Re: [Matplotlib-users] a possible bug report

[Eric F. <ef...@ha...>]

On 2014/06/12, 6:07 AM, M.Rule wrote:
> Hi all,
>
> I haven't been able to find a more official place to report potential
> Matplotlib bugs, so I'm going to describe the issue I'm seeing here.
> Sorry if this is the wrong forum.

This is *exactly* the right place to make a report like this.  It is 
better to start with a message to a wide audience (at least, we hope it 
is a wide audience) such as this list, or maybe stack overflow, to see 
if someone else recognizes the problem.  In many cases, it is not a 
matplotlib bug.  If the response to an email like this does not lead to 
a solution, and the consensus is that it looks like you have hit a real 
bug, *then* file an issue on github.

>
> On my system, it takes matplotlib a very very long time to close plots.
> Sometimes, up to 20 minutes to close a simple figure. Creating new
> figures remains fast. The problem seems to occur only when I've loaded a
> large amount of data in to python ( on the order of 1GB ). I am using
> the current version of Ubuntu and running "ipython --pylab". To
> reproduce on my system, it is sufficient to load a large amount of data,
> create a plot.. any plot, and then try to close it using the little "x"
> at the top right corner of the window. The whole session will freeze for
> an extended period of time. The plot does not have to be complex: a
> hundred datapoints, a thousand, it makes no difference. Since the
> problem only occurs when a large amount of data has been loaded, my
> guess is that there is a problem with how Matplotlib/Pylab/Python is
> trying to free the memory associated with the figure?

This sounds like the problem that prompted another user to propose 
https://github.com/matplotlib/matplotlib/pull/3045, except that your 
case sounds *much* more severe.

Can you reproduce the data loading and plot generation in a script that 
does not have to be run via ipython? And if so, is it still slow?

Is the large amount of data in the form of a very large number of python 
objects?  Is there something odd about the data structure--extreme 
complexity that would make garbage collection take an absurd amount of time?

Since this does sound like the problem addressed by the pull request 
("PR") noted above, please add your report (and any answers to my 
questions) as a comment on that PR.

Eric
>
> So... I just though I'd put this out there in case anyone else sees the
> same issue, or in case a developer who knows why this might be happening
> reads this. The workaround for me is... to simply wait for the figures
> to close, however long that may take, or restart the whole session.
>
> Best,
> michael.
>
>
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