Generalize the signature of LinearInterpolation and CubicInterpolation

Author: timholy

README.md

@@ -127,7 +127,7 @@ which support multidimensional data as well:
 f(x,y) = log(x+y)
 xs = 1:0.2:5
 ys = 2:0.1:5
-A = [f(x+y) for x in xs, y in ys]
+A = [f(x,y) for x in xs, y in ys]
 
 # linear interpolation
 interp_linear = LinearInterpolation((xs, ys), A)

src/convenience-constructors.jl

@@ -1,10 +1,20 @@
 # convenience copnstructors for linear / cubic spline interpolations
 # 1D version
-LinearInterpolation(range::T, vs; extrapolation_bc = Throw()) where {T <: AbstractRange} = extrapolate(scale(interpolate(vs, BSpline(Linear())), range), extrapolation_bc)
-LinearInterpolation(range::T, vs; extrapolation_bc = Throw()) where {T <: AbstractArray} = extrapolate(interpolate((range, ), vs, Gridded(Linear())), extrapolation_bc)
-CubicSplineInterpolation(range::T, vs; bc = Line(OnGrid()), extrapolation_bc = Throw()) where {T <: AbstractRange} = extrapolate(scale(interpolate(vs, BSpline(Cubic(bc))), range), extrapolation_bc)
+LinearInterpolation(range::AbstractRange, vs::AbstractVector; extrapolation_bc = Throw()) =
+    extrapolate(scale(interpolate(vs, BSpline(Linear())), range), extrapolation_bc)
+LinearInterpolation(range::AbstractVector, vs::AbstractVector; extrapolation_bc = Throw()) =
+    extrapolate(interpolate((range, ), vs, Gridded(Linear())), extrapolation_bc)
+CubicSplineInterpolation(range::AbstractRange, vs::AbstractVector;
+                         bc = Line(OnGrid()), extrapolation_bc = Throw()) =
+    extrapolate(scale(interpolate(vs, BSpline(Cubic(bc))), range), extrapolation_bc)
 
 # multivariate versions
-LinearInterpolation(ranges::NTuple{N,T}, vs; extrapolation_bc = Throw()) where {N,T <: AbstractRange} = extrapolate(scale(interpolate(vs, BSpline(Linear())), ranges...), extrapolation_bc)
-LinearInterpolation(ranges::NTuple{N,T}, vs; extrapolation_bc = Throw()) where {N,T <: AbstractArray} = extrapolate(interpolate(ranges, vs, Gridded(Linear())), extrapolation_bc)
-CubicSplineInterpolation(ranges::NTuple{N,T}, vs; bc = Line(OnGrid()), extrapolation_bc = Throw()) where {N,T <: AbstractRange} = extrapolate(scale(interpolate(vs, BSpline(Cubic(bc))), ranges...), extrapolation_bc)
+LinearInterpolation(ranges::NTuple{N,AbstractRange}, vs::AbstractArray{T,N};
+                    extrapolation_bc = Throw()) where {N,T} =
+    extrapolate(scale(interpolate(vs, BSpline(Linear())), ranges...), extrapolation_bc)
+LinearInterpolation(ranges::NTuple{N,AbstractVector}, vs::AbstractArray{T,N};
+                    extrapolation_bc = Throw()) where {N,T} =
+    extrapolate(interpolate(ranges, vs, Gridded(Linear())), extrapolation_bc)
+CubicSplineInterpolation(ranges::NTuple{N,AbstractRange}, vs::AbstractArray{T,N};
+                         bc = Line(OnGrid()), extrapolation_bc = Throw()) where {N,T} =
+    extrapolate(scale(interpolate(vs, BSpline(Cubic(bc))), ranges...), extrapolation_bc)

test/convenience-constructors.jl

@@ -178,6 +178,17 @@ end
         @test extrap(x_lower, y_lower) ≈ A[1, 1] - ΔA_l
         @test extrap(x_higher, y_higher) ≈ A[end, end] + ΔA_h
     end
+
+    @testset "issue #230" begin # at least, I think this is what issue #230 is really about
+        f(x,y) = log(x+y)
+        xs = 1:5
+        ys = 2:0.1:5
+        A = [f(x,y) for x in xs, y in ys]
+        itp = LinearInterpolation((xs, ys), A)
+        for (i, j) in zip(Iterators.product(xs, ys), eachindex(A))
+            @test itp(i...) ≈ A[j]
+        end
+    end
 end
 
 end