improve inference in tensorizer length (#358)

Author: jishnub

src/Multivariate/TensorSpace.jl

@@ -29,7 +29,7 @@ const TrivialTensorizer{d} = Tensorizer{NTuple{d,Ones{Int,1,Tuple{OneToInf{Int}}
 
 eltype(::Type{<:Tensorizer{<:Tuple{Vararg{Any,N}}}}) where {N} = NTuple{N,Int}
 dimensions(a::Tensorizer) = map(sum,a.blocks)
-Base.length(a::Tensorizer) = mapreduce(sum,*,a.blocks)
+Base.length(a::Tensorizer) = reduce(*, dimensions(a)) # easier type-inference than mapreduce
 
 Base.keys(a::Tensorizer) = oneto(length(a))
 

test/runtests.jl

@@ -481,6 +481,7 @@ end
         @testset "2D" begin
             ax = Ones{Int}(∞)
             t = ApproxFunBase.Tensorizer((ax,ax))
+            @test (@inferred length(t)) == length(ax)^2
             v = collect(Iterators.take(t, 150))
             @test eltype(v) == eltype(t)
             @testset for (i, vi) in enumerate(v)
@@ -495,7 +496,7 @@ end
             t = ApproxFunBase.Tensorizer((ax,ax,ax))
             v = collect(Iterators.take(t, 150))
             @test eltype(v) == eltype(t)
-            @testset for i in eachindex(v)
+            @testset for (i,vi) in enumerate(v)
                 blk = ApproxFunBase.block(t, i)
                 @test i ∈ ApproxFunBase.blockrange(t, blk)
             end