Replacing missing values in a matrix is super slow

General Usage
38

But even the first run should not allocate an array of the full size.
Everything is done in-place.

See this, that works but is doing the same!

julia> capnan0!(A,B,v) = B[A .> v] .= NaN
capnan0! (generic function with 2 methods)

julia> A = randn((128, 512, 256));

julia> B = copy(A);

julia> capnan0!(A, B, 100);

julia> @time capnan0!(A, B, 100); A .= B; @time capnan0!(A, B, 100); A .= B; @time capnan0!(A, B, 100); #
  0.018046 seconds (8 allocations: 2.004 MiB)
  0.014085 seconds (8 allocations: 2.004 MiB)
  0.014415 seconds (8 allocations: 2.004 MiB)

There are some aliasing bugs which might occur also here?

EDIT: The mechanism maybe works in the second run since we do no assignments then.

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