Processes

Point processes can be simulated with the function rand on different geometries:

Base.rand — Method

rand([rng], p, g, n=1; [algo])

Generate n realizations of spatial point process p inside geometry g. Optionally specify sampling algorithm algo and random number generator rng.

For example, a Poisson process with given intensity in a rectangular region:

p = PoissonProcess(0.1)
b = Box((0.,0.), (100.,100.))

s = rand(p, b, 2)

plot(plot(s[1]), plot(s[2]))

or the superposition of two Binomial processes:

p₁ = BinomialProcess(50)
p₂ = BinomialProcess(50)
p  = p₁ ∪ p₂ # 100 points

s = rand(p, b, 2)

plot(plot(s[1]), plot(s[2]))

The homogeneity property of a point process can be checked with the ishomogeneous function:

PointPatterns.ishomogeneous — Function

ishomogeneous(p)

Tells whether or not the spatial point process p is homogeneous.

Below is the list of currently implemented point processes.

BinomialProcess

PointPatterns.BinomialProcess — Type

BinomialProcess(n)

A Binomial point process with n points.

PoissonProcess

PointPatterns.PoissonProcess — Type

PoissonProcess(λ)

A Poisson process with intensity λ.

UnionProcess

PointPatterns.UnionProcess — Type

UnionProcess(p₁, p₂)

Union (or superposition) of spatial point processes p₁ and p₂.