Type stable scale function. Closes #111 (#112)

* Type stable scale function. Closes #111

Also adds methods for eltype and ndims to AbstractInterpolation

* Add `@inferred` to scaling tests

Author: sglyon

src/Interpolations.jl

@@ -34,7 +34,7 @@ export
 
 using WoodburyMatrices, Ratios, AxisAlgorithms
 
-import Base: convert, size, getindex, gradient, scale, promote_rule
+import Base: convert, size, getindex, gradient, scale, promote_rule, ndims, eltype
 
 abstract Flag
 abstract InterpolationType <: Flag
@@ -76,6 +76,12 @@ itptype(itp::AbstractInterpolation ) = itptype(typeof(itp))
 gridtype{T,N,IT<:DimSpec{InterpolationType},GT<:DimSpec{GridType}}(::Type{AbstractInterpolation{T,N,IT,GT}}) = GT
 gridtype{ITP<:AbstractInterpolation}(::Type{ITP}) = gridtype(super(ITP))
 gridtype(itp::AbstractInterpolation) = gridtype(typeof(itp))
+ndims{T,N,IT<:DimSpec{InterpolationType},GT<:DimSpec{GridType}}(::Type{AbstractInterpolation{T,N,IT,GT}}) = N
+ndims{ITP<:AbstractInterpolation}(::Type{ITP}) = ndims(super(ITP))
+ndims(itp::AbstractInterpolation) = ndims(typeof(itp))
+eltype{T,N,IT<:DimSpec{InterpolationType},GT<:DimSpec{GridType}}(::Type{AbstractInterpolation{T,N,IT,GT}}) = T
+eltype{ITP<:AbstractInterpolation}(::Type{ITP}) = eltype(super(ITP))
+eltype(itp::AbstractInterpolation) = eltype(typeof(itp))
 count_interp_dims{T<:AbstractInterpolation}(::Type{T}, N) = N
 
 include("nointerp/nointerp.jl")

src/scaling/scaling.jl

@@ -6,10 +6,16 @@ immutable ScaledInterpolation{T,N,ITPT,IT,GT,RT} <: AbstractInterpolationWrapper
     itp::ITPT
     ranges::RT
 end
-ScaledInterpolation{T,ITPT,IT,GT,RT}(::Type{T}, N, itp::ITPT, ::Type{IT}, ::Type{GT}, ranges::RT) =
-    ScaledInterpolation{T,N,ITPT,IT,GT,RT}(itp, ranges)
+@generated function ScaledInterpolation{ITPT,RT}(itp::ITPT, ranges::RT)
+    T = eltype(itp)
+    N = ndims(itp)
+    IT = itptype(itp)
+    GT = gridtype(itp)
+    :(ScaledInterpolation{$T,$N,$ITPT,$IT,$GT,$RT}(itp, ranges))
+end
+
 """
-`scale(itp, xs, ys, ...)` scales an existing interpolation object to allow for indexing using other coordinate axes than unit ranges, by wrapping the interpolation object and transforming the indices from the provided axes onto unit ranges upon indexing.
+`scale(itp, xs, ys, ...)` scales an existing interpolation object to allow for indexing using other coordinate axes than unit ranges, by wrapping the interpolation object and transforming the indices from the provided axes onto unit ranges upon indexing.a
 
 The parameters `xs` etc must be either ranges or linspaces, and there must be one coordinate range/linspace for each dimension of the interpolation object.
 
@@ -25,7 +31,7 @@ function scale{T,N,IT,GT}(itp::AbstractInterpolation{T,N,IT,GT}, ranges::Range..
         end
     end
 
-    ScaledInterpolation(T,N,itp,IT,GT,ranges)
+    ScaledInterpolation(itp, ranges)
 end
 
 @generated function getindex{T,N,ITPT,IT<:DimSpec}(sitp::ScaledInterpolation{T,N,ITPT,IT}, xs::Number...)

test/scaling/scaling.jl

@@ -8,7 +8,7 @@ using Base.Test
 
 itp = interpolate(1:1.0:10, BSpline(Linear()), OnGrid())
 
-sitp = scale(itp, -3:.5:1.5)
+sitp = @inferred(scale(itp, -3:.5:1.5))
 
 for (x,y) in zip(-3:.05:1.5, 1:.1:10)
     @test_approx_eq sitp[x] y
@@ -24,7 +24,7 @@ ys = -4:.2:4
 zs = Float64[testfunction(x,y) for x in xs, y in ys]
 
 itp2 = interpolate(zs, BSpline(Quadratic(Flat())), OnGrid())
-sitp2 = scale(itp2, xs, ys)
+sitp2 = @inferred scale(itp2, xs, ys)
 
 for x in xs, y in ys
     @test_approx_eq testfunction(x,y) sitp2[x,y]
@@ -34,7 +34,7 @@ end
 xs = -pi:.1:pi
 ys = sin(xs)
 itp = interpolate(ys, BSpline(Linear()), OnGrid())
-sitp = scale(itp, xs)
+sitp = @inferred scale(itp, xs)
 
 for x in -pi:.1:pi
     g = @inferred(gradient(sitp, x))[1]
@@ -46,13 +46,13 @@ end
 @inferred(getindex(sitp2, -3, 1))
 @inferred(getindex(sitp2, -3.4, 1))
 
-sitp32 = 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)
+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)
 @test typeof(@inferred(getindex(sitp32, -3.4f0, 1.2f0))) == Float32
 
 # Iteration
 itp = interpolate(rand(3,3,3), BSpline(Quadratic(Flat())), OnCell())
 knots = map(d->1:100:201, 1:3)
-sitp = scale(itp, knots...)
+sitp = @inferred scale(itp, knots...)
 function foo!(dest, sitp)
     i = 0
     for s in eachvalue(sitp)