About a week ago I sent a message to the users mailing list with tick mark performance problems. I now have a proof of concept patch which (mis-)uses the projection keyword in add_subplot to use a custom Axes class. Import one python file, use "projection='fastticks'" -> boring scatter plots render about 2x as fast and plots with lots of minor ticks render 6x faster.
The code is at https://github.com/jbmohler/mplfastaxes ; the core idea is in fastaxes.py which uses a single Line2D for all tick marks of a given flavor rather than a Line2D for every single tick mark. There are two reasons this isn't a total win: 1) it's not done yet in all tick/grid configurations. 2) it loses flexibility in tick labeling The lost flexibility may matter a great deal to other people. In my use-case, the labeling flexibility simply seems misguided and the performance is much much preferred. Comments welcome about how this could move forward toward being included in MPL. 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
