[][src]Crate poisson_diskus

Sampling of a Poisson disk distribution in multiple dimensions.

The Poisson disk distribution produces samples of which no two samples are too close to each other. This results in a more uniform distribution than from pure random sampling.

This library is an implementation of the algorithm introduced by Robert Bridson [1] which is O(N) for producing N samples. That is, the sampling time increases linearly with the number of produced samples. For two-dimensional sampling, the sampling time increases with the area and for three-dimensional sampling with the volume.

Examples

Three dimensions

use poisson_diskus::bridson;
 
let box_size = [3.0, 5.0, 7.0];
let rmin = 0.5;
let num_attempts = 30;
 
let coords = bridson(&box_size, rmin, num_attempts).unwrap();

Larger number of dimensions

use poisson_diskus::bridson;
 
let box_size = [3.0, 5.0, 3.0, 2.0, 1.0];
let rmin = 1.0;
let num_attempts = 30;
 
let coords = bridson(&box_size, rmin, num_attempts).unwrap();
 
for coord in coords {
    assert_eq!(coord.len(), box_size.len());
}

Citations

[1] Bridson, R. (2007). Fast Poisson disk sampling in arbitrary dimensions. SIGGRAPH sketches, 10, 1.

Enums

Error

Errors encountered when sampling coordinates.

Functions

bridson

Generate samples from a Poisson disc distribution within the given box.

bridson_rng

Generate samples from a Poisson disc distribution using a specific random number generator.