Houdini 20.5 Nodes Copernicus nodes

Worley Noise 3D Copernicus node

Generates Worley noise from 3d locations.

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This operation generates a noise pattern using [Worley noise | Wp:Worley_nose]. Worley noise is useful for producing cellular patterns.

The source location is not the pixel’s image coordinates, however, but its world coordinates.

Parameters

Element Size

The size, in world coordinates, of the basic element of the noise.

Element Scale

Per-axis scaling of the element size for anistropic noise.

Jitter

Worley noise measures distance to points on a grid. This is how much to jitter those points before measuring. Values greater than 1 may produce artifacs as they will jitter past the search radius.

Jitter Scale

Per-axis scaling of the jitter.

Metric

Worley noises can define different metrics for computing the distance to a point.

Euclidean

The usual L2 distance metric. This results in circular shapes.

Manhattan

The maximum of the two axial distances, this results in diamond shapes.

Chebyshev

The sum of the two axial distances. This results in square shapes.

Offset

Offset of the noise function in image coordinates.

Inputs

size_ref

A representative layer that determines the size of the output image and controls the metadata.

pos

An RGB layer for the position of each pixel to evaluate the noise at.

Outputs

dist1

A Mono layer with distance to the nearest point.

dist2

A Mono layer with the distance to the second nearest point. Commonly dist2 - dist1 is used as a border estimate.

border

An SDF Mono layer storing the exact distance to the border between the two closest points.

Because this is a 2d slice of a 3d cell, the distance function will appear to have non-uniform sizes if the boundary plane isn’t perpendicular to the layer.

center

A RGB layer storing the image coordinates of the closest grid point.

id

An ID layer storing the hash of the closest grid point. Note this can be negative.

See also

Copernicus nodes