On 2/3/2011 10:06 AM, Eric Firing wrote:
> On 02/02/2011 10:17 PM, Eric Firing wrote:
>> On 02/02/2011 08:38 PM, Robert Abiad wrote:
>>>
>> [...]
>>> I'll put it in as an enhancement, but I'm still unsure if there is a
>>> bug in
>>> there as well. Is there something I should be doing to clear memory
>>> after the
>>> first figure is closed other than close()? I don't understand why
>>> memory usage
>>> grows each time I replot, but I'm pretty sure it isn't desireable
>>> behavior. As
>>> I mentioned, this effect is worse with plot.
>>>
>>> So is this a bug or improper usage?
>>
>> I'm not quite sure, but I don't think there is a specifically matplotlib
>> memory leak bug at work here. Are you using ipython, and if so, have you
>> turned off the caching? In its default mode, ipython keeps lots of
>> references, thereby keeping memory in use. Also, memory management and
>> reporting can be a bit tricky and misleading.
>>
>> Nevertheless, the attached script may be illustrating the problem. Try
>> running it from the command line as-is (maybe shorten the loop--it
>> doesn't take 100 iterations to show the pattern) and then commenting out
>> the line as indicated in the comment. It seems that if anything is done
>> that adds ever so slightly to memory use while the figure is displayed,
>> then when the figure is closed, its memory is not reused. I'm puzzled.
>
> I wasn't thinking straight--there is no mystery and no memory leak.
> Ignore my example script referred to above. It was saving rows of the z
> array, not single elements as I had intended, so of course memory use
> was growing substantially.
>
> Eric
>
You may not see a memory leak, but I still can't get my memory back without
killing python. I
turned off the ipython caching and even ran without iPython on both Windows and
Ubuntu, but when I
use imshow(), followed by close('all') and another imshow(), I run out of
memory. I can see from
the OS that the memory does not come back after close() and that it grows after
the second imshow().
Any other ideas? Looks like a bug to me otherwise.
-robert
------------------------------------------------------------------------------
The modern datacenter depends on network connectivity to access resources
and provide services. The best practices for maximizing a physical server's
connectivity to a physical network are well understood - see how these
rules translate into the virtual world?
http://p.sf.net/sfu/oracle-sfdevnlfb
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
