Hope to close the both side indices check about tensorcast.jl HOT 2 OPEN

Your first example could be written:

julia> testm2 == @reduce _[_,j] := sum(i) table[i,j,1,1]
true

In the second, are you hoping to get an array of arrays? Perhaps like this:

julia> @reduce test3[k,l][_,j] := sum(i) table[i,j,k,l]
2×2 Matrix{TransmuteDims.TransmutedDimsArray{Float64, 2, (0, 1), (2,), SubArray{Float64, 1, Array{Float64, 3}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64, Int64}, true}}}:
 [0.94672 0.889256]  [0.44493 1.67686]
 [1.11919 1.04312]   [1.1044 0.49902]

julia> test3[1,1] == testm2
true

from tensorcast.jl.

Thanks. You are definitely right. Actually, I use this code just as an example. Since TensorCast also includes summation over indices, we can solve the second problem easily by @reduce. My original question also calls package Trapz to perform numerical integration over the first dimension. Just I want to simplify the process I substitute to sum to express my idea in brief.

from tensorcast.jl.