Also, if you're adventurous, try installing valgrind and running:

valgrind --tool=massif python slicer.py

valgrind --tool=memcheck --leak-check=yes --log-file=slicer_leak python 
slicer.py

and send me the output -- (probably off list because they will be large 
files).

Cheers,
Mike

Aaron Botnick wrote:
> Hi all,
> 
> I'm using MPL to plot a 6 panel figure of 2d data using pcolormesh.  I 
> started this script last night, and found it consuming over 3GB of 
> memory when I got in this morning.  After reading through old posts to 
> this list, I came across this suggestion:
> 
> http://sourceforge.net/mailarchive/forum.php?thread_name=47558A63.8050307%40cornell.edu&forum_name=matplotlib-users
>  
> <http://sourceforge.net/mailarchive/forum.php?thread_name=47558A63.8050307%40cornell.edu&forum_name=matplotlib-users>
> 
> ...to use gc.collect(), unfortunately this does not solve my 
> problem...after implementing it, my script is now at nearly 800MB within 
> 15 minutes of running.  I am looping this over several thousand data files.
> 
> I am using MPL - 0.92.2, numpy - 1.0.1, and the Agg backend, and running 
> in non-interactive mode on a Fedora Linux box with Python 2.4.  MPL and 
> numpy were installed from source rather than the distribution.
> 
> Following the suggestion to track down memory-leaks, the 
> cbook.print_cycles(gc.garbage) call returns None at every iteration of 
> the loop.  However, using the comparison of original objects ( 
> gc.get_objects() ) to new objects created after the first loop 
> iteration, there are a lot of new objects present.
> 
> I've included a copy of the script in an attachment (slicer.py).
> 
> Any help would be great, thanks!
> 
> -- Aaron Botnick
> 
> 
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-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

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