# Nested Vectors/Arrays to multidimensional tensor
**URL:** https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186
**Category:** General Usage
**Created:** [March 19, 2020, 2:23pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186 "2020-03-19T14:23:07Z")
**Posts on this page:** 6
**Page:** 1
### Author:  [@LudiWin](https://discourse.julialang.org/u/LudiWin)
#### Post date: [March 19, 2020, 2:23pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/1 "2020-03-19T14:23:07Z")
I searched far and wide in the Julia forum and stackoverflow but haven’t found a general answer to my question (or I missed the point of the answers):
How can I collect an arbitrary number of nested vectors/arrays into a single multi dimensional tensor?
A minimum working example that generates a similar set of data is the following
`data = [[rand(13,14) for i in 1:12] for j in 1:11]`
`data representation: Vector{Array{Array{Float64,2},1}`
How can I transform this into a single 4 dimensional tensor of the shape `(11, 12, 13, 14)`?
Obviously I could write basically boiler plate code on my own but I was wondering whether there is some function/package that does that for me.
The application is computational statistics where I want to manipulate the data tensors along its dimensions directly thus circumventing onerous for-loops.
Thanks for any help in advance! =)
---
### Author:  [@Tamas\_Papp](https://discourse.julialang.org/u/Tamas_Papp)
#### Post date: [March 19, 2020, 2:59pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/2 "2020-03-19T14:59:54Z")
Try something like
```julia
data = [[rand(13,14) for i in 1:12] for j in 1:11]
A = permutedims(reshape(mapreduce(xs -> vec(reduce(hcat, xs)), hcat, data),
13, 14, 12, :),
(4, 3, 1, 2))
data[1][1] == A[1, 1, :, :] # true
```
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### Author:  [@mcabbott](https://discourse.julialang.org/u/mcabbott)
#### Post date: [March 19, 2020, 3:23pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/3 "2020-03-19T15:23:12Z")
I have some packages which may interest you (one [just announced](https://discourse.julialang.org/t/ann-lazystack-slicemap-starslice/36072) this week):
```julia
julia> data = [[rand(13,14) for i in 1:12] for j in 1:11];
julia> using LazyStack
julia> stack(stack.(data)) |> size # this is a view, copy for Array
(13, 14, 12, 11)
julia> permutedims(stack(stack.(data)), (4,3,1,2)) |> size
(11, 12, 13, 14)
julia> using TensorCast
julia> size(@cast out[a,b,c,d] := data[a][b][c,d])
(11, 12, 13, 14)
```
---
### Author:  [@LudiWin](https://discourse.julialang.org/u/LudiWin)
#### Post date: [March 19, 2020, 4:39pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/4 "2020-03-19T16:39:56Z")
Thank you for your replies.
I will have a look into the answers. =)
---
### Author:  [@LudiWin](https://discourse.julialang.org/u/LudiWin)
#### Post date: [May 26, 2020, 11:27am UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/5 "2020-05-26T11:27:50Z")
Ultimately, I rewrote the methods and worked explicitly with multi-dimensional arrays and `cat(array1, array2)` and from the start instead of nested arrays.
---
### Author:  [@aplavin](https://discourse.julialang.org/u/aplavin)
#### Post date: [May 26, 2020, 3:06pm UTC](https://discourse.julialang.org/t/nested-vectors-arrays-to-multidimensional-tensor/36186/6 "2020-05-26T15:06:19Z")
I find [https://github.com/JuliaData/SplitApplyCombine.jl](https://github.com/JuliaData/SplitApplyCombine.jl) really useful for this kind of problems, and routinely use its functions. There are both copying and non-copying (i.e. `view`) versions.