poisson2disk: Poisson Disk Sampling

In pracma: Practical Numerical Math Functions

Poisson Disk Sampling

Description

Approximate Poisson disk distribution of points in a rectangle.

Usage

poisson2disk(n, a = 1, b = 1, m = 10, info = TRUE)

Arguments

n	number of points to generate in a rectangle.
a, b	width and height of the rectangle
m	number of points to try in each step.
info	shall additional info be printed.

Details

Realizes Mitchell's best-candidate algorithm for creating a Poisson disk distribution on a rectangle. Can be used for sampling, and will be more appropriate in some sampling applications than uniform sampling or grid-like sampling.

With m = 1 uniform sampling will be generated.

Value

Returns the points as a matrix with two columns for x- and y-coordinates. Prints the minimal distance between points generated.

Note

Bridson's algorithm for Poisson disk sampling may be added later as an alternative. Also a variant that generates points in a circle.

References

A. Lagae and Ph. Dutre. A Comparison of Methods for Generating Poisson Disk Distributions. Computer Graphics Forum, Vol. 27(1), pp. 114-129, 2008. URL: citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.192.5862

Examples

set.seed(1111)
P <- poisson2disk(n = 20, m = 10)
head(P)
##            [,1]       [,2]
## [1,] 0.46550264 0.41292487
## [2,] 0.13710541 0.98737065
## [3,] 0.96028255 0.83222920
## [4,] 0.06044078 0.09325431
## [5,] 0.78579426 0.09267546
## [6,] 0.49670274 0.99852771

# Plotting points
# plot(P, pch = 'x', col = "blue")

pracma documentation built on Nov. 10, 2023, 1:14 a.m.