FastNoiseLite¶
Inherits: Noise < Resource < RefCounted < Object
Generates noise using the FastNoiseLite library.
Description¶
This class generates noise using the FastNoiseLite library, which is a collection of several noise algorithms including Cellular, Perlin, Value, and more.
Most generated noise values are in the range of [-1, 1]
, but not always. Some of the cellular noise algorithms return results above 1
.
Properties¶
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Enumerations¶
enum NoiseType:
NoiseType TYPE_VALUE = 5
A lattice of points are assigned random values then interpolated based on neighboring values.
NoiseType TYPE_VALUE_CUBIC = 4
Similar to Value noise, but slower. Has more variance in peaks and valleys.
Cubic noise can be used to avoid certain artifacts when using value noise to create a bumpmap. In general, you should always use this mode if the value noise is being used for a heightmap or bumpmap.
NoiseType TYPE_PERLIN = 3
A lattice of random gradients. Their dot products are interpolated to obtain values in between the lattices.
NoiseType TYPE_CELLULAR = 2
Cellular includes both Worley noise and Voronoi diagrams which creates various regions of the same value.
NoiseType TYPE_SIMPLEX = 0
As opposed to TYPE_PERLIN, gradients exist in a simplex lattice rather than a grid lattice, avoiding directional artifacts.
NoiseType TYPE_SIMPLEX_SMOOTH = 1
Modified, higher quality version of TYPE_SIMPLEX, but slower.
enum FractalType:
FractalType FRACTAL_NONE = 0
No fractal noise.
FractalType FRACTAL_FBM = 1
Method using Fractional Brownian Motion to combine octaves into a fractal.
FractalType FRACTAL_RIDGED = 2
Method of combining octaves into a fractal resulting in a "ridged" look.
FractalType FRACTAL_PING_PONG = 3
Method of combining octaves into a fractal with a ping pong effect.
enum CellularDistanceFunction:
CellularDistanceFunction DISTANCE_EUCLIDEAN = 0
Euclidean distance to the nearest point.
CellularDistanceFunction DISTANCE_EUCLIDEAN_SQUARED = 1
Squared Euclidean distance to the nearest point.
CellularDistanceFunction DISTANCE_MANHATTAN = 2
Manhattan distance (taxicab metric) to the nearest point.