Add temporary svec util (#1186)

Author: juliohm

src/neighborsearch.jl

@@ -95,10 +95,3 @@ end
 include("neighborsearch/ball.jl")
 include("neighborsearch/knearest.jl")
 include("neighborsearch/kball.jl")
-
-# -----------------
-# HELPER FUNCTIONS
-# -----------------
-
-# NearestNeighbors.jl only accepts AbstractVector
-_svector(c::CRS) = SVector(CoordRefSystems.raw(c))

src/neighborsearch/ball.jl

@@ -20,7 +20,7 @@ end
 
 function BallSearch(domain::D, ball::B) where {D<:Domain,B<:MetricBall}
   m = metric(ball)
-  xs = [_svector(coords(centroid(domain, i))) for i in 1:nelements(domain)]
+  xs = [svec(centroid(domain, i)) for i in 1:nelements(domain)]
   tree = m isa MinkowskiMetric ? KDTree(xs, m) : BallTree(xs, m)
   BallSearch{D,B,typeof(tree)}(domain, ball, tree)
 end
@@ -36,7 +36,7 @@ function search(pₒ::Point, method::BallSearch; mask=nothing)
   r = ustrip(u, radius(method.ball))
 
   # adjust CRS of query point
-  x = _svector(convert(C, coords(pₒ)))
+  x = svec(convert(C, coords(pₒ)))
 
   inds = inrange(tree, x, r)
 

src/neighborsearch/kball.jl

@@ -22,7 +22,7 @@ end
 
 function KBallSearch(domain::D, k::Int, ball::B) where {D<:Domain,B<:MetricBall}
   m = metric(ball)
-  xs = [_svector(coords(centroid(domain, i))) for i in 1:nelements(domain)]
+  xs = [svec(centroid(domain, i)) for i in 1:nelements(domain)]
   tree = m isa MinkowskiMetric ? KDTree(xs, m) : BallTree(xs, m)
   KBallSearch{D,B,typeof(tree)}(domain, k, ball, tree)
 end
@@ -41,7 +41,7 @@ function searchdists!(neighbors, distances, pₒ::Point, method::KBallSearch; ma
   r = ustrip(u, radius(method.ball))
 
   # adjust CRS of query point
-  x = _svector(convert(C, coords(pₒ)))
+  x = svec(convert(C, coords(pₒ)))
 
   inds, dists = knn(tree, x, k, true)
 

src/neighborsearch/knearest.jl

@@ -18,7 +18,7 @@ struct KNearestSearch{D<:Domain,T} <: BoundedNeighborSearchMethod
 end
 
 function KNearestSearch(domain::D, k::Int; metric=Euclidean()) where {D<:Domain}
-  xs = [_svector(coords(centroid(domain, i))) for i in 1:nelements(domain)]
+  xs = [svec(centroid(domain, i)) for i in 1:nelements(domain)]
   tree = metric isa MinkowskiMetric ? KDTree(xs, metric) : BallTree(xs, metric)
   KNearestSearch{D,typeof(tree)}(domain, k, tree)
 end
@@ -34,7 +34,7 @@ function searchdists!(neighbors, distances, pₒ::Point, method::KNearestSearch;
   k = method.k
 
   # adjust CRS of query point
-  x = _svector(convert(C, coords(pₒ)))
+  x = svec(convert(C, coords(pₒ)))
 
   inds, dists = knn(tree, x, k, true)
 

src/traversing/source.jl

@@ -23,8 +23,7 @@ function traverse(domain, path::SourcePath)
   assertion(length(sources) ≤ nelements(domain), "more sources than points in object")
 
   # fit search tree
-  xs = [ustrip.(to(centroid(domain, s))) for s in sources]
-  kdtree = KDTree(xs)
+  kdtree = KDTree([svec(centroid(domain, s)) for s in sources])
 
   # other locations that are not sources
   others = setdiff(1:nelements(domain), sources)
@@ -35,8 +34,8 @@ function traverse(domain, path::SourcePath)
   # compute distances to sources
   dists = []
   for batch in batches
-    coords = [ustrip.(to(centroid(domain, b))) for b in batch]
-    _, ds = knn(kdtree, coords, length(sources), true)
+    xs = [svec(centroid(domain, b)) for b in batch]
+    _, ds = knn(kdtree, xs, length(sources), true)
     append!(dists, ds)
   end
 

src/utils/crs.jl

@@ -33,6 +33,19 @@ ignoring the original units of the coordinate reference system.
 flat(p::Point) = Point(flat(coords(p)))
 flat(c::CRS) = Cartesian{datum(c)}(CoordRefSystems.raw(c))
 
+"""
+    svec(p)
+
+Return `SVector` with raw coordinates of point `p`.
+
+### Notes
+
+This utility function exists because NearestNeighbors.jl
+currently only accepts coordinates of type `AbstractVector`.
+"""
+svec(p::Point) = svec(coords(p))
+svec(c::CRS) = SVector(CoordRefSystems.raw(c))
+
 """
     coordsum(points; weights=nothing)