On Tue, Dec 14, 2010 at 4:22 PM, Benjamin Root <ben.r...@ou.edu> wrote:
>
>
> On Tue, Dec 14, 2010 at 4:06 PM, Russell Owen <ro...@uw.edu> wrote:
>
>> On Dec 14, 2010, at 1:50 PM, Benjamin Root wrote:
>>
>> On Tue, Dec 14, 2010 at 3:18 PM, Russell E. Owen <ro...@uw.edu> wrote:
>>
>>> I tried the test script on linux using matplotlib svn trunk rev8840
>>> (which appears to include your patch) and found a leak that starts out
>>> small but gets systematically larger. This is with Python 2.6.5 and
>>> Tkinter built against Tcl/Tk 8.4.13.
>>>
>>> Is anyone else seeing this?
>>>
>>> time rss memory mem/sec
>>> (sec) (kb) (kb/sec)
>>> 0.0 36816 nan
>>> 5.0 36860 nan
>>> 10.0 36860 0.0
>>> 15.1 36860 0.0
>>> 20.1 36860 0.0
>>> 25.1 36896 1.8
>>> ...
>>> 326.5 36896 0.1
>>> 331.6 36972 0.3
>>> ...
>>> 401.9 36972 0.3
>>> 406.9 36980 0.3
>>> ...
>>>
>>> 602.8 37684 1.4
>>> 607.8 37700 1.4
>>>
>>> This is different behavior than on Mac OS X, but still alarming.
>>>
>>> -- Russell
>>>
>>>
>> Russell,
>>
>> I am curious, I recently ran into problems with mixing builds of numpy and
>> matplotlib at various levels of revisions. I eventually had to do a
>> complete clean rebuild. Note, what I mean by a complete clean rebuild is
>> that I removed the numpy and matplotlib source directories and re-checkout
>> the codes from source and then rebuild. I would be curious if the problem
>> persists after that.
>>
>>
>> An interesting question. I can say that this was a clean build of
>> matplotlib since I ran it "in place" (in build/lib.linux-x86_64-2.6/) after
>> building it rather than installing it in site-packages to avoid messing up
>> other users (on the linux system this was a shared python). I modified the
>> script to print matplotlib.__file__ to make sure I was running the right
>> version. I doubt it was a clean build of numpy. But considering no numerics
>> are occurring in this example (it is literally just creating an Axes on a
>> Canvas and calling canvas.draw() repeatedly) do you think numpy could
>> possibly come into this?
>>
>>
> It is quite possible. Numpy is used extensively throughout the matplotlib
> system, regardless of whether you are using it or not. Also, the fact that
> you are on a shared system is interesting. For those situations, try doing
>
> "python setupegg.py develop --user"
>
> for the build command. What this does is builds everything in-place (the
> build directory symbolically links to those files), and then uses your
> ~/.local directory to install an egg.lnk file to point back to the build
> directory. This should have higher search precedence than the system
> install of matplotlib and numpy.
>
> Note, I had mixed success with this approach on a RHEL (5?) system
> recently. I don't know how recently ~/.local became widely accepted among
> various distros.
>
>
>> Might you run the script on your system with the clean build?
>>
>> -- Russell
>>
>>
> I will give it a shot (once my other analysis programs are done for the
> day).
>
> Ben Root
>
I ran your script from the url you posted earlier. My build does not show
any leak for about a minute. I am fairly certain that what we have here is
a build mixing issue or an issue with an unknown combination of libraries
interacting. Could you post your build logs?
Ben Root
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