StackViews.jl

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# StackViews

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[![Coverage](https://codecov.io/gh/JuliaArrays/StackViews.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaArrays/StackViews.jl)

`StackViews` provides only one array type: `StackView`. There are multiple ways to understand `StackView`:

- inverse of `eachslice`
- `cat` variant
- view object
- lazy version of `repeat` special case

## `StackView` as the inverse of `eachslice`

`StackView` can be seen as the inverse of `eachslice`:

```julia
julia> using StackViews

julia> X = rand(100, 100);

julia> StackView(collect(eachslice(X, dims=1)), 1) == X
true
```

## `StackView` as a variant of `cat`

`StackView` works very similar to `cat` and its `vcat`/`hcat`/`hvcat` variants in Base.

```julia
julia> using StackViews

julia> A = reshape(collect(1:6), 2, 3)
2×3 Matrix{Int64}:
 1  3  5
 2  4  6

julia> B = reshape(collect(7:12), 2, 3)
2×3 Matrix{Int64}:
 7   9  11
 8  10  12

julia> StackView(A, B; dims=3) # mostly equivalent to `cat(A, B, dims=3)`
2×3×2 StackView{Int64, 3, 3, ...}:
[:, :, 1] =
 1  3  5
 2  4  6

[:, :, 2] =
 7   9  11
 8  10  12
```

Unlike `cat`s, `StackView` always creats new dimension:

```julia
julia> StackView(A, B; dims=1) # `cat(A, B, dims=1)` outputs 4×3 Matrix
2×2×3 StackView{Int64, 3, 1, ...}:
[:, :, 1] =
 1  2
 7  8

[:, :, 2] =
 3   4
 9  10

[:, :, 3] =
  5   6
 11  12

julia> StackView(A, B; dims=2) # `cat(A, B, dims=2)` outputs 2×6 Matrix
2×2×3 StackView{Int64, 3, 2, ...}:
[:, :, 1] =
 1  7
 2  8

[:, :, 2] =
 3   9
 4  10

[:, :, 3] =
 5  11
 6  12
```

## `StackView` as a view object

Without `StackView`, people use `reshape` + `cat` for the previous examples:

```julia
julia> StackView(A, B, dims=1) == cat(map(x->reshape(x, 1, axes(x)...), (A, B))...; dims=1)
true
```

but `StackView` is only a view and thus don't create any memory:

```julia
frames = [rand(1000, 1000) for _ in 1:100];
@btime StackView($frames, Val(1)); # 143.905 ns (0 allocations: 0 bytes)
@btime cat(map(x->reshape(x, 1, axes(x)...), $frames)...; dims=1); # 1.127 s (1119 allocations: 763.06 MiB)
```

Of course, since it is a view, if you modify it, original arrays get modified, too:

```julia
A = [1, 2, 3, 4]
B = [5, 6, 7, 8]
sv = StackView(A, B)
fill!(sv, -1) # A and B are modified
A == B == fill(-1, 4) # true
```

If indexed in contiguous memeory order, it has almost zero overhead for `getindex` and `setindex!`:

```julia
function arrsum_cart(A::AbstractArray)
    rst = zero(eltype(A))
    @inbounds for I in CartesianIndices(A)
        rst += A[I]
    end
    return rst
end

As = StackView(frames);
Ac = cat(map(x->reshape(x, axes(x)..., 1), frames)...; dims=3);
As == Ac # true

@btime arrsum_cart($As); # 122.703 ms (0 allocations: 0 bytes)
@btime arrsum_cart($Ac); # 123.813 ms (0 allocations: 0 bytes)
```

## `StackView` as a lazy version of `repeat` special case

`StackView` allows you to stack the same array object multiple times, which makes a special
version of `repeat` when there's only one none-1 repeat count:

```julia
A = rand(1000, 1000);
n = 100;
StackView([A for _ in 1:n]) == repeat(A, ntuple(_->1, ndims(A))..., n) # true
@btime StackView([$A for _ in 1:$n]); # 403.156 ns (2 allocations: 1.75 KiB)
@btime repeat($A, ntuple(_->1, ndims($A))..., $n) # 590.043 ms (4 allocations: 762.94 MiB)
```

## More examples

When arrays are of different types and sizes, `StackView` just kills `cat`s:

```julia
julia> using StackViews, PaddedViews

julia> A = collect(reshape(1:8, 2, 4));

julia> B = collect(reshape(9:16, 4, 2));

julia> StackView(paddedviews(-1, A, B), 3)
4×4×2 StackView{Int64, 3, 3, ...}:
[:, :, 1] =
  1   3   5   7
  2   4   6   8
 -1  -1  -1  -1
 -1  -1  -1  -1

[:, :, 2] =
  9  13  -1  -1
 10  14  -1  -1
 11  15  -1  -1
 12  16  -1  -1

julia> StackView(sym_paddedviews(-1, A, B), 3)
4×4×2 StackView{Int64, 3, 3, ...):
[:, :, 1] =
 -1  -1  -1  -1
  1   3   5   7
  2   4   6   8
 -1  -1  -1  -1

[:, :, 2] =
 -1   9  13  -1
 -1  10  14  -1
 -1  11  15  -1
 -1  12  16  -1
```

There is some mind work here but by chaining more views you can get some interesting result:

```julia
using PaddedViews, StackViews
using ImageCore, ImageShow, TestImages, ColorVectorSpace

toucan = testimage("toucan") # 150×162 RGBA image
moon = testimage("moon") # 256×256 Gray image

# equivalently, you can just use `mosaic(toucan, moon; nrow=1)`
mosaicview(StackView(sym_paddedviews(zero(RGB), toucan, moon)); nrow=1)
```

![](https://user-images.githubusercontent.com/1525481/97542758-4b5ade80-1995-11eb-87cc-5fd2b0ba23fc.png)

## Other similar packages

- There's a lot of overlap between this and [LazyStack.jl](https://github.com/mcabbott/LazyStack.jl); I didn't notice its existance when I wrote this.

StackViews.jl

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