The problem is that the rendering logic for matplotlib resides in the
backend. I would recommand using the "notebook" backend for matplotlib
which should improve the situation.

Or you can use a plotting library for the notebook such as bqplot.

Sylvain

On Jan 14, 2017 3:38 PM, <[email protected]> wrote:

> It's quite easy to generate generate the graph of a function that depends
> upon a parameter and illustrate how that graph changes when we change the
> parameter using interact. A simple example to interact with the frequency
> of a sine function might be written as follows:
>
> %matplotlib inline
> import matplotlib.pyplot as plt
> import numpy as np
> from ipywidgets import interact, FloatSlider
>
> def myplot(a):
>     xs = np.linspace(-3,3,100)
>     ys = np.sin(a*xs)
>     plt.plot(xs,ys)
> demo = interact(myplot, a=FloatSlider(value=1, min=-3, max=3, step=0.01))
>
> When I do so, though, the axes flicker as I move the slider. I can improve
> the situation a bit by setting the axes ticks and limits but I can't seem
> to get it to go away entirely. I would guess that a better solution would
> be to create one axes instance and fiddle with the lines directly, but I
> haven't got that to work either.
>
> What is the best practice for interacting with these types of graphics
> smoothly?
>
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