Feature/distance gradient

Project.toml

@@ -5,6 +5,7 @@ version = "0.0.1"
 
 [deps]
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
+NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
 [compat]

docs/src/gallery.md

@@ -27,8 +27,15 @@ heatmap(rand(EdgeGradient(), (45, 45)))
 heatmap(rand(WaveSurface(), (45, 45)))
 ```
 
+## Distance gradient
+
+```@example gallery
+sources = unique(rand(1:2025, 15))
+heatmap(rand(DistanceGradient(sources), (45, 45)))
+```
+
 ## Rectangular cluster
 
 ```@example gallery
 heatmap(rand(RectangularCluster(), (45, 45)))
-```
+```

docs/src/index.md

@@ -10,6 +10,7 @@ NoGradient
 PlanarGradient
 EdgeGradient
 WaveSurface
+DistanceGradient
 RectangularCluster
 ```
 

src/NeutralLandscapes.jl

@@ -2,6 +2,7 @@ module NeutralLandscapes
 
 import NaNMath
 using Random: rand!
+using NearestNeighbors
 
 abstract type NeutralLandscapeMaker end
 export NeutralLandscapeMaker
@@ -21,6 +22,9 @@ export EdgeGradient
 include(joinpath("algorithms", "wavesurface.jl"))
 export WaveSurface
 
+include(joinpath("algorithms", "distancegradient.jl"))
+export DistanceGradient
+
 include(joinpath("algorithms", "rectangularcluster.jl"))
 export RectangularCluster
 

src/algorithms/distancegradient.jl

@@ -0,0 +1,25 @@
+"""
+    DistanceGradient
+
+The `sources` field is the *linear* indices of the matrix, from which the
+distance must be calculated.
+"""
+struct DistanceGradient <: NeutralLandscapeMaker
+    sources::Vector{Integer}
+end
+
+DistanceGradient() = DistanceGradient([1])
+
+function _landscape!(mat, alg::DistanceGradient)
+    @assert maximum(alg.sources) <= length(mat)
+    @assert minimum(alg.sources) > 0
+    indices = vcat(CartesianIndices(mat)...)
+    coordinates = zeros(Float64, (2, length(indices)))
+    coordinates[1,:] .= getindex.(indices, 1)
+    coordinates[2,:] .= getindex.(indices, 2)
+    guesses = coordinates[:,setdiff(eachindex(mat),alg.sources)]
+    tree = KDTree(coordinates[:,alg.sources])
+    mat[setdiff(eachindex(mat),alg.sources)] .= nn(tree, guesses)[2]
+    mat[alg.sources] .= 0.0
+    return mat
+end

src/algorithms/nogradient.jl

@@ -6,4 +6,4 @@ This type is used to generate a random landscape with no gradients
 struct NoGradient <: NeutralLandscapeMaker
 end
 
-_landscape!(mat, ::NoGradient) where {IT <: Integer} = rand!(mat)
+_landscape!(mat, ::NoGradient) = rand!(mat)