Interact + PyPlot: only update when releasing slider

[Andrei Berceanu]

I have some code along the lines of

f = figure()
@manipulate for α=1:0.1:3, β=1:0.1:3, γ=1:0.1:3; withfig(f) do
        y = fun(α,β,γ)
        PyPlot.plot(x, y)
    end
end

where fun is a *very slow* function to evaluate. Is there any way to tell @manipulate to update the resulting plot only after I release the sliders? Otherwise what I get is, I release them to the desised values and then have to wait ages for all the intermediate plots to be drawn.

Tnx!

[John Myles White]

I suspect the only way to do this is to change Interact so that it exposes a minimum time threshold before it registers a state change.

— John

[Andrei Berceanu]

Another option would be to use drop-down boxes with selectable values or custom text boxes instead of sliders, at least as a temporary fix. Anyone knows how I can do that?
By the way, iirc, IPython does have the update-on-release mechanism implemented in their interactive widget functionality.

[Shashi Gowda]

Unfortunately, the @manipulate macro can only rerun the expression at every update of any of its input.

What you need here is Reactive's `sampleon` function:

using Reactive, Interact

f = figure();

α=slider(1:0.1:3)

β=slider(1:0.1:3)

γ=slider(1:0.1:3)

replot = button("Replot") # Commit your changes

map(display, α, β, γ, replot) # optional

sampled_coeffs = sampleon(redo, lift(tuple, α, β, γ))

withfig(f)

@lift plot(apply(fun, sampled_coeffs))

IPython doesn't do update on release, Interact, in fact, uses the same widgets. What it does do is have at most 4 updates at any given time in the processing pipeline (any more updates replace the last update in the queue).

[Shashi Gowda]

John's suggestion is also a good way to do this. You can sample the signals at a specific interval instead of on button clicks:

# At 2 fps, with repeats dropped.

sampled_coeffs = droprepeats(sampleon(fps(2), lift(tuple, α, β, γ)))

[Andrei Berceanu]

Thank you both for the suggestions! I am currently trying the "Replot" button approach, but ran into some errors, as follows:

using Reactive, Interact
using PyPlot

fun(α, β, γ) = cos(α + sin(β+γ)) #example function

f = figure();

α=slider(1:0.1:3)
β=slider(1:0.1:3)
γ=slider(1:0.1:3)
replot = button("Replot") # Commit your changes
map(display, α, β, γ, replot) # optional

-->  `start` has no method matching start(::Slider{Float64})

sampled_coeffs = sampleon(redo, lift(tuple, α, β, γ))

-->  redo not defined

withfig(f)
@lift plot(apply(fun, sampled_coeffs))
--> `withfig` has no method matching withfig(::Figure)

[Shashi Gowda]

using Reactive, Interact

using PyPlot

f = figure();

α=slider(1:0.1:3)

β=slider(1:0.1:3)

γ=slider(1:0.1:3)

replot = button("Replot") # Commit your changes

map(display, [α, β, γ, replot]) # optional

coeffs = sampleon(replot, lift(tuple, α, β, γ))

@manipulate for x = coeffs; withfig(f) do

        plot(fun(x...))

    end

end

Sorry, in my rush to reply, I left behind some typos and bad thinking. Tried this, it works.

[Steven G. Johnson]

On Monday, September 8, 2014 11:15:05 AM UTC-4, Andrei Berceanu wrote:

Another option would be to use drop-down boxes with selectable values or custom text boxes instead of sliders, at least as a temporary fix. Anyone knows how I can do that?

Just wrap dropdown(...) around the range to get a dropdown menu instead of a slider:

@manipulate for n in dropdown(1:5)

    ...

end

By the way, iirc, IPython does have the update-on-release mechanism implemented in their interactive widget functionality.

We are using the same JavaScript widgets as IPython.  Maybe you just need to set some option when the widget is created?