use a separate parameter for the hyper rectangle (#174)

KristofferC · Dec 27, 2023 · 3eca4e8 · 3eca4e8
1 parent dc04c19
commit 3eca4e8
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Showing 3 changed files with 11 additions and 12 deletions.
diff --git a/src/hyperrectangles.jl b/src/hyperrectangles.jl
@@ -21,7 +21,7 @@ function compute_bbox(data::AbstractVector{V}) where {V <: AbstractVector}
         maxes[j] = dim_max
         mins[j] = dim_min
     end
-    return HyperRectangle(V(mins), V(maxes))
+    return HyperRectangle(SVector(mins), SVector(maxes))
 end
 
 

diff --git a/src/kd_tree.jl b/src/kd_tree.jl
@@ -5,9 +5,9 @@ struct KDNode{T}
     split_dim::Int16  # The dimension the hyper rectangle was split at
 end
 
-struct KDTree{V <: AbstractVector, M <: MinkowskiMetric, T} <: NNTree{V,M}
+struct KDTree{V <: AbstractVector, M <: MinkowskiMetric, T, TH} <: NNTree{V,M}
     data::Vector{V}
-    hyper_rec::HyperRectangle{V}
+    hyper_rec::HyperRectangle{TH}
     indices::Vector{Int}
     metric::M
     nodes::Vector{KDNode{T}}
@@ -31,7 +31,6 @@ function KDTree(data::AbstractVector{V},
     reorder = !isempty(reorderbuffer) || (storedata ? reorder : false)
 
     tree_data = TreeData(data, leafsize)
-    n_d = length(V)
     n_p = length(data)
 
     indices = collect(1:n_p)
@@ -77,7 +76,6 @@ function KDTree(data::AbstractVector{V},
         end
     end
 
-    backup_rec = HyperRectangle(copy(hyper_rec.mins), copy(hyper_rec.maxes))
     KDTree(storedata ? data : similar(data, 0), hyper_rec, indices, metric, nodes, tree_data, reorder)
 end
 
@@ -99,13 +97,6 @@ end
            reorderbuffer = reorderbuffer_points)
 end
 
-Base.@propagate_inbounds function setindex(s::StaticArray, v, i)
-    return StaticArrays.setindex(s, v, i)
-end
-Base.@propagate_inbounds function setindex(s::V, v, i) where {V <: AbstractArray}
-    return V(setindex(SVector{length(V)}(s), v, i))
-end
-
 function build_KDTree(index::Int,
                       data::AbstractVector{V},
                       data_reordered::Vector{V},

diff --git a/test/test_knn.jl b/test/test_knn.jl
@@ -116,3 +116,11 @@ import Tensors
               nn(stree, vpoints) == nn(stree, spoints)
     end
 end
+
+
+@testset "subarray" begin
+    dynamic_view(X) = [NearestNeighbors.SizedVector{length(v)}(v) for v in eachslice(X; dims = ndims(X))]
+    data = randn(1000, 1000)
+    view = dynamic_view(data)
+    @test KDTree(view) isa KDTree
+end