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Returns a Voronoi Noise values of distances which are similar to Worley noise, but has additional outputs of cells positions.
The 3d position at which to sample the noise.
Randomization between cells in the noise pattern. The jitter should normally be clamped between 0 and 1.
The metric is an integer representing how the distance is measured for Worley noise
0 - Euclidean Distance
1 - Distance Squared
2 - Manhattan Distance
3 - Chebyshev Distance
The frequency of the noise. Higher values give smaller scaled details in the noise.
The offset of the input into the noise function. If you visualize the noise as a 2D graph or 3D height field, this has the effect of “panning” across the space of possible noise outputs. If you have the general noise effect you want but just want to get a different set of values for a different look, try changing the offset.
This variable is overwritten with the distances to the nearest cell points, in order of closeness. The type of output depends on signature of the node
These variables are overwritten with the cell positions, in order of closeness to the input position. The output variables return non-null values depending on signature: in case of float-signature a non-null value will be returned only by p1; in case of vector2-signature a non-null value will be returned by p1 and p2; in case of vector3-signature (default) a non-null value will be returned by all three p-variables.