https://editor.p5js.org/yl11194/sketches/8VGwUN2O5

random walk ⇒ ripple

class Walker {
  // Objects have a constructor where they are initialized.
  constructor() {
    // Objects have data.
    this.x = width / 2;
    this.y = height / 2;
  }
    // Objects have methods.
  show() {
    stroke(0);
    point(this.x, this.y);
  }

    step() {
    let r = random(1);
    //{!2} A 40% chance of moving to the right
    if (r < 0.4) {
      this.x++;
    } else if (r < 0.6) {
      this.x--;
    } else if (r < 0.8) {
      this.y++;
    } else {
      this.y--;
    }
  }
}
// A Walker object
let walker;
let walker01;

//{!1} Remember how p5.js works? setup() is executed once when the sketch starts.
function setup() {
  createCanvas(640, 240);
  // Create the walker.
  walker = new Walker();
  walker01 = new Walker();
  background(255);
}

//{!1} Then draw() loops forever and ever (until you quit).
function draw() {
  // Call functions on the walker.
  walker.step();
  walker.show();
  walker01.step();
  walker01.show();
}

• Traditional Random Walk
  • In this basic model, the walker moves one step at a time in one of four possible directions (up, down, left, right) with equal probability (typically 25% each).
  • It is a simple yet powerful model used for simulating phenomena like molecular motion or animal foraging behavior.
• Random Walk with Diagonal Moves
  • This variation allows the walker to move diagonally in addition to the four cardinal directions.
  • The walker now has eight possible movement directions, making the motion more complex and varied.
• Random Walk with Non-Uniform Probabilities
  • Here, the movement probabilities are not equal. For example, the walker might have a 40% chance of moving right and a 20% chance for each of the other directions.
  • This introduces a directional bias, allowing the walker to favor a particular path or trend.
• Random Walk with Gaussian Distribution
  • Instead of fixed step sizes, this method assigns step sizes based on a normal (Gaussian) distribution.
  • This results in most steps being small and a few being significantly larger, creating a more organic, uneven motion.
• Random Walk with Perlin Noise
  • Perlin noise is a smooth pseudo-random sequence often used in computer graphics for generating natural-looking textures and animations.
  • By applying Perlin noise to control the walker’s movement, the resulting motion is more fluid and coherent compared to purely random steps.

Class Notes