|
1 | | -module ScalingTests |
2 | | - |
3 | 1 | using Interpolations |
4 | 2 | using Test, LinearAlgebra |
5 | 3 |
|
6 | | -# Model linear interpolation of y = -3 + .5x by interpolating y=x |
7 | | -# and then scaling to the new x range |
8 | | - |
9 | | -itp = interpolate(1:1.0:10, BSpline(Linear()), OnGrid()) |
| 4 | +@testset "Scaling" begin |
| 5 | + # Model linear interpolation of y = -3 + .5x by interpolating y=x |
| 6 | + # and then scaling to the new x range |
10 | 7 |
|
11 | | -sitp = @inferred(scale(itp, -3:.5:1.5)) |
12 | | -@test typeof(sitp) <: Interpolations.ScaledInterpolation |
13 | | -@test parent(sitp) === itp |
14 | | - |
15 | | -for (x,y) in zip(-3:.05:1.5, 1:.1:10) |
16 | | - @test sitp[x] ≈ y |
17 | | -end |
| 8 | + itp = interpolate(1:1.0:10, BSpline(Linear()), OnGrid()) |
18 | 9 |
|
19 | | -# Verify that it works in >1D, with different types of ranges |
| 10 | + sitp = @inferred(scale(itp, -3:.5:1.5)) |
| 11 | + @test typeof(sitp) <: Interpolations.ScaledInterpolation |
| 12 | + @test parent(sitp) === itp |
20 | 13 |
|
21 | | -gauss(phi, mu, sigma) = exp(-(phi-mu)^2 / (2sigma)^2) |
22 | | -testfunction(x,y) = gauss(x, 0.5, 4) * gauss(y, -.5, 2) |
| 14 | + for (x,y) in zip(-3:.05:1.5, 1:.1:10) |
| 15 | + @test sitp(x) ≈ y |
| 16 | + end |
23 | 17 |
|
24 | | -xs = -5:.5:5 |
25 | | -ys = -4:.2:4 |
26 | | -zs = Float64[testfunction(x,y) for x in xs, y in ys] |
| 18 | + # Verify that it works in >1D, with different types of ranges |
27 | 19 |
|
28 | | -itp2 = interpolate(zs, BSpline(Quadratic(Flat())), OnGrid()) |
29 | | -sitp2 = @inferred scale(itp2, xs, ys) |
| 20 | + gauss(phi, mu, sigma) = exp(-(phi-mu)^2 / (2sigma)^2) |
| 21 | + testfunction(x,y) = gauss(x, 0.5, 4) * gauss(y, -.5, 2) |
30 | 22 |
|
31 | | -for x in xs, y in ys |
32 | | - @test testfunction(x,y) ≈ sitp2[x,y] |
33 | | -end |
| 23 | + xs = -5:.5:5 |
| 24 | + ys = -4:.2:4 |
| 25 | + zs = Float64[testfunction(x,y) for x in xs, y in ys] |
34 | 26 |
|
35 | | -# Test gradients of scaled grids |
36 | | -xs = -pi:.1:pi |
37 | | -ys = map(sin, xs) |
38 | | -itp = interpolate(ys, BSpline(Linear()), OnGrid()) |
39 | | -sitp = @inferred scale(itp, xs) |
| 27 | + itp2 = interpolate(zs, BSpline(Quadratic(Flat())), OnGrid()) |
| 28 | + sitp2 = @inferred scale(itp2, xs, ys) |
40 | 29 |
|
41 | | -for x in -pi:.1:pi |
42 | | - g = @inferred(Interpolations.gradient(sitp, x))[1] |
43 | | - @test ≈(cos(x),g,atol=0.05) |
44 | | -end |
| 30 | + for x in xs, y in ys |
| 31 | + @test testfunction(x,y) ≈ sitp2(x,y) |
| 32 | + end |
45 | 33 |
|
46 | | -# Verify that return types are reasonable |
47 | | -@inferred(getindex(sitp2, -3.4, 1.2)) |
48 | | -@inferred(getindex(sitp2, -3, 1)) |
49 | | -@inferred(getindex(sitp2, -3.4, 1)) |
50 | | - |
51 | | -sitp32 = @inferred scale(interpolate(Float32[testfunction(x,y) for x in -5:.5:5, y in -4:.2:4], BSpline(Quadratic(Flat())), OnGrid()), -5f0:.5f0:5f0, -4f0:.2f0:4f0) |
52 | | -@test typeof(@inferred(getindex(sitp32, -3.4f0, 1.2f0))) == Float32 |
53 | | - |
54 | | -# Iteration |
55 | | -itp = interpolate(rand(3,3,3), BSpline(Quadratic(Flat())), OnCell()) |
56 | | -knots = map(d->1:10:21, 1:3) |
57 | | -sitp = @inferred scale(itp, knots...) |
58 | | - |
59 | | -iter = @inferred(eachvalue(sitp)) |
60 | | - |
61 | | -@static if VERSION < v"0.7.0-DEV.5126" |
62 | | - state = @inferred(start(iter)) |
63 | | - @test !(@inferred(done(iter, state))) |
64 | | - val, state = @inferred(next(iter, state)) |
65 | | -else |
66 | | - iter_next = iterate(iter) |
67 | | - @test iter_next isa Tuple |
68 | | - @test iter_next[1] isa Float64 |
69 | | - state = iter_next[2] |
70 | | - inferred_next = Base.return_types(iterate, (typeof(iter),)) |
71 | | - @test length(inferred_next) == 1 |
72 | | - @test inferred_next[1] == Union{Nothing,Tuple{Float64,typeof(state)}} |
73 | | - iter_next = iterate(iter, state) |
74 | | - @test iter_next isa Tuple |
75 | | - @test iter_next[1] isa Float64 |
76 | | - inferred_next = Base.return_types(iterate, (typeof(iter),typeof(state))) |
77 | | - state = iter_next[2] |
78 | | - @test length(inferred_next) == 1 |
79 | | - @test inferred_next[1] == Union{Nothing,Tuple{Float64,typeof(state)}} |
80 | | -end |
| 34 | + # Test gradients of scaled grids |
| 35 | + xs = -pi:.1:pi |
| 36 | + ys = map(sin, xs) |
| 37 | + itp = interpolate(ys, BSpline(Linear()), OnGrid()) |
| 38 | + sitp = @inferred scale(itp, xs) |
81 | 39 |
|
82 | | -function foo!(dest, sitp) |
83 | | - i = 0 |
84 | | - for s in eachvalue(sitp) |
85 | | - dest[i+=1] = s |
86 | | - end |
87 | | - dest |
88 | | -end |
89 | | -function bar!(dest, sitp) |
90 | | - for I in CartesianIndices(size(dest)) |
91 | | - dest[I] = sitp[I] |
| 40 | + for x in -pi:.1:pi |
| 41 | + g = @inferred(Interpolations.gradient(sitp, x))[1] |
| 42 | + @test ≈(cos(x),g,atol=0.05) |
92 | 43 | end |
93 | | - dest |
94 | | -end |
95 | | -rfoo = Array{Float64}(undef, Interpolations.ssize(sitp)) |
96 | | -rbar = similar(rfoo) |
97 | | -foo!(rfoo, sitp) |
98 | | -bar!(rbar, sitp) |
99 | | -@test rfoo ≈ rbar |
| 44 | + |
| 45 | + # Verify that return types are reasonable |
| 46 | + @inferred(sitp2(-3.4, 1.2)) |
| 47 | + @inferred(sitp2(-3, 1)) |
| 48 | + @inferred(sitp2(-3.4, 1)) |
| 49 | + |
| 50 | + sitp32 = @inferred scale(interpolate(Float32[testfunction(x,y) for x in -5:.5:5, y in -4:.2:4], BSpline(Quadratic(Flat())), OnGrid()), -5f0:.5f0:5f0, -4f0:.2f0:4f0) |
| 51 | + @test typeof(@inferred(sitp32(-3.4f0, 1.2f0))) == Float32 |
| 52 | + |
| 53 | + # # Iteration |
| 54 | + # itp = interpolate(rand(3,3,3), BSpline(Quadratic(Flat())), OnCell()) |
| 55 | + # knots = map(d->1:10:21, 1:3) |
| 56 | + # sitp = @inferred scale(itp, knots...) |
| 57 | + |
| 58 | + # iter = @inferred(eachvalue(sitp)) |
| 59 | + |
| 60 | + # iter_next = iterate(iter) |
| 61 | + # @test iter_next isa Tuple |
| 62 | + # @test iter_next[1] isa Float64 |
| 63 | + # state = iter_next[2] |
| 64 | + # inferred_next = Base.return_types(iterate, (typeof(iter),)) |
| 65 | + # @test length(inferred_next) == 1 |
| 66 | + # @test inferred_next[1] == Union{Nothing,Tuple{Float64,typeof(state)}} |
| 67 | + # iter_next = iterate(iter, state) |
| 68 | + # @test iter_next isa Tuple |
| 69 | + # @test iter_next[1] isa Float64 |
| 70 | + # inferred_next = Base.return_types(iterate, (typeof(iter),typeof(state))) |
| 71 | + # state = iter_next[2] |
| 72 | + # @test length(inferred_next) == 1 |
| 73 | + # @test inferred_next[1] == Union{Nothing,Tuple{Float64,typeof(state)}} |
| 74 | + |
| 75 | + # function foo!(dest, sitp) |
| 76 | + # i = 0 |
| 77 | + # for s in eachvalue(sitp) |
| 78 | + # dest[i+=1] = s |
| 79 | + # end |
| 80 | + # dest |
| 81 | + # end |
| 82 | + # function bar!(dest, sitp) |
| 83 | + # for I in CartesianIndices(size(dest)) |
| 84 | + # dest[I] = sitp[I] |
| 85 | + # end |
| 86 | + # dest |
| 87 | + # end |
| 88 | + # rfoo = Array{Float64}(undef, Interpolations.ssize(sitp)) |
| 89 | + # rbar = similar(rfoo) |
| 90 | + # foo!(rfoo, sitp) |
| 91 | + # bar!(rbar, sitp) |
| 92 | + # @test rfoo ≈ rbar |
100 | 93 |
|
101 | 94 | end |
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