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‎src/rewrite.jl

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struct MyInterp{T,N,A<:AbstractArray{T,N}}
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data::A
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end
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@inline (itp::MyInterp{T,N})(i::Vararg{<:Number,N}) where {T,N} = expand(itp, i)
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@inline function expand(itp::MyInterp, ipre::Tuple{Vararg{Number,L}}, ipost::Vararg{Integer,M}) where {L,M} # force specialization
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ifront, ilast = Base.front(ipre), ipre[end]
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im, ip = floor(ilast), ceil(ilast)
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return (ip - ilast)*expand(itp, ifront, unsafe_trunc(Int, im), ipost...) +
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(ilast - im)*expand(itp, ifront, unsafe_trunc(Int, ip), ipost...)
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end
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@inline expand(itp::MyInterp, ::Tuple{}, ipost::Vararg{Integer,N}) where N =
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@inbounds itp.data[CartesianIndex(ipost)]

‎test/InterpolationTestUtils.jl

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module InterpolationTestUtils
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using Test, Interpolations
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using Interpolations: degree, itpflag, bounds, lbounds, ubounds
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using Interpolations: substitute
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export check_axes, check_inbounds_values, check_oob, can_eval_near_boundaries
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export MyPair
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const failstore = Ref{Any}(nothing) # stash the inputs to failing tests here
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## Property accessors
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coefs(itp) = itp.coefs
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boundaryconditions(itp::AbstractInterpolation) = boundaryconditions(itpflag(itp))
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boundaryconditions(bs::BSpline) = degree(bs)
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boundaryconditions(ni::NoInterp) = ni
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ndaccessor(x, d) = x
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ndaccessor(x::Tuple, d) = x[d]
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haspadding(itp) = haspadding(boundaryconditions(itp))
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haspadding(::Union{Constant,Linear,NoInterp}) = false
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haspadding(::Quadratic{BC}) where BC = haspadding(BC())
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haspadding(::Cubic{BC}) where BC = haspadding(BC())
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haspadding(::BC) where BC<:Interpolations.BoundaryCondition = !(BC <: Union{Periodic,InPlace,InPlaceQ})
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haspadding(bcs::Tuple) = map(haspadding, bcs)
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haspadding(::NoInterp) = false
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getindexib(itp, i...) = @inbounds itp[i...]
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callib(itp, i...) = @inbounds itp(i...)
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⊂(r1::AbstractRange, r2::AbstractRange) = first(r2) < first(r1) < last(r2) && first(r2) < last(r1) < last(r2)
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function check_axes(itp, A, isinplace=false)
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@test ndims(itp) == ndims(A)
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axsi, axsA = @inferred(axes(itp)), axes(A)
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szi, szA = @inferred(size(itp)), size(A)
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haspad = haspadding(itp)
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for d = 1:ndims(A)
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if isinplace && ndaccessor(haspad, d)
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@test axsi[d] != axsA[d] && axsi[d] ⊂ axsA[d]
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@test szi[d] < szA[d]
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else
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@test axsi[d] == axsA[d]
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@test szi[d] == szA[d]
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end
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end
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nothing
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end
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function check_inbounds_values(itp, A)
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for i in eachindex(itp)
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@test A[i] ≈ itp[i] == itp[Tuple(i)...] ≈ itp(i) ≈ itp(float.(Tuple(i))...)
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end
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if ndims(itp) == 1
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for i in eachindex(itp)
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@test itp[i,1] ≈ A[i] # used in the AbstractArray display infrastructure
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@test_throws BoundsError itp[i,2]
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@test getindexib(itp, i, 2) ≈ A[i]
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@test callib(itp, i, 2) ≈ A[i]
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end
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end
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nothing
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end
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function check_oob(itp)
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widen(r) = first(r)-1:last(r)+1
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indsi = axes(itp)
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indsci = CartesianIndices(indsi)
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for i in CartesianIndices(widen.(indsi))
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i ∈ indsci && continue
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@test_throws BoundsError itp[i]
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end
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nothing
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end
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function can_eval_near_boundaries(itp::AbstractInterpolation{T,1}) where T
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l, u = bounds(itp, 1)
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@test isfinite(itp(l+0.1))
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@test isfinite(itp(u-0.1))
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@test_throws BoundsError itp(l-0.1)
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@test_throws BoundsError itp(u+0.1)
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end
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function can_eval_near_boundaries(itp::AbstractInterpolation)
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l, u = lbounds(itp), ubounds(itp)
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for d = 1:ndims(itp)
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nearl = substitute(l, d, l[d]+0.1)
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# @show summary(itp) nearl
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@test isfinite(itp(nearl...))
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outl = substitute(l, d, l[d]-0.1)
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@test_throws BoundsError itp(outl...)
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nearu = substitute(u, d, u[d]-0.1)
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# @show nearu
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@test isfinite(itp(nearu...))
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outu = substitute(u, d, u[d]+0.1)
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@test_throws BoundsError itp(outu...)
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end
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end
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# Used for multi-valued tests
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import Base: +, -, *, /, ≈
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struct MyPair{T}
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first::T
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second::T
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end
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# Here's the interface your type must define
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(+)(p1::MyPair, p2::MyPair) = MyPair(p1.first+p2.first, p1.second+p2.second)
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(-)(p1::MyPair, p2::MyPair) = MyPair(p1.first-p2.first, p1.second-p2.second)
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(*)(n::Number, p::MyPair) = MyPair(n*p.first, n*p.second)
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(*)(p::MyPair, n::Number) = n*p
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(/)(p::MyPair, n::Number) = MyPair(p.first/n, p.second/n)
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Base.zero(::Type{MyPair{T}}) where {T} = MyPair(zero(T),zero(T))
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Base.promote_rule(::Type{MyPair{T1}}, ::Type{T2}) where {T1,T2<:Number} = MyPair{promote_type(T1,T2)}
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≈(p1::MyPair, p2::MyPair) = (p1.first ≈ p2.first) & (p1.second ≈ p2.second)
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end

‎test/b-splines/constant.jl

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module ConstantTests
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using Interpolations
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using Test
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# Instantiation
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N1 = 10
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A1 = rand(Float64, N1) * 100
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A2 = rand(Float64, N1, N1) * 100
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A3 = rand(Float64, N1, N1, N1) * 100
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getindexib(itp, i...) = @inbounds itp[i...]
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callib(itp, i...) = @inbounds itp(i...)
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for (constructor, copier) in ((interpolate, x->x), (interpolate!, copy))
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itp1c = @inferred(constructor(copier(A1), BSpline(Constant()), OnCell()))
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itp1g = @inferred(constructor(copier(A1), BSpline(Constant()), OnGrid()))
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itp2c = @inferred(constructor(copier(A2), BSpline(Constant()), OnCell()))
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itp2g = @inferred(constructor(copier(A2), BSpline(Constant()), OnGrid()))
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itp3c = @inferred(constructor(copier(A3), BSpline(Constant()), OnCell()))
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itp3g = @inferred(constructor(copier(A3), BSpline(Constant()), OnGrid()))
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@test parent(itp1c) === itp1c.coefs
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@testset "Constant" begin
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# Instantiation
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N1 = 10
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A1 = rand(Float64, N1) * 100
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A2 = rand(Float64, N1, N1) * 100
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A3 = rand(Float64, N1, N1, N1) * 100
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for (constructor, copier) in ((interpolate, x->x), (interpolate!, copy))
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isinplace = constructor == interpolate!
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itp1c = @inferred(constructor(copier(A1), BSpline(Constant()), OnCell()))
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itp1g = @inferred(constructor(copier(A1), BSpline(Constant()), OnGrid()))
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itp2c = @inferred(constructor(copier(A2), BSpline(Constant()), OnCell()))
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itp2g = @inferred(constructor(copier(A2), BSpline(Constant()), OnGrid()))
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itp3c = @inferred(constructor(copier(A3), BSpline(Constant()), OnCell()))
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itp3g = @inferred(constructor(copier(A3), BSpline(Constant()), OnGrid()))
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@test parent(itp1c) === itp1c.coefs
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@test Interpolations.lbounds(itp1c) == (0.5,)
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@test Interpolations.lbounds(itp1g) == (1,)
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@test Interpolations.ubounds(itp1c) == (N1 + 0.5,)
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@test Interpolations.ubounds(itp1g) == (N1,)
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# Evaluation on provided data points
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for (itp, A) in ((itp1c, A1), (itp1g, A1), (itp2c, A2), (itp2g, A2), (itp3c, A3), (itp3g, A3))
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check_axes(itp, A, isinplace)
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check_inbounds_values(itp, A)
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check_oob(itp)
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can_eval_near_boundaries(itp)
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end
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# Evaluation on provided data points
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for (itp, A) in ((itp1c, A1), (itp1g, A1), (itp2c, A2), (itp2g, A2), (itp3c, A3), (itp3g, A3))
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for i in eachindex(itp)
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@test A[i] == itp[i] == itp[Tuple(i)...] == itp(i) == itp(float.(Tuple(i))...)
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# Evaluation between data points (tests constancy)
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for i in 2:N1-1
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@test A1[i] == itp1c(i+.3) == itp1g(i+.3) == itp1c(i-.3) == itp1g(i-.3)
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end
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@test @inferred(axes(itp)) == axes(A)
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@test @inferred(size(itp)) == size(A)
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# @test @inferred(axes(itp)) == (contructor == interpolate ? (1:N1) : (2:N1-1))
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# @test @inferred(size(itp)) == (contructor == interpolate ? N1 : N1-2)
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end
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for itp in (itp1c, itp1g)
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for i = 1:N1
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@test itp[i,1] == A1[i] # used in the AbstractArray display infrastructure
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@test_throws BoundsError itp[i,2]
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@test_broken getindexib(itp, i, 2) == A1[i]
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@test_broken callib(itp, i, 2) == A1[i]
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# 2D
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for i in 2:N1-1, j in 2:N1-1
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@test A2[i,j] == itp2c(i+.4,j-.3) == itp2g(i+.4,j-.3)
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end
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# 3D
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for i in 2:N1-1, j in 2:N1-1, k in 2:N1-1
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@test A3[i,j,k] == itp3c(i+.4,j-.3,k+.1) == itp3g(i+.4,j-.3,k+.2)
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end
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end
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# Evaluation between data points (tests constancy)
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for i in 2:N1-1
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@test A1[i] == itp1c(i+.3) == itp1g(i+.3) == itp1c(i-.3) == itp1g(i-.3)
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end
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# 2D
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for i in 2:N1-1, j in 2:N1-1
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@test A2[i,j] == itp2c(i+.4,j-.3) == itp2g(i+.4,j-.3)
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end
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# 3D
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for i in 2:N1-1, j in 2:N1-1, k in 2:N1-1
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@test A3[i,j,k] == itp3c(i+.4,j-.3,k+.1) == itp3g(i+.4,j-.3,k+.2)
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# Edge behavior
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@test A1[1] == itp1c(.7)
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@test A1[N1] == itp1c(N1+.3)
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end
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# Edge behavior
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@test A1[1] == itp1c(.7)
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@test A1[N1] == itp1c(N1+.3)
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end
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end

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