Remove Requires and branches for unsupported VERSIONs

Project.toml

@@ -1,6 +1,6 @@
 name = "Interpolations"
 uuid = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
-version = "0.16.1"
+version = "0.16.2"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -10,7 +10,6 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Ratios = "c84ed2f1-dad5-54f0-aa8e-dbefe2724439"
-Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SharedArrays = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
@@ -29,9 +28,9 @@ Adapt = "2, 3, 4.0"
 AxisAlgorithms = "0.3, 1"
 ChainRulesCore = "0.10, 1.0, 1.2, 1.3"
 ForwardDiff = "0.10, 1.0"
+JLArrays = "0.2"
 OffsetArrays = "0.10, 0.11, 1.0.1"
 Ratios = "0.3, 0.4"
-Requires = "1.1"
 StaticArrays = "0.12, 1"
 Unitful = "1"
 WoodburyMatrices = "0.4, 0.5, 1.0"
@@ -40,15 +39,11 @@ julia = "1.9"
 [extras]
 ColorVectorSpace = "c3611d14-8923-5661-9e6a-0046d554d3a4"
 DualNumbers = "fa6b7ba4-c1ee-5f82-b5fc-ecf0adba8f74"
+JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
-Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-SharedArrays = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["OffsetArrays", "Unitful", "SharedArrays", "ForwardDiff", "LinearAlgebra", "DualNumbers", "Random", "Pkg", "Test", "Zygote", "ColorVectorSpace"]
+test = ["ColorVectorSpace", "DualNumbers", "JLArrays", "ForwardDiff", "Test", "Unitful", "Zygote"]

ext/InterpolationsUnitfulExt.jl

@@ -1,10 +1,6 @@
 module InterpolationsUnitfulExt
 
-if !isdefined(Base, :get_extension)
-    import ..Unitful, ..Interpolations
-else
-    import Unitful, Interpolations
-end
+import Unitful, Interpolations
 
 Interpolations.tweight(A::AbstractArray{T}) where T <: Unitful.Quantity = Interpolations.tweight(Unitful.ustrip(A))
 

src/Interpolations.jl

@@ -473,18 +473,6 @@ include("lanczos/lanczos_opencv.jl")
 include("iterate.jl")
 include("chainrules/chainrules.jl")
 include("hermite/cubic.jl")
-if VERSION >= v"1.6"
-    include("gpu_support.jl")
-end
-
-if !isdefined(Base, :get_extension)
-using Requires
-end
-
-@static if !isdefined(Base, :get_extension)
-function __init__()
-    @require Unitful="1986cc42-f94f-5a68-af5c-568840ba703d" include("../ext/InterpolationsUnitfulExt.jl")
-end
-end
+include("gpu_support.jl")
 
 end # module

src/b-splines/b-splines.jl

@@ -253,12 +253,8 @@ function interpolate!(A::AbstractArray, it::IT, λ::Real, k::Int) where {IT<:Dim
     interpolate!(tweight(A), A, it, λ, k)
 end
 
-if VERSION >= v"1.7.0-beta1"
-    # https://github.com/JuliaLang/julia/pull/40623
-    lut!(dl, d, du) = lu!(Tridiagonal(dl, d, du), NoPivot())
-else
-    lut!(dl, d, du) = lu!(Tridiagonal(dl, d, du), Val(false))
-end
+# https://github.com/JuliaLang/julia/pull/40623
+lut!(dl, d, du) = lu!(Tridiagonal(dl, d, du), NoPivot())
 
 include("constant.jl")
 include("linear.jl")

test/chainrules.jl

@@ -8,32 +8,20 @@ using Zygote: Zygote
 
     itp = interpolate(y,BSpline(Linear()))
 
-    if VERSION ≥ v"1.3"
-        @test Zygote.gradient(itp, 1) == Tuple(Interpolations.gradient(itp, 1))
-    else
-        @test_skip Zygote.gradient(itp, 1) == Tuple(Interpolations.gradient(itp, 1))
-    end
+    @test Zygote.gradient(itp, 1) == Tuple(Interpolations.gradient(itp, 1))
 
     # 2D example
     x2 = [i*j for i=1:5, j=1:5]
     y2 = sin.(x2)
 
     itp2 = interpolate(y2, BSpline(Cubic(Line(OnGrid()))))
 
-    if VERSION ≥ v"1.3"
-        @test Zygote.gradient(itp2,1,2) == Tuple(Interpolations.gradient(itp2,1,2))
-    else
-        @test_skip Zygote.gradient(itp2,1,2) == Tuple(Interpolations.gradient(itp2,1,2))
-    end
+    @test Zygote.gradient(itp2,1,2) == Tuple(Interpolations.gradient(itp2,1,2))
 
     # Matrix-valued
     y=[[[0 0; 0 0]] [[1 2; 0 0]];
        [[0 0; 3 4]] [[1 2; 3 4]]]
     itp_m = interpolate(y, BSpline(Linear()))
-    if VERSION ≥ v"1.3"
-        @test Zygote.jacobian(itp_m, 1,1) == Tuple((x->[x...]).(Interpolations.gradient(itp_m, 1,1)))
-    else
-        @test_skip Zygote.jacobian(itp_m, 1,1) == Tuple((x->[x...]).(Interpolations.gradient(itp_m, 1,1)))
-    end
+    @test Zygote.jacobian(itp_m, 1,1) == Tuple((x->[x...]).(Interpolations.gradient(itp_m, 1,1)))
 
 end

test/iterate.jl

@@ -44,23 +44,17 @@ macro test_knots(itersym, type, expect...)
         IterEqCheck = :( kiter ≈ kref )
     end
 
-    # Check Type-stability if v > 1.2
-    @static if VERSION >= v"1.2"
-        # Check Type-stability using inferred
-        type_stability_checks = quote
-            @testset "type stability" begin
-                iteratetype = Union{Nothing, knotType}
-                y = @inferred iteratetype iterate($itersym)
-                if y !== nothing
-                    @test_nowarn @inferred iteratetype iterate($itersym, y[2])
-                end
-                isBounded && @test_nowarn @inferred Integer length($itersym)
-                @test_nowarn @inferred Type eltype($itersym)
+    # Check Type-stability using inferred
+    type_stability_checks = quote
+        @testset "type stability" begin
+            iteratetype = Union{Nothing, knotType}
+            y = @inferred iteratetype iterate($itersym)
+            if y !== nothing
+                @test_nowarn @inferred iteratetype iterate($itersym, y[2])
             end
+            isBounded && @test_nowarn @inferred Integer length($itersym)
+            @test_nowarn @inferred Type eltype($itersym)
         end
-    else
-        # Skip Type-stability checks as @inferred AllowedTypes is Undefined
-        type_stability_checks = :()
     end
 
     # Build test_knots tests
@@ -159,28 +153,14 @@ knot_ref(seq, ::Interpolations.BoundaryCondition) = seq
 function knot_ref(seq, ::Periodic)
     Δ = diff(seq)
     iter = Iterators.flatten((first(seq), Iterators.cycle(Δ)))
-    @static if VERSION >= v"1.5"
-        Iterators.accumulate(+, iter)
-    else
-        # Generate 200 samples (2x factor on testing done by @test_knots)
-        # Then wrap with cycle to get IteratorSize === IsInfinite
-        # TODO: Remove when Julia v1 is no longer supported
-        ref = Iterators.take(iter, 200) |> collect |> cumsum |> Iterators.cycle
-    end
+    Iterators.accumulate(+, iter)
 end
 
 function knot_ref(seq, ::Reflect)
     Δ = diff(seq)
     Δ = vcat(Δ, reverse(Δ))
     iter = Iterators.flatten((first(seq), Iterators.cycle(Δ)))
-    @static if VERSION >= v"1.5"
-        Iterators.accumulate(+, iter)
-    else
-        # Generate 200 samples (2x factor on testing done by @test_knots)
-        # Then wrap with cycle to get IteratorSize === IsInfinite
-        # TODO: Remove when Julia v1 is no longer supported
-        ref = Iterators.take(iter, 200) |> collect |> cumsum |> Iterators.cycle
-    end
+    Iterators.accumulate(+, iter)
 end
 
 @testset "knot_ref" begin

test/runtests.jl

@@ -58,9 +58,5 @@ const isci = get(ENV, "CI", "") in ("true", "True")
     # Chain rules interaction
     include("chainrules.jl")
 
-    if VERSION >= v"1.6"
-        import Pkg
-        Pkg.add("JLArrays")
-        include("gpu_support.jl")
-    end
+    include("gpu_support.jl")
 end