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Add tests from TrixiParticles.jl
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‎test/grid_nhs.jl‎

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@testset verbose=true "GridNeighborhoodSearch" begin
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@testset "Coordinate Limits" begin
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# Test the threshold for very large and very small coordinates.
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coords1 = [Inf, -Inf]
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coords2 = [NaN, 0]
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coords3 = [typemax(Int) + 1.0, -typemax(Int) - 1.0]
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@test TrixiNeighborhoodSearch.cell_coords(coords1, nothing, (1.0, 1.0)) ==
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(typemax(Int), typemin(Int))
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@test TrixiNeighborhoodSearch.cell_coords(coords2, nothing, (1.0, 1.0)) ==
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(typemax(Int), 0)
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@test TrixiNeighborhoodSearch.cell_coords(coords3, nothing, (1.0, 1.0)) ==
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(typemax(Int), typemin(Int))
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end
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@testset "Rectangular Point Cloud 2D" begin
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#### Setup
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# Rectangular filled with equidistant spaced particles
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# from (x, y) = (-0.25, -0.25) to (x, y) = (0.35, 0.35)
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range = -0.25:0.1:0.35
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coordinates1 = hcat(collect.(Iterators.product(range, range))...)
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nparticles = size(coordinates1, 2)
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particle_position1 = [0.05, 0.05]
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particle_spacing = 0.1
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radius = particle_spacing
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# Create neighborhood search
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nhs1 = GridNeighborhoodSearch{2}(radius, nparticles)
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coords_fun(i) = coordinates1[:, i]
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initialize!(nhs1, coords_fun)
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# Get each neighbor for `particle_position1`
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neighbors1 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs1)))
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# Move particles
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coordinates2 = coordinates1 .+ [1.4, -3.5]
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# Update neighborhood search
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coords_fun2(i) = coordinates2[:, i]
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update!(nhs1, coords_fun2)
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# Get each neighbor for updated NHS
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neighbors2 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs1)))
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# Change position
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particle_position2 = particle_position1 .+ [1.4, -3.5]
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# Get each neighbor for `particle_position2`
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neighbors3 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position2,
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nhs1)))
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# Double search radius
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nhs2 = GridNeighborhoodSearch{2}(2 * radius, size(coordinates1, 2))
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initialize!(nhs2, coords_fun)
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# Get each neighbor in double search radius
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neighbors4 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs2)))
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# Move particles
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coordinates2 = coordinates1 .+ [0.4, -0.4]
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# Update neighborhood search
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update!(nhs2, coords_fun2)
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# Get each neighbor in double search radius
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neighbors5 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs2)))
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#### Verification
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@test neighbors1 == [17, 18, 19, 24, 25, 26, 31, 32, 33]
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@test neighbors2 == Int[]
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@test neighbors3 == [17, 18, 19, 24, 25, 26, 31, 32, 33]
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@test neighbors4 == [
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9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 23, 24, 25,
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26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47,
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48, 49]
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@test neighbors5 == [36, 37, 38, 43, 44, 45]
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end
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@testset "Rectangular Point Cloud 3D" begin
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#### Setup
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# Rectangular filled with equidistant spaced particles
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# from (x, y, z) = (-0.25, -0.25, -0.25) to (x, y) = (0.35, 0.35, 0.35)
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range = -0.25:0.1:0.35
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coordinates1 = hcat(collect.(Iterators.product(range, range, range))...)
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nparticles = size(coordinates1, 2)
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particle_position1 = [0.05, 0.05, 0.05]
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particle_spacing = 0.1
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radius = particle_spacing
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# Create neighborhood search
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nhs1 = GridNeighborhoodSearch{3}(radius, nparticles)
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coords_fun(i) = coordinates1[:, i]
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initialize!(nhs1, coords_fun)
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# Get each neighbor for `particle_position1`
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neighbors1 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs1)))
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# Move particles
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coordinates2 = coordinates1 .+ [1.4, -3.5, 0.8]
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# Update neighborhood search
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coords_fun2(i) = coordinates2[:, i]
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update!(nhs1, coords_fun2)
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# Get each neighbor for updated NHS
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neighbors2 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position1,
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nhs1)))
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# Change position
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particle_position2 = particle_position1 .+ [1.4, -3.5, 0.8]
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# Get each neighbor for `particle_position2`
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neighbors3 = sort(collect(TrixiNeighborhoodSearch.eachneighbor(particle_position2,
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nhs1)))
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#### Verification
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@test neighbors1 ==
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[115, 116, 117, 122, 123, 124, 129, 130, 131, 164, 165, 166, 171, 172,
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173, 178, 179, 180, 213, 214, 215, 220, 221, 222, 227, 228, 229]
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@test neighbors2 == Int[]
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@test neighbors3 ==
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[115, 116, 117, 122, 123, 124, 129, 130, 131, 164, 165, 166, 171, 172,
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173, 178, 179, 180, 213, 214, 215, 220, 221, 222, 227, 228, 229]
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end
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@testset verbose=true "Periodicity 2D" begin
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@testset "Simple Example" begin
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coords = [-0.08 0.0 0.18 0.1 -0.08
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-0.12 -0.05 -0.09 0.15 0.39]
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# 3 x 6 cells
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nhs = GridNeighborhoodSearch{2}(0.1, size(coords, 2),
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periodic_box_min_corner = [-0.1, -0.2],
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periodic_box_max_corner = [0.2, 0.4])
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initialize!(nhs, coords)
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neighbors = [sort(collect(TrixiNeighborhoodSearch.eachneighbor(coords[:, i],
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nhs)))
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for i in 1:5]
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# Note that (1, 2) and (2, 3) are not neighbors, but they are in neighboring cells
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@test neighbors[1] == [1, 2, 3, 5]
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@test neighbors[2] == [1, 2, 3]
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@test neighbors[3] == [1, 2, 3]
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@test neighbors[4] == [4]
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@test neighbors[5] == [1, 5]
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neighbors_loop = [Int[] for _ in axes(coords, 2)]
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for_particle_neighbor(coords, coords, nhs,
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particles = axes(coords, 2)) do particle,
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neighbor,
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pos_diff,
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distance
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append!(neighbors_loop[particle], neighbor)
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end
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@test sort(neighbors_loop[1]) == [1, 3, 5]
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@test sort(neighbors_loop[2]) == [2]
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@test sort(neighbors_loop[3]) == [1, 3]
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@test sort(neighbors_loop[4]) == [4]
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@test sort(neighbors_loop[5]) == [1, 5]
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end
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@testset "Rounding Up Cell Sizes" begin
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coords = [-0.08 0.0 0.18 0.1 -0.08
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-0.12 -0.05 -0.09 0.15 0.42]
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# 3 x 6 cells
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nhs = GridNeighborhoodSearch{2}(0.1, size(coords, 2),
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periodic_box_min_corner = [-0.1, -0.2],
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periodic_box_max_corner = [0.205, 0.43])
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initialize!(nhs, coords)
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neighbors = [sort(collect(TrixiNeighborhoodSearch.eachneighbor(coords[:, i],
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nhs)))
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for i in 1:5]
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# Note that (1, 2) and (2, 3) are not neighbors, but they are in neighboring cells
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@test neighbors[1] == [1, 2, 3, 5]
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@test neighbors[2] == [1, 2, 3]
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@test neighbors[3] == [1, 2, 3]
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@test neighbors[4] == [4]
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@test neighbors[5] == [1, 5]
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neighbors_loop = [Int[] for _ in axes(coords, 2)]
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for_particle_neighbor(coords, coords, nhs,
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particles = axes(coords, 2)) do particle,
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neighbor,
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pos_diff,
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distance
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append!(neighbors_loop[particle], neighbor)
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end
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@test sort(neighbors_loop[1]) == [1, 3, 5]
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@test sort(neighbors_loop[2]) == [2]
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@test sort(neighbors_loop[3]) == [1, 3]
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@test sort(neighbors_loop[4]) == [4]
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@test sort(neighbors_loop[5]) == [1, 5]
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end
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@testset "Offset Domain Triggering Split Cells" begin
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# This used to trigger a "split cell bug", where the left and right boundary
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# cells were only partially contained in the domain.
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# The left particle was placed inside a ghost cells, which causes it to not
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# see the right particle, even though it is within the search distance.
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# The domain size is an integer multiple of the cell size, but the NHS did not
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# offset the grid based on the domain position.
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# See https://github.com/trixi-framework/TrixiNeighborhoodSearch.jl/pull/211
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# for a more detailed explanation.
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coords = [-1.4 1.9
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0.0 0.0]
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# 5 x 1 cells
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nhs = GridNeighborhoodSearch{2}(1.0, size(coords, 2),
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periodic_box_min_corner = [-1.5, 0.0],
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periodic_box_max_corner = [2.5, 3.0])
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initialize!(nhs, coords)
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neighbors = [sort(unique(collect(TrixiNeighborhoodSearch.eachneighbor(coords[:,
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i],
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nhs))))
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for i in 1:2]
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@test neighbors[1] == [1, 2]
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@test neighbors[2] == [1, 2]
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end
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end
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@testset verbose=true "Periodicity 3D" begin
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coords = [-0.08 0.0 0.18 0.1 -0.08
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-0.12 -0.05 -0.09 0.15 0.39
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0.14 0.34 0.12 0.06 0.13]
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# 3 x 6 x 3 cells
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nhs = GridNeighborhoodSearch{3}(0.1, size(coords, 2),
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periodic_box_min_corner = [-0.1, -0.2, 0.05],
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periodic_box_max_corner = [0.2, 0.4, 0.35])
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initialize!(nhs, coords)
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neighbors = [sort(collect(TrixiNeighborhoodSearch.eachneighbor(coords[:, i], nhs)))
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for i in 1:5]
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# Note that (1, 2) and (2, 3) are not neighbors, but they are in neighboring cells
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@test neighbors[1] == [1, 2, 3, 5]
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@test neighbors[2] == [1, 2, 3]
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@test neighbors[3] == [1, 2, 3]
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@test neighbors[4] == [4]
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@test neighbors[5] == [1, 5]
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neighbors_loop = [Int[] for _ in axes(coords, 2)]
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for_particle_neighbor(coords, coords,
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nhs) do particle, neighbor, pos_diff, distance
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append!(neighbors_loop[particle], neighbor)
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end
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@test sort(neighbors_loop[1]) == [1, 3, 5]
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@test sort(neighbors_loop[2]) == [2]
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@test sort(neighbors_loop[3]) == [1, 3]
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@test sort(neighbors_loop[4]) == [4]
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@test sort(neighbors_loop[5]) == [1, 5]
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end
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end

‎test/runtests.jl‎

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include("test_util.jl")
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@testset verbose=true "TrixiNeighborhoodSearch.jl Tests" begin end
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@testset verbose=true "TrixiNeighborhoodSearch.jl Tests" begin
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include("trivial_nhs.jl")
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include("grid_nhs.jl")
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end

‎test/trivial_nhs.jl‎

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@testset verbose=true "TrivialNeighborhoodSearch" begin
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# Setup with 5 particles
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nhs = TrivialNeighborhoodSearch{2}(1.0, Base.OneTo(5))
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# Get each neighbor for arbitrary coordinates
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neighbors = collect(TrixiNeighborhoodSearch.eachneighbor([1.0, 2.0], nhs))
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#### Verification
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@test neighbors == [1, 2, 3, 4, 5]
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end

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