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Interactive Plots and Diagrams





In [1]:



    


using Reactive, Interact

Interactive plotting can be useful and fun. Here we have a few examples to get you started creating your own interactive plots. We will extensively use the @manipulate macro from the introductory notebook.

Compose

Compose is an excellent tool for creating declarative vector graphics. Here is an example compose diagram you can play around with.





In [2]:



    


using Color
using Compose

@manipulate for color=["yellow", "cyan", "tomato"], rotate=0:.05:2π, n=3:20
    compose(context(), fill(color),
    polygon([((1+sin(θ+rotate))/2, (1+cos(θ+rotate))/2) for θ in 0:2π/n:2π]))
end



    


















    
















    
















    
















    
Out[2]:

Gadfly





In [3]:



    


using Gadfly



    











In [4]:



    


@manipulate for ϕ = 0:π/16:4π, f = [:sin => sin, :cos => cos], both = false
    if both
        plot([θ -> sin(θ + ϕ), θ -> cos(θ + ϕ)], 0, 8)
    else
        plot(θ -> f(θ + ϕ), 0, 8)
    end
end



    


















    
















    
















    
















    
Out[4]:









  
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    f(x)
  



  





















In [5]:



    


@manipulate for n=1:25, g = [Geom.line, Geom.point]
    Gadfly.plot(y=rand(n), x=rand(n), g)
end



    


















    
















    
















    
Out[5]:









  
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    y

PyPlot





In [6]:



    


using PyPlot



    


















    






INFO: Loading help data...
Warning: using PyPlot.plot in module Main conflicts with an existing identifier.
Warning: using PyPlot.text in module Main conflicts with an existing identifier.

Since PyPlot API has functions with side effects, you want to create a figure first and use it in each iteration of @manipulate with withfig. Notice f = figure() and withfig(f) in the example below. The rest of it is straightforward.





In [7]:



    


f = figure()
x = linspace(0,2π,1000)
@manipulate for α=1:0.1:3, β=1:0.1:3, γ=1:0.1:3, leg="a funny plot"; withfig(f) do
        PyPlot.plot(x, cos(α*x + sin(β*x + γ)))
        legend([leg])
    end
end



    


















    
















    
















    
















    
















    
Out[7]:

As an added bonus, you can even fire up a Python GUI with pygui(true) and be able to use the widgets above to update the plot.

Content source: FavioVazquez/Interact.jl

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