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Michael Abbott
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README.md

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@@ -53,7 +53,7 @@ Besides which, there are several other ways to achieve similar things:
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* For an array of arrays, you can also use [`JuliennedArrays.Align`](https://bramtayl.github.io/JuliennedArrays.jl/latest/#JuliennedArrays.Align). This requires (or enables) you to specify which dimensions of the output belong to the sub-arrays, instead of writing `PermutedDimsArray(stack(...), ...)`.
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* There is also [`RecursiveArrayTools.VectorOfArray`](https://github.com/JuliaDiffEq/RecursiveArrayTools.jl#vectorofarray) which as its name hints only allows a one-dimensional container. Linear indexing retreives a slice, not an element, which is sometimes surprising.
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* And there is [`SplitApplyCombine.combinedimsview'](https://github.com/JuliaData/SplitApplyCombine.jl#combinedimsviewarray), which is very similar to `stack`, but doesn't handle tuples.
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* And there is [`SplitApplyCombine.combinedimsview`](https://github.com/JuliaData/SplitApplyCombine.jl#combinedimsviewarray), which is very similar to `stack`, but doesn't handle tuples.
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* For a tuple of arrays, [`LazyArrays.Hcat`](https://github.com/JuliaArrays/LazyArrays.jl#concatenation) is at present faster to index than `stack`, but doesn't allow arbitrary dimensions.
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* For a generator of arrays, the built-in `reduce(hcat,...)` may work, but it slow compared to `stack`: see [test/speed.jl](test/speed.jl) for some examples.
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