cat is not type-inferrable

[sethaxen]

It seems that when using cat, Julia cannot infer the types of the resulting dimensions:

julia> using DimensionalData, Test

julia> foo(x, y) = cat(x, y; dims=Dim{:foo}([:c, :d]));

julia> da = DimArray(randn(3), Dim{:a})
3-element DimArray{Float64,1} with dimensions: Dim{:a}
 1   0.54291
 2  -0.0289045
 3   0.526266

julia> foo(da, da)
3×2 DimArray{Float64,2} with dimensions: 
  Dim{:a},
  Dim{:foo} Categorical{Symbol} Symbol[:c, :d] ForwardOrdered
   :c          :d
  0.54291     0.54291
 -0.0289045  -0.0289045
  0.526266    0.526266

julia> @inferred foo(da, da)
ERROR: return type DimArray{Float64, 2, Tuple{Dim{:a, DimensionalData.Dimensions.LookupArrays.NoLookup{Base.OneTo{Int64}}}, Dim{:foo, DimensionalData.Dimensions.LookupArrays.Categorical{Symbol, Vector{Symbol}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.NoMetadata}}}, Tuple{}, Matrix{Float64}, DimensionalData.NoName, DimensionalData.Dimensions.LookupArrays.NoMetadata} does not match inferred return type DimArray{Float64, 2, _A, Tuple{}, Matrix{Float64}, DimensionalData.NoName, DimensionalData.Dimensions.LookupArrays.NoMetadata} where _A<:Tuple

[rafaqz]

Yeah, it doesnt yet know the order or if the lookup is ordered at all.

You can (fully) specify the Categorical lookup manually and it should be type stable.

[rafaqz]

Yes its fine if you specify Categorical with the order keyword:

using DimensionalData.LookupArrays
bar(x, y) = cat(x, y; dims=Dim{:foo}(Categorical([:c, :d]; order=ForwardOrdered())))

julia> @inferred bar(da, da)
3×2 DimArray{Float64,2} with dimensions: 
  Dim{:a},
  Dim{:foo} Categorical{Symbol} Symbol[:c, :d] ForwardOrdered
   :c         :d
  1.6825     1.6825
  0.216932   0.216932
 -0.66003   -0.66003

[sethaxen]

@rafaqz it seems on v0.25 even specifying the lookup does not cause cat to be type-inferrable:

julia> using DimensionalData, Test

julia> using DimensionalData.LookupArrays

julia> bar(x, y) = cat(x, y; dims=Dim{:foo}(Categorical([:c, :d]; order=ForwardOrdered())))
bar (generic function with 1 method)

julia> da = DimArray(randn(3), Dim{:a})
3-element DimArray{Float64,1} with dimensions: Dim{:a}
 1  -0.214735
 2   0.395572
 3  -0.388922

julia> @inferred bar(da, da)
ERROR: return type DimArray{Float64, 2, Tuple{Dim{:a, NoLookup{Base.OneTo{Int64}}}, Dim{:foo, Categorical{Symbol, Vector{Symbol}, ForwardOrdered, NoMetadata}}}, Tuple{}, Matrix{Float64}, DimensionalData.NoName, NoMetadata} does not match inferred return type Any

[rafaqz]

Making cat type stable when allowing it to still work on runtime-validated incorrect dims is pretty hard.

Maybe we need to separate out method dispatch for this specific case so its not mixed into a method with multiple return types.

A PR would help, I've spent too much time working on cat lately 😅