# Random noise

I started to undestand what Generative Art is all about: generating randomness and moving it around, containing it, bending it to your will. You need to be a randomness hacker. A noise whisperer.

There are many ways you can use to vizualize noise: dots, lines, bars and wavy lines with stacked randomness.

**Hint**: The examples below are written in Javascript. Refresh the page multiple times to see different random results.

This is how pure random 2D noise looks like:

It’s pretty boring.

And the same pure randomness in the form of vertical lines:

It becomes a little more interesting when you stack multiple levels of randomness:

To control the positioning, you can use probability distribution functions that are more likely to generate numbers in a specific range, rather than uniformly distributed numbers.

The easiest way is to use power functions, either with exponent larger than 1, or smaller.

Smaller than 1 exponents generate smooth distributions because `Math.random()`

generates numbers in the range 0…1.

In these two examples below, I’m aligning the noise to left or right by using `Math.pow(Math.random(), 0.1)`

for the X axis:

And the same distribution, represented as lines:

A more popular way to distribute randomness is the Normal distribution, also called Gaussian or Laplace–Gauss) distribution. You can check different implementations at RosettaCode.org - Normal distribution. It concentrates the noise to make a soft 🔔"Bell curve" like this:

And the lines:

I wrote this post because a few months ago, *I had no idea that these functions exist*, let alone why they would be useful.

If you found this interesting, you can also check this similar article by Tyler Hobbs: Probability distributions for algorithmic artists.