Inhomogeneous (#35)

* simplify rand_single using _sampleweights

* update Meshes.jl interface for homogeneoussampling with weights

* Meshes.jl

* return pointset

* instantiate PointSet views

* Update src/PointPatterns.jl

---------

Co-authored-by: Júlio Hoffimann <julio.hoffimann@gmail.com>

Author: ErickChacon

src/processes/poisson.jl

@@ -52,15 +52,8 @@ function rand_single(rng::Random.AbstractRNG, p::PoissonProcess{<:Real}, g, ::Co
   V = measure(g)
   n = rand(rng, Poisson(λ * V))
 
-  if iszero(n)
-    nothing
-  else
-    # simulate homogeneous process
-    points = sample(g, HomogeneousSampling(n))
-
-    # return point pattern
-    PointSet(points)
-  end
+  # simulate n points
+  iszero(n) ? nothing : PointSet(sample(g, HomogeneousSampling(n)))
 end
 
 #--------------------
@@ -72,7 +65,8 @@ function rand_single(rng::Random.AbstractRNG, p::PoissonProcess{<:Function}, g,
   pp = rand_single(rng, PoissonProcess(algo.λmax), g, ConstantIntensity())
 
   # thin point pattern
-  thin(pp, RandomThinning(x -> p.λ(x) / algo.λmax))
+  points = thin(pp, RandomThinning(x -> p.λ(x) / algo.λmax))
+  PointSet(collect(points))
 end
 
 rand_single(rng::Random.AbstractRNG, p::PoissonProcess{<:Function}, d::Domain, algo::ConstantIntensity) =
@@ -85,17 +79,5 @@ function rand_single(rng::Random.AbstractRNG, p::PoissonProcess{<:AbstractVector
   n = rand(rng, Poisson(sum(λ .* V)))
 
   # simulate n points
-  if iszero(n)
-    nothing
-  else
-    # sample elements with weights proportial to expected number of points
-    w = WeightedSampling(n, λ .* V, replace=true)
-
-    # within each element sample a single point
-    sampler = HomogeneousSampling(1)
-    points = (first(sample(rng, e, sampler)) for e in sample(rng, d, w))
-
-    # return point pattern
-    PointSet(points)
-  end
+  iszero(n) ? nothing : PointSet(sample(rng, d, HomogeneousSampling(n, λ .* V)))
 end