Powerful convenience for Julia visualizations and data analysis http://juliaplots.github.io/
[slack] <oxinabox> The constrained optimization problem i am thinking for laying out DAGs (which is both Pert charts and I htink Sankey diagrams)
Every node has an X and a Y coord, that are Integer variables.
Every root node is constrained to have X[i] = 0
for every link from node i to node j
we add the constraint that X[i] < X[j]
so it has to be to the right of its partent,
and we add into the objective being minimized:+ (X[i] - X[j])^2 + (Y[i] - Y[j])^2
which should mean it tries to put things close together.
In particular that should mean that if there is a connection between only 2 nodes then they are places one right of the other.
Then we just need to stop it putting two things in the same place.
Expressing that is harder,
I think what have to do is have a Integery matrix for all possible positions.
And then constrain it so that all elements are <=2
But that means having to reformulate all the earlier constraints in terms of X and Y to be in termsof this matrix somehow, which seems hard.
But this is like a classic scheduling MIP problem of filling slots, and I know i have written those before…
[slack] <eirikeb> I want to draw a contour at some levels, specified using levels=[1.0] or something, and then fill areas withing those levels. I did the following:
```using Plots
A = [ix/2 - (ix -5)^2 + 2*iy for ix=1:10, iy=1:10] # Matrix with an expanding ridge in the middle
Want a plot that fills the positive area
p1 = contour(A,levels=[0.0]) # Perfect, only need to fill it
p2 = contourf(A,levels=[0.0]) # Not what I wanted/expected :(
plot(p1,p2) # How can I fill p1```
What am I missing here? I tried google but couldn't find anything :(
[slack] <daschw> or maybe
A,
levels = [-20, 0, 20],
clims = (-20, 20),
color = cgrad([:white, :red]),
colorbar = false,
)unfortunately we do not support different alpha values for color gradients
[slack] <eirikeb> Well, almost! I want to specify a single level, say 0, and fill the area which is above/below this level with color. Like contour(A,levels=[0,0]) draws the outline just like I want it, but I need to fill it. Contourf(ill?)(A,levels=[0,0]) just draws normal contour lines, but with an added contour-line at the specified levels (I think). I want to specify which level(s) the lines are,
I have attached a picture.
I guess if I set clims(-epsilon,epsilon) that could work too, if I find a color scheme that starts at/ends at the colors I want.: https://files.slack.com/files-pri/T68168MUP-F015Z0R0DUP/download/screenshot_from_2020-07-01_15-50-41.png
b->g and a->f, and a->f in the image in the PR
[slack] <eirikeb> I actually think the plot in the screenshot was generated by GR a year or two ago, if I can remember correctly. I was trying to find the code, that I used to generate it, but the code is lost on a server I don't have access to anymore :(
Anyways, I ended up doing:level = 0.0 #What ever desired level I want
contourf(A,clims=(level-1e-15,level+1e-15))
This works pretty well:: https://files.slack.com/files-pri/T68168MUP-F016LCJTL3E/download/screenshot_from_2020-07-01_21-19-30.png
[slack] <eirikeb> I actually think the plot in the screenshot was generated by GR a year or two ago, if I can remember correctly. I was trying to find the code, that I used to generate it, but the code is lost on a server I don't have access to anymore :(
Anyways, I ended up doing:level = 0.0 #What ever desired level I want
contourf(A,clims=(level-1e-15,level+1e-15))
This works very well, but feels contrived!
Plots.plotarea(p.subplots[1]) would return the actual box where plot gouse
contour_labels = true. The whole thing breaks if I try to use PyPlot. I am using Plots version 1.5.3 and PyPlot 2.9.0using Plots
gr()
n = 500
x1 = range(-1, stop=10, length=n);
x2 = range(-1, stop=10, length=n);
f(x) = (x[1])^2 + (x[2])^2
z = [f([x1[i], x2[j]]) for j = 1:n for i = 1:n];
contour(x1,x2,z,
levels = [4, 8, 12, 16],
xaxis = ("x₁", (0,4), (0:1:10)),
yaxis = ("x₂", (0,4)),
clims = (1,15),
# contour_labels = true,
aspect_ratio = :equal
)This is the error I get when I try PyPlot as the backend:
type Array has no field surfgetproperty(::Array{Float64,1}, ::Symbol) at Base.jl:33
py_add_series(::Plots.Plot{Plots.PyPlotBackend}, ::Plots.Series) at pyplot.jl:629
_before_layout_calcs(::Plots.Plot{Plots.PyPlotBackend}) at pyplot.jl:947
prepare_output(::Plots.Plot{Plots.PyPlotBackend}) at plot.jl:177
showjuno(::IOContext{Base.GenericIOBuffer{Array{UInt8,1}}}, ::MIME{Symbol("image/svg+xml")}, ::Plots.Plot{Plots.PyPlotBackend}) at output.jl:258
show(::IOContext{Base.GenericIOBuffer{Array{UInt8,1}}}, ::MIME{Symbol("image/svg+xml")}, ::Plots.Plot{Plots.PyPlotBackend}) at output.jl:212
show(::IOContext{Base.GenericIOBuffer{Array{UInt8,1}}}, ::String, ::Plots.Plot{Plots.PyPlotBackend}) at multimedia.jl:109
displayinplotpane(::Plots.Plot{Plots.PyPlotBackend}) at showdisplay.jl:67
displayandrender(::Plots.Plot{Plots.PyPlotBackend}) at showdisplay.jl:131
(::Atom.var”#208#213"{String})() at eval.jl:136
#invokelatest#1 at essentials.jl:712 [inlined]
invokelatest at essentials.jl:711 [inlined]
macro expansion at dynamic.jl:24 [inlined]
eval(::String, ::Int64, ::String, ::String, ::Bool) at eval.jl:113
invokelatest(::Any, ::Any, ::Vararg{Any,N} where N; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at essentials.jl:712
invokelatest(::Any, ::Any, ::Vararg{Any,N} where N) at essentials.jl:711
macro expansion at eval.jl:41 [inlined]
(::Atom.var”#188#189")() at task.jl:358
histogram2d(θ,r,proj = :polar, m = 2) , but I get this error InexactError: trunc(Int32, NaN) . I don't get this when using scatter with the same inputs, so I assume it's just not an option?