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

General Usage
2

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

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

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.