Is there a way to "enumerate" `mapslices` other than```i = 0result = mapslices(m

General Usage
, ,
1

Is there a way to “enumerate” mapslices other than

i = 0
result = mapslices(myarray; dims=dims) do x
    i += 1
    myfunction(x, i)
end

?

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2

(I’m the OP) I’m aware of eachslice but unfortunately I’m deliberately avoiding it, because dims in eachslice has the opposite meaning to that in mapslices (e.g. dims=1 <=> dims=2), and I want to follow the mapslices convention for other reasons.

3

Take a look at JuliennedArrays.jl:

julia> using JuliennedArrays

julia> v = rand(3,3,3);

julia> dims = (1, 2);

julia> result = map(enumerate(Slices(v, dims...))) do (i, v)
           sum(v)^i
       end
3-element Vector{Float64}:
  3.1860188187847314
 15.902106695465024
 67.67688399859075
4

This is several times faster - a factor of five for me:

map(enumerate(splitdimsview(v, 3))) do (i, v)
    sum(v)^i
end

That is:

using SplitApplyCombine, JuliennedArrays, BenchmarkTools

v = rand(100,100,100)

f_ja(v) = map(enumerate(Slices(v, 1, 2))) do (i, v)
	sum(v)^i
end

f_sac(v) = map(enumerate(splitdimsview(v, 3))) do (i, v)
	sum(v)^i
end

julia> @benchmark f_ja($v)
BenchmarkTools.Trial: 
  memory estimate:  1.69 KiB
  allocs estimate:  22
  --------------
  minimum time:     1.614 ms (0.00% GC)
  median time:      1.684 ms (0.00% GC)
  mean time:        1.720 ms (0.00% GC)
  maximum time:     6.179 ms (0.00% GC)
  --------------
  samples:          2906
  evals/sample:     1

julia> @benchmark f_sac($v)
BenchmarkTools.Trial: 
  memory estimate:  896 bytes
  allocs estimate:  1
  --------------
  minimum time:     324.384 μs (0.00% GC)
  median time:      367.401 μs (0.00% GC)
  mean time:        371.568 μs (0.00% GC)
  maximum time:     928.039 μs (0.00% GC)
  --------------
  samples:          10000
  evals/sample:     1

But yes, different dims convention compared to mapslices.

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