Noise Functions

We can generate random values using a pseudorandom number generator:

X	1	2	3	4	...
rand(X)	28	21	96	96	...

import random

randX = [random.randint(0, 100) for x in range(0, 50)]
print(randX)

Many areas of procedural generation require random values, but the randomness needs to look more organic:

This is the job of a noise function. It produces random data, but the data has an underlying organic nature.

The above examples were in one dimension
- X is an array of numbers, for each number in X there is a corresponding value.
However it is often useful to generate noise for 2 or more dimensions:
In the above example a random value is assigned to each (x, y) coordinate pair:
- 2D noise functions are often used to generate terrains in which the height values are the result of the noise function applied to each point.
Noise functions can be extended into 3 or more dimensions:
- For example, a 3D noise function could be used for modelling gas. The random value at each 3D point could describe its density.
- 3D noise functions can also be used to animate 2D noise functions:
  - A 3D array of data is produced and then cut into a series of 2D slices.
  - You can then convert each slice into an individual frame of an animation.
  - This can then be used for when you need 2D noise that changes over time, such as when animating the formation of clouds.

Prerequisites