Have you tried using "draw_idle"? That will schedule the draw for the
next time the event loop is idle.
Mike
On 06/24/2013 07:39 AM, Thomas Robitaille wrote:
> Hi everyone,
>
> The following shows an example of a simple data viewer which includes
> a slider, a bitmap, and a scatter plot:
>
> """
> import numpy as np
> from matplotlib import pyplot as plt
> from matplotlib.widgets import Slider
>
> fig = plt.figure()
>
> ax1 = fig.add_axes([0.1, 0.1, 0.4, 0.7])
> image = ax1.imshow(np.random.random((512, 512)), vmin=0., vmax=1.)
>
> ax2 = fig.add_axes([0.1, 0.9, 0.85, 0.05])
> ax2.set_xticklabels("")
> ax2.set_yticklabels("")
> slider = Slider(ax2, "", 0., 1.)
>
> def update_vmax(value):
> image.set_clim(0., value)
> fig.canvas.draw()
>
> slider.on_changed(update_vmax)
>
> ax3 = fig.add_axes([0.55, 0.1, 0.4, 0.7])
> x = np.random.random(10000)
> y = np.random.random(10000)
> ax3.scatter(x, y)
>
> plt.show()
> """
>
> When moving the slider, the vmax of the image changes, but I get very
> slow frame rates (~2/sec) on my computer with the MacOS X backend. I
> was wondering whether people here have any tips on speeding things up?
>
> As far as I can figure out, this is slow because both the slider and
> the callback function call ``fig.canvas.draw``. Slider calls it before
> the callback function, so I definitely need to draw things in that
> function, but I can get a factor of 2x speedup by doing
>
> slider.drawon = False
>
> which prevents ``canvas.draw()`` being called twice. However, this is
> still much too slow, so I started to look into using ``draw_artist``
> to only update elements that need updating, but this requires
> partially re-implementing the Slider class.
>
> As a side note, using ``draw_artist`` also does not work on the MacOS X
> backend:
>
> https://github.com/matplotlib/matplotlib/issues/166
>
> but I'm willing to have a solution that wouldn't work on this backend
> if it was the only way.
>
> Does anyone have a clean solution to increasing the frame rate of this
> example?
>
> Thanks!
> Tom
>
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