On 07/08/2014 11:33 AM, Bartosz wrote:Hi, I also have found tick marks to be a real performance drain and am
> When improving the performance of plotting high-dimensional data using
> faceted scatter plots, I noticed that much of time was spent on the axis
> creation (even 50%!).
> On my machine creating 20x20 array of subplots without actually plotting
> anything takes about 11 seconds (for comparison plotting 5000 points on
> all of them takes only 0.6s!):
> import matplotlib
> import matplotlib.pyplot as plt
> fig, axes = plt.subplots(20,20)
> Profiling shows that 50% of computation time is spent on axis/ticks
> creation , which I have to remove anyways. Is there any easy way of
> creating thinned axes without ticks and spines?
> So far I solved the problem by subclassing Axes class (see this gist
> ) and removing all spines and ticks. Running the above example gives
> a 10x boost in performance (from 11s to 0.9s).
> import thin_axes
> fig, axes = plt.subplots(20,20, subplot_kw=dict(projection='thin'))
trying to fix this. I have yet to get my ideas all in a shape which is
worthy of a pull request. It's a rather large change under the hood and
so there are probably quite a few edge cases which I'm not really aware
of since I'm sure I only care about 50% (or less) of the full range of
flexibility. That said, simple graphs with basic tick marks are much
slower than they need to be.
My work is at https://github.com/jbmohler/mplfastaxes and I also used
the custom projection method to replace the Axes/Axis classes. I have
incorporated your example because I think it is interesting (even
through 20x20 grid of axes seems crazy to me ... it may make sense
though :) ).
You have addressed a somewhat different case than myself because I've
focused on the speed of drawing the graphics where-as your gist
illustrates that making a new figure with many axes is very slow. I
believe the same ideas apply and I'm going to spend some time right now
improving my code's initialization which is basically unchanged from MPL
at this point.
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