On 07/08/2014 11:33 AM, Bartosz wrote: > Hi, > > 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 > matplotlib.interactive(True) > import matplotlib.pyplot as plt > fig, axes = plt.subplots(20,20) > plt.show() > > Profiling shows that 50% of computation time is spent on axis/ticks > creation [1], 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 > [2]) 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')) > plt.show()
Hi, I also have found tick marks to be a real performance drain and am 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. Joel ------------------------------------------------------------------------------ Open source business process management suite built on Java and Eclipse Turn processes into business applications with Bonita BPM Community Edition Quickly connect people, data, and systems into organized workflows Winner of BOSSIE, CODIE, OW2 and Gartner awards http://p.sf.net/sfu/Bonitasoft _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
