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Reactivated tests (forgot to do it in last commit).
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‎test/maintests.jl‎

Lines changed: 124 additions & 124 deletions
Original file line numberDiff line numberDiff line change
@@ -2,130 +2,130 @@ using GPUArrays
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using ReadVTK, WriteVTK
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@info "Test backends: $(join(arrays,", "))"
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# @testset "util.jl" begin
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# I = CartesianIndex(1,2,3,4)
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# @test I+δ(3,I) == CartesianIndex(1,2,4,4)
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# @test WaterLily.CI(I,5)==CartesianIndex(1,2,3,4,5)
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# @test WaterLily.CIj(3,I,5)==CartesianIndex(1,2,5,4)
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# @test WaterLily.CIj(2,CartesianIndex(16,16,16,3),14)==CartesianIndex(16,14,16,3)
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# @test loc(3,CartesianIndex(3,4,5)) == SVector(3,4,4.5) .- 1.5
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# I = CartesianIndex(rand(2:10,3)...)
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# @test loc(0,I) == SVector(I.I...) .- 1.5
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# ex,sym = :(a[I,i] = Math.add(p.b[I],func(I,q))),[]
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# WaterLily.grab!(sym,ex)
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# @test ex == :(a[I, i] = Math.add(b[I], func(I, q)))
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# @test sym == [:a, :I, :i, :(p.b), :q]
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# for f ∈ arrays
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# p = zeros(4,5) |> f
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# apply!(x->x[1]+x[2]+3,p) # add 2×1.5 to move edge to origin
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# @test inside(p) == CartesianIndices((2:3,2:4))
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# @test inside(p,buff=0) == CartesianIndices(p)
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# @test L₂(p) == 187
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# u = zeros(5,5,2) |> f
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# apply!((i,x)->x[i],u)
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# @test GPUArrays.@allowscalar [u[i,j,1].-(i-2) for i in 1:3, j in 1:3]==zeros(3,3)
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# Ng, D, U = (6, 6), 2, (1.0, 0.5)
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# u = rand(Ng..., D) |> f # vector
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# σ = rand(Ng...) |> f # scalar
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# BC!(u, U)
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# @test GPUArrays.@allowscalar all(u[1, :, 1] .== U[1]) && all(u[2, :, 1] .== U[1]) && all(u[end, :, 1] .== U[1]) &&
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# all(u[3:end-1, 1, 1] .== u[3:end-1, 2, 1]) && all(u[3:end-1, end, 1] .== u[3:end-1, end-1, 1])
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# @test GPUArrays.@allowscalar all(u[:, 1, 2] .== U[2]) && all(u[:, 2, 2] .== U[2]) && all(u[:, end, 2] .== U[2]) &&
39-
# all(u[1, 3:end-1, 2] .== u[2, 3:end-1, 2]) && all(u[end, 3:end-1, 2] .== u[end-1, 3:end-1, 2])
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# GPUArrays.@allowscalar u[end,:,1] .= 3
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# BC!(u,U,true) # save exit values
43-
# @test GPUArrays.@allowscalar all(u[end, :, 1] .== 3)
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# WaterLily.exitBC!(u,u,0) # conservative exit check
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# @test GPUArrays.@allowscalar all(u[end,2:end-1, 1] .== U[1])
47-
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# # test BC with function
49-
# Ubc(i,x,t) = i==1 ? 1.0 : 0.5
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# v = rand(Ng..., D) |> f # vector
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# BC!(v,Ubc,false); BC!(u,U,false) # make sure we apply the same
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# @test all(v[1, :, 1] .≈ u[1, :, 1]) && all(v[2, :, 1] .≈ u[2, :, 1]) && all(v[end, :, 1] .≈ u[end, :, 1])
53-
# @test all(v[:, 1, 2] .≈ u[:, 1, 2]) && all(v[:, 2, 2] .≈ u[:, 2, 2]) && all(v[:, end, 2] .≈ u[:, end, 2])
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# # test exit bc
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# GPUArrays.@allowscalar v[end,:,1] .= 3
56-
# BC!(v,Ubc,true) # save exit values
57-
# @test GPUArrays.@allowscalar all(v[end, :, 1] .== 3)
58-
59-
# BC!(u,U,true,(2,)) # periodic in y and save exit values
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# @test GPUArrays.@allowscalar all(u[:, 1:2, 1] .== u[:, end-1:end, 1]) && all(u[:, 1:2, 1] .== u[:,end-1:end,1])
61-
# WaterLily.perBC!(σ,(1,2)) # periodic in two directions
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# @test GPUArrays.@allowscalar all(σ[1, 2:end-1] .== σ[end-1, 2:end-1]) && all(σ[2:end-1, 1] .== σ[2:end-1, end-1])
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# u = rand(Ng..., D) |> f # vector
65-
# BC!(u,U,true,(1,)) #saveexit has no effect here as x-periodic
66-
# @test GPUArrays.@allowscalar all(u[1:2, :, 1] .== u[end-1:end, :, 1]) && all(u[1:2, :, 2] .== u[end-1:end, :, 2]) &&
67-
# all(u[:, 1, 2] .== U[2]) && all(u[:, 2, 2] .== U[2]) && all(u[:, end, 2] .== U[2])
68-
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# # test interpolation
70-
# a = zeros(5,5,2) |> f; b = zeros(5,5) |> f
71-
# apply!((i,x)->x[i]+1.5,a); apply!(x->x[1]+1.5,b) # offset for start of grid
72-
# @test GPUArrays.@allowscalar all(WaterLily.interp(SVector(2.5,1),a) .≈ [2.5,1.])
73-
# @test GPUArrays.@allowscalar all(WaterLily.interp(SVector(3.5,3),a) .≈ [3.5,3.])
74-
# @test GPUArrays.@allowscalar WaterLily.interp(SVector(2.5,1),b) ≈ 2.5
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# @test GPUArrays.@allowscalar WaterLily.interp(SVector(3.5,3),b) ≈ 3.5
76-
# end
77-
# end
78-
79-
# function Poisson_setup(poisson,N::NTuple{D};f=Array,T=Float32) where D
80-
# c = ones(T,N...,D) |> f; BC!(c, ntuple(zero,D))
81-
# x = zeros(T,N) |> f; z = copy(x)
82-
# pois = poisson(x,c,z)
83-
# soln = map(I->T(I.I[1]),CartesianIndices(N)) |> f
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# I = first(inside(x))
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# GPUArrays.@allowscalar @. soln -= soln[I]
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# z = mult!(pois,soln)
87-
# solver!(pois)
88-
# GPUArrays.@allowscalar @. x -= x[I]
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# return L₂(x-soln)/L₂(soln),pois
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# end
91-
92-
# @testset "Poisson.jl" begin
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# for f ∈ arrays
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# err,pois = Poisson_setup(Poisson,(5,5);f)
95-
# @test GPUArrays.@allowscalar parent(pois.D)==f(Float32[0 0 0 0 0; 0 -2 -3 -2 0; 0 -3 -4 -3 0; 0 -2 -3 -2 0; 0 0 0 0 0])
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# @test GPUArrays.@allowscalar parent(pois.iD)≈f(Float32[0 0 0 0 0; 0 -1/2 -1/3 -1/2 0; 0 -1/3 -1/4 -1/3 0; 0 -1/2 -1/3 -1/2 0; 0 0 0 0 0])
97-
# @test err < 1e-5
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# err,pois = Poisson_setup(Poisson,(2^6+2,2^6+2);f)
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# @test err < 1e-6
100-
# @test pois.n[] < 310
101-
# err,pois = Poisson_setup(Poisson,(2^4+2,2^4+2,2^4+2);f)
102-
# @test err < 1e-6
103-
# @test pois.n[] < 35
104-
# end
105-
# end
106-
107-
# @testset "MultiLevelPoisson.jl" begin
108-
# I = CartesianIndex(4,3,2)
109-
# @test all(WaterLily.down(J)==I for J ∈ WaterLily.up(I))
110-
# @test_throws AssertionError("MultiLevelPoisson requires size=a2ⁿ, where n>2") Poisson_setup(MultiLevelPoisson,(15+2,3^4+2))
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112-
# err,pois = Poisson_setup(MultiLevelPoisson,(10,10))
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# @test pois.levels[3].D == Float32[0 0 0 0; 0 -2 -2 0; 0 -2 -2 0; 0 0 0 0]
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# @test err < 1e-5
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# pois.levels[1].L[5:6,:,1].=0
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# WaterLily.update!(pois)
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# @test pois.levels[3].D == Float32[0 0 0 0; 0 -1 -1 0; 0 -1 -1 0; 0 0 0 0]
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# for f ∈ arrays
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# err,pois = Poisson_setup(MultiLevelPoisson,(2^6+2,2^6+2);f)
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# @test err < 1e-6
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# @test pois.n[] ≤ 3
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# err,pois = Poisson_setup(MultiLevelPoisson,(2^4+2,2^4+2,2^4+2);f)
125-
# @test err < 1e-6
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# @test pois.n[] ≤ 3
127-
# end
128-
# end
5+
@testset "util.jl" begin
6+
I = CartesianIndex(1,2,3,4)
7+
@test I+δ(3,I) == CartesianIndex(1,2,4,4)
8+
@test WaterLily.CI(I,5)==CartesianIndex(1,2,3,4,5)
9+
@test WaterLily.CIj(3,I,5)==CartesianIndex(1,2,5,4)
10+
@test WaterLily.CIj(2,CartesianIndex(16,16,16,3),14)==CartesianIndex(16,14,16,3)
11+
12+
@test loc(3,CartesianIndex(3,4,5)) == SVector(3,4,4.5) .- 1.5
13+
I = CartesianIndex(rand(2:10,3)...)
14+
@test loc(0,I) == SVector(I.I...) .- 1.5
15+
16+
ex,sym = :(a[I,i] = Math.add(p.b[I],func(I,q))),[]
17+
WaterLily.grab!(sym,ex)
18+
@test ex == :(a[I, i] = Math.add(b[I], func(I, q)))
19+
@test sym == [:a, :I, :i, :(p.b), :q]
20+
21+
for f ∈ arrays
22+
p = zeros(4,5) |> f
23+
apply!(x->x[1]+x[2]+3,p) # add 2×1.5 to move edge to origin
24+
@test inside(p) == CartesianIndices((2:3,2:4))
25+
@test inside(p,buff=0) == CartesianIndices(p)
26+
@test L₂(p) == 187
27+
28+
u = zeros(5,5,2) |> f
29+
apply!((i,x)->x[i],u)
30+
@test GPUArrays.@allowscalar [u[i,j,1].-(i-2) for i in 1:3, j in 1:3]==zeros(3,3)
31+
32+
Ng, D, U = (6, 6), 2, (1.0, 0.5)
33+
u = rand(Ng..., D) |> f # vector
34+
σ = rand(Ng...) |> f # scalar
35+
BC!(u, U)
36+
@test GPUArrays.@allowscalar all(u[1, :, 1] .== U[1]) && all(u[2, :, 1] .== U[1]) && all(u[end, :, 1] .== U[1]) &&
37+
all(u[3:end-1, 1, 1] .== u[3:end-1, 2, 1]) && all(u[3:end-1, end, 1] .== u[3:end-1, end-1, 1])
38+
@test GPUArrays.@allowscalar all(u[:, 1, 2] .== U[2]) && all(u[:, 2, 2] .== U[2]) && all(u[:, end, 2] .== U[2]) &&
39+
all(u[1, 3:end-1, 2] .== u[2, 3:end-1, 2]) && all(u[end, 3:end-1, 2] .== u[end-1, 3:end-1, 2])
40+
41+
GPUArrays.@allowscalar u[end,:,1] .= 3
42+
BC!(u,U,true) # save exit values
43+
@test GPUArrays.@allowscalar all(u[end, :, 1] .== 3)
44+
45+
WaterLily.exitBC!(u,u,0) # conservative exit check
46+
@test GPUArrays.@allowscalar all(u[end,2:end-1, 1] .== U[1])
47+
48+
# test BC with function
49+
Ubc(i,x,t) = i==1 ? 1.0 : 0.5
50+
v = rand(Ng..., D) |> f # vector
51+
BC!(v,Ubc,false); BC!(u,U,false) # make sure we apply the same
52+
@test all(v[1, :, 1] .≈ u[1, :, 1]) && all(v[2, :, 1] .≈ u[2, :, 1]) && all(v[end, :, 1] .≈ u[end, :, 1])
53+
@test all(v[:, 1, 2] .≈ u[:, 1, 2]) && all(v[:, 2, 2] .≈ u[:, 2, 2]) && all(v[:, end, 2] .≈ u[:, end, 2])
54+
# test exit bc
55+
GPUArrays.@allowscalar v[end,:,1] .= 3
56+
BC!(v,Ubc,true) # save exit values
57+
@test GPUArrays.@allowscalar all(v[end, :, 1] .== 3)
58+
59+
BC!(u,U,true,(2,)) # periodic in y and save exit values
60+
@test GPUArrays.@allowscalar all(u[:, 1:2, 1] .== u[:, end-1:end, 1]) && all(u[:, 1:2, 1] .== u[:,end-1:end,1])
61+
WaterLily.perBC!(σ,(1,2)) # periodic in two directions
62+
@test GPUArrays.@allowscalar all(σ[1, 2:end-1] .== σ[end-1, 2:end-1]) && all(σ[2:end-1, 1] .== σ[2:end-1, end-1])
63+
64+
u = rand(Ng..., D) |> f # vector
65+
BC!(u,U,true,(1,)) #saveexit has no effect here as x-periodic
66+
@test GPUArrays.@allowscalar all(u[1:2, :, 1] .== u[end-1:end, :, 1]) && all(u[1:2, :, 2] .== u[end-1:end, :, 2]) &&
67+
all(u[:, 1, 2] .== U[2]) && all(u[:, 2, 2] .== U[2]) && all(u[:, end, 2] .== U[2])
68+
69+
# test interpolation
70+
a = zeros(5,5,2) |> f; b = zeros(5,5) |> f
71+
apply!((i,x)->x[i]+1.5,a); apply!(x->x[1]+1.5,b) # offset for start of grid
72+
@test GPUArrays.@allowscalar all(WaterLily.interp(SVector(2.5,1),a) .≈ [2.5,1.])
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@test GPUArrays.@allowscalar all(WaterLily.interp(SVector(3.5,3),a) .≈ [3.5,3.])
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@test GPUArrays.@allowscalar WaterLily.interp(SVector(2.5,1),b) ≈ 2.5
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@test GPUArrays.@allowscalar WaterLily.interp(SVector(3.5,3),b) ≈ 3.5
76+
end
77+
end
78+
79+
function Poisson_setup(poisson,N::NTuple{D};f=Array,T=Float32) where D
80+
c = ones(T,N...,D) |> f; BC!(c, ntuple(zero,D))
81+
x = zeros(T,N) |> f; z = copy(x)
82+
pois = poisson(x,c,z)
83+
soln = map(I->T(I.I[1]),CartesianIndices(N)) |> f
84+
I = first(inside(x))
85+
GPUArrays.@allowscalar @. soln -= soln[I]
86+
z = mult!(pois,soln)
87+
solver!(pois)
88+
GPUArrays.@allowscalar @. x -= x[I]
89+
return L₂(x-soln)/L₂(soln),pois
90+
end
91+
92+
@testset "Poisson.jl" begin
93+
for f ∈ arrays
94+
err,pois = Poisson_setup(Poisson,(5,5);f)
95+
@test GPUArrays.@allowscalar parent(pois.D)==f(Float32[0 0 0 0 0; 0 -2 -3 -2 0; 0 -3 -4 -3 0; 0 -2 -3 -2 0; 0 0 0 0 0])
96+
@test GPUArrays.@allowscalar parent(pois.iD)≈f(Float32[0 0 0 0 0; 0 -1/2 -1/3 -1/2 0; 0 -1/3 -1/4 -1/3 0; 0 -1/2 -1/3 -1/2 0; 0 0 0 0 0])
97+
@test err < 1e-5
98+
err,pois = Poisson_setup(Poisson,(2^6+2,2^6+2);f)
99+
@test err < 1e-6
100+
@test pois.n[] < 310
101+
err,pois = Poisson_setup(Poisson,(2^4+2,2^4+2,2^4+2);f)
102+
@test err < 1e-6
103+
@test pois.n[] < 35
104+
end
105+
end
106+
107+
@testset "MultiLevelPoisson.jl" begin
108+
I = CartesianIndex(4,3,2)
109+
@test all(WaterLily.down(J)==I for J ∈ WaterLily.up(I))
110+
@test_throws AssertionError("MultiLevelPoisson requires size=a2ⁿ, where n>2") Poisson_setup(MultiLevelPoisson,(15+2,3^4+2))
111+
112+
err,pois = Poisson_setup(MultiLevelPoisson,(10,10))
113+
@test pois.levels[3].D == Float32[0 0 0 0; 0 -2 -2 0; 0 -2 -2 0; 0 0 0 0]
114+
@test err < 1e-5
115+
116+
pois.levels[1].L[5:6,:,1].=0
117+
WaterLily.update!(pois)
118+
@test pois.levels[3].D == Float32[0 0 0 0; 0 -1 -1 0; 0 -1 -1 0; 0 0 0 0]
119+
120+
for f ∈ arrays
121+
err,pois = Poisson_setup(MultiLevelPoisson,(2^6+2,2^6+2);f)
122+
@test err < 1e-6
123+
@test pois.n[] ≤ 3
124+
err,pois = Poisson_setup(MultiLevelPoisson,(2^4+2,2^4+2,2^4+2);f)
125+
@test err < 1e-6
126+
@test pois.n[] ≤ 3
127+
end
128+
end
129129

130130
@testset "Flow.jl" begin
131131
# test than vanLeer behaves correctly

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