Julia plotting unknown number of layers in Gadfly - arrays

Question

I'm trying to create a plot in Julia (currently using Gadfly but I'd be willing to use a different package). I have a multidimensional array. For a fixed dimension size (e.g. 4875x3x3 an appropriate plot would be:
p=Gadfly.plot(
layer(y=sim1.value[:,1,1],x=[sim1.range],Geom.line, Theme(default_color=color("red"))),
layer(y=sim1.value[:,1,2],x=[sim1.range],Geom.line, Theme(default_color=color("blue"))),
layer(y=sim1.value[:,1,3],x=[sim1.range],Geom.line, Theme(default_color=color("green")))
)
but in general I want to be able to write a plot statement where I do not know the third dimension of the sim1.value array. How can I write such a statement?
perhaps something like:
p=Gadfly.plot([layer(y=sim1.value[:,1,i],x=[sim1.range], Geom.line, Theme(default_color=color("red"))) for i in 1:size(sim1)[3]])
but this doesn't work.
I was able to solve this problem by reshaping the array into a dataframe and adding a column to indicate what the third dimension is, but I was wondering if there was a way to do this without creating a dataframe.
Data look something like this:
julia> sim1.value
4875x3x3 Array{Float64,3}:
[:, :, 1] =
0.201974 0.881742 0.497407
0.0751914 0.921308 0.732588
-0.109084 1.06304 1.15962
-0.0149133 0.896267 1.22897
0.717094 0.72558 0.456043
0.971697 0.792255 0.40328
0.971697 0.792255 0.227884
-0.600564 1.23815 0.499631
-0.881391 1.07994 0.59905
-0.530923 1.00278 0.447363
⋮
0.866138 0.657875 0.280823
1.00881 0.594015 0.894645
0.470741 0.859117 1.09108
0.919887 0.540488 1.01126
2.22095 0.194968 0.954895
2.5013 0.202698 2.05665
1.94958 0.257192 2.01836
2.24015 0.209885 1.67657
0.76246 0.739945 2.2389
0.673887 0.640661 2.15134
[:, :, 2] =
1.28742 0.760712 1.61112
2.21436 0.229947 1.87528
-1.66456 1.46374 1.94794
-2.4864 1.84093 2.34668
-2.79278 1.61191 2.22896
-1.46289 1.21712 1.96906
-0.580682 1.3222 1.45223
0.17112 1.20572 0.74517
0.734113 0.629927 1.43462
1.29676 0.266065 1.52497
⋮
1.2871 0.595874 0.195617
1.84438 0.383567 1.15537
2.12446 0.520074 0.957211
2.36307 0.222486 0.402168
2.43727 0.19843 0.636037
2.33525 0.302378 0.811371
1.09497 0.605816 0.297978
1.366 0.56246 0.343701
1.366 0.56246 0.219561
1.35889 0.630971 0.281955
[:, :, 3] =
0.649675 0.899028 0.628103
0.718837 0.665043 0.153844
0.914646 0.807048 0.207743
0.612839 0.790611 0.293676
0.759457 0.758115 0.280334
0.77993 0.774677 0.396879
-1.63825 1.38275 0.85772
-1.43517 1.45871 0.835853
-1.15413 1.35757 1.05071
-1.10967 1.37525 0.685986
⋮
1.15299 0.561492 0.680718
1.14853 0.629728 0.294947
1.65147 0.517422 0.22285
1.65147 0.517422 0.517451
1.78835 0.719658 0.745866
2.36554 0.426616 1.49432
0.855502 0.739237 1.24224
-0.175234 0.701025 1.07798
-0.221313 0.939255 1.3463
1.58094 0.368615 1.63817

Answer 1

Apparently "splatting", if that's the correct term, works here. Try:
p=Gadfly.plot([layer(y=sim1.value[:,1,i],x=[sim1.range], Geom.line, Theme(default_color=color("red"))) for i in 1:size(sim1)[3]]...)
For different layer colors, this is just a guess/hack (feel free to edit for correctness).
p=Gadfly.plot([layer(y=sim1.value[:,1,i],x=[sim1.range], Geom.line, Theme(default_color=color(["red" "blue" "green" "cyan" "magenta" "yellow"][i%6+1]))) for i in 1:size(sim1)[3]]...)
Perhaps one of Gadfly's Scale color parameters would help here.
Addendum:
See first comment below for color selection method.