Logical indexing per-dim

[IanButterworth]

Is your feature request related to a problem? Please describe.
Related to JuliaGPU/CuArrays.jl#290, it would be great to be able to logically index per-dim, i.e. without having to allocate the full index

Describe the solution you'd like

x[:, x[1, :] .> 3]

Describe alternatives you've considered
This approach works but allocates the index

reshape(x[repeat(view(x, 1, :) .> 3, size(x,1))], size(x,1), :)

If there was such a thing as a repeatview, this could be efficient. i.e. a view version of repeat

[IanButterworth]

I made a suggestion issue in base for repeatview: JuliaLang/julia#34029

[IanButterworth]

I tried an approach suggested in the issue above, but it's suboptimal in performance

using LazyArrays, FillArrays
function filterByRow(x::CuArray, row::Int; thresh=0.0)
    nrows, ncols = size(x)
    col_idxs = 1:ncols                               #idx of every col
    row_copy = Fill(true, 1, nrows)                  #trues of length nrows
    rep_idx_2D = LazyArray(@~ col_idxs .* row_copy)' #lazy copy of col_idxs to every row
    keep_cols = view(x, row, :) .> thresh            #cols to keep
    bool_idx = view(keep_cols,rep_idx_2D)            #logical index on elements to keep
    return reshape(x[bool_idx], nrows, :)            #keep and reshape
end

[simeonschaub]

Describe the solution you'd like

x[:, x[1, :] .> 3]

Maybe, I am misunderstanding something here, but that already works for regular arrays, right? I was actually surprised this kind of mixed logical indexing doesn't work with CuArrays, so I ended up having to move my array to the cpu for this. How hard would it be to add support for this?