The abstract superclass for procedural noise generators that create coherent noise.
- iOS 10.0+
- macOS 10.12+
- Mac Catalyst 13.0+
- tvOS 10.0+
In general, noise is randomness across a (one-, two-, three-, or many-dimensional) domain—for example, you can create noise by filling an image with values from a random number generator. Unlike such truly random noise, coherent noise is consistent and smooth: you can always generate the same output from a specific seed value, and small variations across the domain create only small variations in noise values.
You don’t instantiate or work directly with this class. Instead, the concrete subclasses of
GKCoherentNoiseSource each provide a different style of coherent noise.
Managing Noise Generation Parameters
var octaveCount: Int
The number of octaves of the underlying noise function to use for generating noise.
var seed: Int32
The value that determines the specific configuration of noise produced by the noise source.
A representation of procedural noise, generated by a noise source, that you can use to process, transform, or combine noise.
A sample of procedural noise data from which you can read noise values directly or create noise textures.
A procedural noise generator whose output is a type of fractal coherent noise resembling natural phenomena such as clouds and terrain.
A procedural noise generator whose output is a type of multifractal coherent noise with sharply defined features.
A procedural noise generator whose output (also called Worley noise or cellular noise) divides space into discrete cells surrounding random seed points.