

  updatePixels();

  // No need to swap variables as next

  // will be overwritten in the loop.

  grid = next.clone();

​

}

​