Examples of mortar() for nd arrays?

[kescobo]

The docstring for mortar() shows

mortar(blocks::AbstractArray{R, N}, sizes_1, sizes_2, ..., sizes_N)

But I can't figure out how to use this. Here's what I expected to work:

julia> arr = [[rand(2,3,4)] [rand(2,3,4)]
              [rand(2,3,4)] [rand(2,3,4)]];

julia> typeof(arr)
Matrix{Array{Float64, 3}} (alias for Array{Array{Float64, 3}, 2})

julia> mortar(arr, [2,2], [3,3], ones(Int, 4))
ERROR: MethodError: no method matching mortar(::Matrix{Array{Float64, 3}}, ::Vector{Int64}, ::Vector{Int64}, ::Vector{Int64})

I was expecting this to produce the equivalent of

julia> BlockedArray(rand(4,6,4), [2,2], [3,3], ones(Int, 4))
2×2×4-blocked 4×6×4 BlockedArray{Float64, 3}:
# ...

[dlfivefifty]

I suspect the docstring ia out of date or just wrong…

since you have an alternative that works is there any reason to want to use mortar? We should probably just delete that docstring.

[kescobo]

you have an alternative that works

The alternative does not work for my use-case, or at least, I don't think so. This is related to #87, where the idea is that I have some images that need to be tiled together with some overlaps, and I want to mortar() together views of the original images, without needing to allocate a new array.

I'm currently getting around this by making a vector of 2D arrays, one for each layer, but it would be nice to be able to have a 3D blocked array instead. If there's a different way to use the BlockedArray() constructor for a group of existing 3D arrays, I'm happy to learn of it - all of my attempts have seemed to concatenate / copy the original arrays

[kescobo]

I just figured this out! It was a problem of not creating the 3D array in the first step - I didn't realize that part was required (nor, actually, how to do that). Here's an example of what I was trying to do before:

julia> m0 = zeros(10, 10, 2); m1 = ones(10, 10, 2);

julia> m0v = @view m0[1:5,1:5,:]; m1v = @view m1[6:10, 6:10,:];

julia> ba = [[[m0v] [m1v]];;;]
1×2×1 Array{SubArray{Float64, 3, Array{Float64, 3}, Tuple{UnitRange{Int64}, UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, 3}:
[:, :, 1] =
 [0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; … ; 0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0;;; 0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0; … ; 0.0 0.0 … 0.0 0.0; 0.0 0.0 … 0.0 0.0]  …  [1.0 1.0 … 1.0 1.0; 1.0 1.0 … 1.0 1.0; … ; 1.0 1.0 … 1.0 1.0; 1.0 1.0 … 1.0 1.0;;; 1.0 1.0 … 1.0 1.0; 1.0 1.0 … 1.0 1.0; … ; 1.0 1.0 … 1.0 1.0; 1.0 1.0 … 1.0 1.0]

julia> ma = mortar(ba)
1×2×1-blocked 5×10×2 BlockArray{Float64, 3, Array{SubArray{Float64, 3, Array{Float64, 3}, Tuple{UnitRange{Int64}, UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, 3}, Tuple{BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}:
[:, :, 1] =
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0

[:, :, 2] =
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0

julia> m1[:,:,2] .= 2; ma
1×2×1-blocked 5×10×2 BlockArray{Float64, 3, Array{SubArray{Float64, 3, Array{Float64, 3}, Tuple{UnitRange{Int64}, UnitRange{Int64}, Base.Slice{Base.OneTo{Int64}}}, false}, 3}, Tuple{BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}, BlockedOneTo{Int64, Vector{Int64}}}}:
[:, :, 1] =
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0
 0.0  0.0  0.0  0.0  0.0  1.0  1.0  1.0  1.0  1.0

[:, :, 2] =
 0.0  0.0  0.0  0.0  0.0  2.0  2.0  2.0  2.0  2.0
 0.0  0.0  0.0  0.0  0.0  2.0  2.0  2.0  2.0  2.0
 0.0  0.0  0.0  0.0  0.0  2.0  2.0  2.0  2.0  2.0
 0.0  0.0  0.0  0.0  0.0  2.0  2.0  2.0  2.0  2.0
 0.0  0.0  0.0  0.0  0.0  2.0  2.0  2.0  2.0  2.0