AcceleratedArrays with spatial indexing
Author evetion
3 Stars
Updated Last
1 Year Ago
Started In
August 2019

Stable Dev Codecov


Accelerate Arrays using Spatial Indexes.

Combines AcceleratedArrays with LibSpatialIndex, speeding up area of interest queries, without having to do exact intersections on all geometries. Takes inspiration from the Python rtree package.

Note that as the acceleration works by using the extents of geometries, the filtered list of geometries is not guaranteed to intersect, we only guarantee that all intersecting geometries are present.


] add GeoAcceleratedArrays


Apply a spatial index on a Vector with geometries using accelerate, after which one can quickly find the intersecting extents for a given area of interest by findall with the in predicate.

AA = accelerate(A, RTreeIndex)
findall(in(aoi), AA)


using GeoAcceleratedArrays
using LibGEOS  # or any other GeoInterface compatible geometries

p1 = readgeom("POLYGON((0 0,1 0,1 1,0 0))")
p2 = readgeom("POLYGON((0 0,-1 0,-1 -1,0 0))")

acc_polys = accelerate([p1, p2], RTreeIndex)
2-element Vector{Polygon} + RTreeIndex with Extents.Extent{(:X, :Y), Tuple{Tuple{Float64, Float64}, Tuple{Float64, Float64}}}((X = (-1.0, 1.0), Y = (-1.0, 1.0))):
 Polygon(Ptr{Nothing} @0x00006000030d2d00)
 Polygon(Ptr{Nothing} @0x00006000030d23a0)

aoi = Extents.Extent(X=(0.5, 1), Y=(0.5, 1))
Extent(X = (0.5, 1.0), Y = (0.5, 1.0))

indices = findall(in(aoi), acc_polys)
1-element Vector{Int64}:

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