It's an implementation of Worley noise. The feature points can be customized. The function returns `[cell_x, cell_y(, cell_z), noise]`

value at the (x, y(,z)) coordinate.

**Since:** 2.3

## Parameters

points, p, dist

`points`

: The feature points, can be 2D or 3D.`p`

: The pixel or voxel coordinate.`dist`

: The noise value of each point is based on its distance to other cells. Different distance strategies make different noises. The`dist`

parameter accepts`"euclidean"`

,`"manhattan"`

,`"chebyshev"`

or`"border"`

.

## Examples

```
use <noise/nz_cell.scad>;
use <golden_spiral.scad>;
size = [100, 50];
half_size = size / 2;
pts_angles = golden_spiral(
from = 3,
to = 10,
point_distance = 3
);
feature_points = [for(pt_angle = pts_angles) pt_angle[0] + half_size];
noised = [
for(y = [0:size[1] - 1])
for(x = [0:size[0] - 1])
[x, y, nz_cell(feature_points, [x, y])]
];
max_dist = max([for(n = noised) n[2]]);
for(n = noised) {
c = abs(n[2] / max_dist);
color([c, c, c])
linear_extrude(n[2] + 0.1)
translate([n[0], n[1]])
square(1);
}
```

You can build a model such as voronoi_fibonacci2: