# How do I reinterpret and reshape a multi-dimensional array \`J\` into a two-dimensional array \`j\` such that \`typeof(j) \<: Matrix\` is true in Julia 0.7

**URL:** <https://discourse.julialang.org/t/how-do-i-reinterpret-and-reshape-a-multi-dimensional-array-j-into-a-two-dimensional-array-j-such-that-typeof-j-matrix-is-true-in-julia-0-7/15911>\
**Category:** General Usage\
**Tags:** question\
**Created:** [October 5, 2018, 4:43am UTC](https://discourse.julialang.org/t/how-do-i-reinterpret-and-reshape-a-multi-dimensional-array-j-into-a-two-dimensional-array-j-such-that-typeof-j-matrix-is-true-in-julia-0-7/15911 "2018-10-05T04:43:09Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![zygmuntszpak](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/zygmuntszpak/32/2591_2.png) [@zygmuntszpak](https://discourse.julialang.org/u/zygmuntszpak)\
**Post date:** [October 5, 2018, 4:43am UTC](https://discourse.julialang.org/t/how-do-i-reinterpret-and-reshape-a-multi-dimensional-array-j-into-a-two-dimensional-array-j-such-that-typeof-j-matrix-is-true-in-julia-0-7/15911/1 "2018-10-05T04:43:09Z")

</div>

When upgrading code from version `0.6.4` to `0.7.0` I came across the following issue:

### Julia 0.6.4

```julia
J = rand(4,10,12)
j = reinterpret(Float64,J,(4*10,12))
typeof(j) <: Matrix # Evaluates to true

```

### Julia 0.7.0

```julia
J = rand(4,10,12)
j = reshape(reinterpret(Float64,vec(J)),(4*10,12))
typeof(j) <: Matrix #Evaluates to false

```

#### Why is this a problem?

This became an issue in a portion of my code where I wanted to reshape a Jacobian matrix into a multi-dimensional array. The reshaping facilitated convenient indexing into the elements of the Jacobian matrix whilst I was looping over the data that is required to construct the entries of the matrix.

I am using `LsqFit.jl` and the required Jacobian matrix is defined to be of type `Matrix`, i.e. `jacobian::Matrix{T}` ([LsqFit.jl/src/curve\_fit.jl at v0.6.0 · JuliaNLSolvers/LsqFit.jl · GitHub](https://github.com/JuliaNLSolvers/LsqFit.jl/blob/v0.6.0/src/curve_fit.jl)). I wanted to construct my Jacobian as a multi-dimensional array, and then subsequently reshape it into a matrix (thereby avoiding reallocation/copy).

In the latest versions of Julia, the reshaped and reinterpreted array was no longer a subtype of `Matrix` which broke my code.

Thanks for some great suggestions on the Julia Slack channel I was able to resolve my problem. I will post the solution below.

---

<div class="post-metadata">

**Author:** ![zygmuntszpak](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/zygmuntszpak/32/2591_2.png) [@zygmuntszpak](https://discourse.julialang.org/u/zygmuntszpak)\
**Post date:** [October 5, 2018, 5:04am UTC](https://discourse.julialang.org/t/how-do-i-reinterpret-and-reshape-a-multi-dimensional-array-j-into-a-two-dimensional-array-j-such-that-typeof-j-matrix-is-true-in-julia-0-7/15911/2 "2018-10-05T05:04:03Z")

</div>

`Kristoffer Carlsson` suggested an _unsanctioned_ way of getting around this by using `unsafe_wrap`. As an example he showed:

```julia
julia> a = rand(5,5,5);

julia> unsafe_wrap(Vector{Float64}, pointer(a), (15,))
15-element Array{Float64,1}:
 0.39667876246883926
 0.22245479132465285

```

with the understanding that one would have to ensure that `a` is protected from the garbage collector.  
He also linked to a related discussion on reshaping `StaticArrays`.

[https://github.com/JuliaArrays/StaticArrays.jl/pull/496#issuecomment-421806480](https://github.com/JuliaArrays/StaticArrays.jl/pull/496#issuecomment-421806480)

`Moritz Schauer` suggested a clever alternative and safer approach which he attributed to `Keno Fisher` and dubbed _Keno’s obvious trick_:

Fill the reshaped _view_ of a full matrix of the shape you need, instead of reshaping the full matrix with a view into the shape you need.

This means that I start by declaring a Jacobian matrix, e.g. `J = zeros(4*10,12)` and then create a reshaped view of the Jacobian matrix: `Jv = reshape(reinterpret(Float64,J), 4, 10, 12)`.

I can then conveniently index into `Jv`. Since `Jv` is a view, I can pass `J` into `LsqFit.jl` because it contains the same data as `Jv` and is also a `Matrix`.

---

<div class="post-metadata">

**Author:** ![Per](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/per/32/10387_2.png) [@Per](https://discourse.julialang.org/u/Per)\
**Post date:** [October 5, 2018, 5:08am UTC](https://discourse.julialang.org/t/how-do-i-reinterpret-and-reshape-a-multi-dimensional-array-j-into-a-two-dimensional-array-j-such-that-typeof-j-matrix-is-true-in-julia-0-7/15911/3 "2018-10-05T05:08:06Z")

</div>

Why not use

```julia
j = reshape(J, (4*10,12))
typeof(j) <: Matrix #Evaluates to true

```

There’s no need for `reinterpret` as the elements are going to be `Float64` still.

Note that a `reshape`d array in Julia 0.7 is similar to a view, in that it shares its data with the original array.