Like all texture style nodes, this node takes a manifold that describes either a 2D or 3D domain to apply a Worley noise texture to. The default beahavior, if no mainfold is attached, is to apply over P in 3D. This node computes Worley noise, as described by Steven Worley.

Input Parameters


Controls the size of the cells. Higher frequencies make smaller cells.

RIB: float frequency
Default: 4.0

Distance Metric

The means to measure distances to neighboring cells. Manhattan distance gives more rectangular shapes and Euclidian distance gives more spherical shapes.

Value Metric C1 inverted displ C1 inverted C2 inverted
0 Euclidean: computes the euclidean distance to the nearest points. It looks a bit more pointy than Squared Euclidean distance. images/PxrWorley_distEuclidean.png images/PxrWorley_distEuclideanC.png images/PxrWorley_distEuclideanC2C.png
1 Euclidean Squared: computes the squared euclidean distance to the nearest points. It looks rounder than pure Euclidean distance. images/PxrWorley_distEuclideanSquared.png images/PxrWorley_distEuclideanSquaredC.png images/PxrWorley_distEuclideanSquaredC2C.png
2 Manhattan: inspired by the grid-like organisation of Manhattan, this is distance to the nearest points when you can only travel around the cell's boundaries. images/PxrWorley_distManhattan.png images/PxrWorley_distManhattanC.png images/PxrWorley_distManhattanC2C.png
3 Chebyshev: also known as the Chessboard Distance, it is somewhat similar to the Manhattan distance, but with 45 degrees rotation. images/PxrWorley_distChebyshev.png images/PxrWorley_distChebyshevC.png images/PxrWorley_distChebyshevC2C.png

Minkowski: it a generalisation of both euclidean and Manhattan distance. The exponent will make the pattern transition from Euclidian to Manhattan.

NOTE: This is much more expensive than the other distance metrics.

images/PxrWorley_distMinkowski4.png images/PxrWorley_distMinkowski4C.png images/PxrWorley_distMinkowski4C2C.png
RIB: int distancemetric
Default: 0


Controls the distortion of the cells.

RIB: float jitter
Default: 0.75


Multiplier for the distances to the first feature.

RIB: float c1
Default: 0.8


Multiplier for the distance to the second feature.

RIB: float c2
Default: -0.2

Minkowski Exponent

Makes the distance transition smoothly from Manhattan (1.0) to Euclidean (2.0) to weird un-explored territories.


C1 inverted


C2 inverted

RIB: float minkowskiExponent
Default: 4.0


Modifies the computed distances to create different shapes:

  • 0: Linear
  • 1: Cosine
RIB: int shape
Default: 0


Causes resulting distances to be clamped to the range 0.0 to 1.0.


c1: 1.0

c2: -0.95

distancemetric: Euclidean

RIB: int clamp
Default: 1


Inverts the final pattern.

RIB: int invert
Default: 0


The manifold over which to apply the noise. (The default is P).

RIB: struct manifold

Output Parameters

The result of Worley noise texture.