Fix gradient for NoInterp

src/b-splines/indexing.jl

@@ -174,6 +174,9 @@ function expand(coefs::AbstractArray{T,N}, vweights::Tuple{}, ixs::Tuple{}, iexp
     @inbounds coefs[iexpanded...]  # @inbounds is safe because we checked in the original call
 end
 
+const HasNoInterp{N} = NTuple{N,Tuple{Vararg{<:Union{Number,NoInterp}}}}
+expand(coefs::AbstractArray, vweights::HasNoInterp, ixs::Indexes, iexpanded::Vararg{Integer,M}) where {M} = NoInterp()
+
 # _expand1 handles the expansion of a single dimension weight list (of length L)
 @inline _expand1(coefs, w1, ix1, wrest, ixrest, iexpanded) =
     w1[1] * expand(coefs, wrest, ixrest, iexpanded..., ix1[1]) +
@@ -182,14 +185,17 @@ end
     w1[1] * expand(coefs, wrest, ixrest, iexpanded..., ix1[1])
 
 # Expansion of the gradient
-function expand(coefs, (vweights, gweights)::Tuple{Weights{N},Weights{N}}, ixs::Indexes{N}) where N
+function expand(coefs, (vweights, gweights)::Tuple{HasNoInterp{N},HasNoInterp{N}}, ixs::Indexes{N}) where N
     # We swap in one gradient dimension per call to expand
-    SVector(ntuple(d->expand(coefs, substitute(vweights, d, gweights), ixs), Val(N)))
+    SVector(skip_nointerp(ntuple(d->expand(coefs, substitute(vweights, d, gweights), ixs), Val(N))...))
 end
-function expand!(dest, coefs, (vweights, gweights)::Tuple{Weights{N},Weights{N}}, ixs::Indexes{N}) where N
+function expand!(dest, coefs, (vweights, gweights)::Tuple{HasNoInterp{N},HasNoInterp{N}}, ixs::Indexes{N}) where N
     # We swap in one gradient dimension per call to expand
+    i = 0
     for d = 1:N
-        dest[d] = expand(coefs, substitute(vweights, d, gweights), ixs)
+        w = substitute(vweights, d, gweights)
+        w isa Weights || continue   # must have a NoInterp in it
+        dest[i+=1] = expand(coefs, w, ixs)
     end
     dest
 end

src/nointerp/nointerp.jl

@@ -17,7 +17,7 @@ base_rem(::NoInterp, bounds, x::Number) = Int(x), 0
 expand_index(::NoInterp, xi::Number, ax::AbstractUnitRange, δx) = (xi,)
 
 value_weights(::NoInterp, δx) = (oneunit(δx),)
-gradient_weights(::NoInterp, δx) = (zero(δx),)
-hessian_weights(::NoInterp, δx) = (zero(δx),)
+gradient_weights(::NoInterp, δx) = (NoInterp(),)
+hessian_weights(::NoInterp, δx) = (NoInterp(),)
 
 padded_axis(ax::AbstractUnitRange, ::NoInterp) = ax

src/utils.jl

@@ -20,3 +20,7 @@ end
 function substitute(default::NTuple{N,Any}, d::Integer, val) where N
     ntuple(i->ifelse(i==d, val, default[i]), Val(N))
 end
+
+@inline skip_nointerp(x, rest...) = (x, skip_nointerp(rest...)...)
+@inline skip_nointerp(::NoInterp, rest...) = skip_nointerp(rest...)
+skip_nointerp() = ()

test/gradient.jl

@@ -106,6 +106,7 @@ using Test, Interpolations, DualNumbers, LinearAlgebra
     @test g[2] ≈ 2 * (4 - 1.75) ^ 2 * (3 - 1.75)
 
     A2 = rand(Float64, nx, nx) * 100
+    gni = [1.0]
     for BC in (Flat,Line,Free,Periodic,Reflect,Natural), GT in (OnGrid, OnCell)
         itp_a = interpolate(A2, (BSpline(Linear()), BSpline(Quadratic(BC()))), GT())
         itp_b = interpolate(A2, (BSpline(Quadratic(BC())), BSpline(Linear())), GT())
@@ -127,11 +128,17 @@ using Test, Interpolations, DualNumbers, LinearAlgebra
             @test epsilon(itp_b(x,yd)) ≈ gtmp[2]
             ix, iy = round(Int, x), round(Int, y)
             gtmp = Interpolations.gradient(itp_c, ix, y)
-            @test_broken length(gtmp) == 1
-            @test_broken epsilon(itp_c(ix,yd)) ≈ gtmp[1]
+            @test length(gtmp) == 1
+            @test epsilon(itp_c(ix,yd)) ≈ gtmp[1]
+            gni[1] = NaN
+            Interpolations.gradient!(gni, itp_c, ix, y)
+            @test gni[1] ≈ gtmp[1]
             gtmp = Interpolations.gradient(itp_d, x, iy)
-            @test_broken length(gtmp) == 1
+            @test length(gtmp) == 1
             @test epsilon(itp_d(xd,iy)) ≈ gtmp[1]
+            gni[1] = NaN
+            Interpolations.gradient!(gni, itp_d, x, iy)
+            @test gni[1] ≈ gtmp[1]
         end
     end