问题描述
我正在尝试在 Julia 中创建一个情节(目前使用的是 Gadfly，但我愿意使用不同的包).我有一个多维数组.对于固定尺寸大小(例如 4875x3x3，适当的绘图将是:
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")))
)
但总的来说，我希望能够在不知道 sim1.value 数组的第三维的情况下编写绘图语句.我怎么能写出这样的声明?
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?
可能是这样的:
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]])
但这不起作用.
我能够通过将数组重塑为数据框并添加一列来指示第三维是什么来解决这个问题，但我想知道是否有一种方法可以在不创建数据框的情况下做到这一点.
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.
数据看起来像这样:
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
推荐答案
显然splatting"，如果这是正确的术语，在这里工作.试试:
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]]...)
对于不同的图层颜色，这只是猜测/破解(请随意编辑以确保正确性).
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]]...)
也许 Gadfly 的 Scale 颜色参数之一在这里会有所帮助.
Perhaps one of Gadfly's Scale color parameters would help here.
附录:
颜色选择方法见下文第一条评论.
See first comment below for color selection method.
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