Noise Equalization

function setup() {

  createCanvas(1000, 1000);

  squareSize = 10;

  noiseSeed(6);

  noise_scale = 0.0005;

  background(100);

}

​

function draw() {

  noLoop();

  // We'll keep track of noise() values in a histogram

  hist_plot_bins = 50;

  histo_to_plot = Array(hist_plot_bins).fill(0);

​

  // Loop through each row and column of a grid

  for (let row = 0; row < height / squareSize; row++) {

    for (let col = 0; col < width / squareSize; col++) {

      // Calculate the x and y position of the square

      let x = col * squareSize;

      let y = row * squareSize;

​

      n = noise(x * noise_scale, y * noise_scale);

      fill(n * 255);

      noStroke();

​

      // Draw the square

      rect(x, y, squareSize, squareSize);

      // Fill our histogram with noise() values

      hist_plot_bin = int(n * hist_plot_bins);

      histo_to_plot[hist_plot_bin] += 1;

    }

  }

  // Draw the histogram 

  {

    sum_histo_plot_counts = histo_to_plot.reduce((a, b) => a + b, 0);

    max_histo_count = Math.max(...histo_to_plot);

    histo_w = 400;

    histo_h = 100;

    noFill();

    stroke(255);

    strokeWeight(1);

    translate(width/8, 3*height/4)

    rect(0, 0, histo_w, histo_h);

    for (x = 0; x <= hist_plot_bins; x += 1) {

      fill(255, 0, 0);

      normalized_height = map(histo_to_plot[x], 0, max_histo_count, 0, 1, true) * 100;

      rect(

        x / hist_plot_bins * histo_w,

        histo_h,

        histo_w / hist_plot_bins,

        -normalized_height

      );

    }

  }

}