Display regression for tuples of arrays

[omus]

While updating the doctests I found that Julia 0.4.6 displays findn and findnz as the following:

julia> I = [1, 4, 3, 5]; J = [4, 7, 18, 9]; V = [1, 2, -5, 3];

julia> S = sparse(I,J,V)
5x18 sparse matrix with 4 Int64 entries:
    [1 ,  4]  =  1
    [4 ,  7]  =  2
    [5 ,  9]  =  3
    [3 , 18]  =  -5

julia> findn(S)
([1,4,5,3],[4,7,9,18])

julia> findnz(S)
([1,4,5,3],[4,7,9,18],[1,2,3,-5])

while Julia 0.5-dev does:

julia> I = [1, 4, 3, 5]; J = [4, 7, 18, 9]; V = [1, 2, -5, 3];

julia> S = sparse(I,J,V)
5×18 sparse matrix with 4 Int64 nonzero entries:
    [1 ,  4]  =  1
    [4 ,  7]  =  2
    [5 ,  9]  =  3
    [3 , 18]  =  -5

julia> findn(S)
(4-element Array{Int64,1}:
 1
 4
 5
 3,4-element Array{Int64,1}:
  4
  7
  9
 18)

julia> findnz(S)
(4-element Array{Int64,1}:
 1
 4
 5
 3,4-element Array{Int64,1}:
  4
  7
  9
 18,4-element Array{Int64,1}:
  1
  2
  3
 -5)

[rfourquet]

Not specific to those functions though (the problem is the display of tuples of arrays).

[omus]

Found another display issue with tuples of arrays. Julia 0.4 also displayed things oddly:

Julia 0.4

julia> a, b = eig([1.0 0.0 0.0; 0.0 3.0 0.0; 0.0 0.0 18.0])
([1.0,3.0,18.0],
3x3 Array{Float64,2}:
 1.0  0.0  0.0
 0.0  1.0  0.0
 0.0  0.0  1.0)

julia> a
3-element Array{Float64,1}:
  1.0
  3.0
 18.0

julia> b
3x3 Array{Float64,2}:
 1.0  0.0  0.0
 0.0  1.0  0.0
 0.0  0.0  1.0

Julia 0.5-dev

julia> a, b = eig([1.0 0.0 0.0; 0.0 3.0 0.0; 0.0 0.0 18.0])
(3-element Array{Float64,1}:
  1.0
  3.0
 18.0,
3×3 Array{Float64,2}:
 1.0  0.0  0.0
 0.0  1.0  0.0
 0.0  0.0  1.0)

[nalimilan]

Tentatively adding to 0.5.0 milestone, as it's one of the regressions introduced by the IOContext changes.