Re: [Matplotlib-users] PNG performance tips

On Mon, 2008-03-03 at 08:16 -0500, Michael Droettboom wrote:
> > I have an application which produces PNG files using the AGG backend.
> > When I profile the application I can see that much of the cpu time is
> > spent in the method write_png called by print_figure in backend_agg.py.
> 
> I have seen this myself.  Keep in mind that timing includes a lot of 
> disk I/O, so if your images are particularly large, or you're saving to 
> a network or external disk, or if another process steps in at that 
> moment and wants to read/write to the disk, that could be the 
> bottleneck, more so than just the CPU time spent doing the PNG 
> compression.  On any reasonably modern PC, I suspect that's the case.
> 
> > Does anyone know which backend is the best for producing fast good
> > quality PNG files (with fast being as important as good quality)?
> 
> They should all be approximately the same wrt actually writing out the 
> file -- they're all using libpng either directly or indirectly.  It also 
> means there's not much that matplotlib can do to improve its 
> performance, short of submitting patches to libpng -- but I suspect 
> there isn't a lot of long-hanging fruit left to improve in such a 
> widely-used library.

My application is web based. I am therefore considering serving the png files
directly from memory in a future release as outlined here:

http://www.scipy.org/Cookbook/Matplotlib/Matplotlib_and_Zope

Although I am still considering what impacts that will have on my caching of
the plots. I am currently saving the png files and reusing them if the same
plot is requested again - but I am considering pickling individual elements of
the plots instead since there are a lot of plots in which the only differences
is some text (I am already caching parts of the plot in memory). But I don't
know the performance of such a solution yet. I will give you a heads up when I
know (which won't be in the immediate future since I have other things that
are higher up on my to do list).

> > In another thread I read that antialiasing could be disabled for better
> > performance. I tried doing that in each call to contourf and it resulted
> > in a performance improvement. Does anyone have other performance tips
> > with regard to PNG files?
> 
> Saving to a Python file-like object (if you're doing that) is slower 
> than saving directly to a file path.
> 
> See the recent thread on "Matplotlib performance" for a discussion of 
> decimation of data (if your data set is really large).

I am writing directly to a file path and I have already decimated my data
sets - so that won't help me.

Cheers,
Jesper