This is very interesting. I have also noticed that ticking has been a
bottleneck in rendering, but always suspected the computation of the ticks
rather than the actual rendering of the marks. Perhaps this might spur some
renewed interest in identifying the specific reason for the bottleneck and
solving that issue now that we know that there are significant performance
gain potential here?
Looking forward to reviewing this at some point in the next few weeks.
Cheers!
Ben Root
On Thu, Jun 26, 2014 at 2:10 PM, Joel B. Mohler <j...@kiwistrawberry.us>
wrote:
> 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
>
>
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