On Wed, Apr 20, 2011 at 9:29 AM, Michael Droettboom <md...@stsci.edu> wrote: > On 04/20/2011 07:48 AM, Caleb Constantine wrote: >> On Tue, Apr 19, 2011 at 2:25 PM, Michael Droettboom<md...@stsci.edu> wrote: >>> Ok. I have a RHEL5 Linux box with Python 2.7.1. >>> >>> With Numpy 1.4.1 and 1.5.1 I don't see any leaks. With Numpy git HEAD, >>> I did see a leak -- I submitted a pull request to Numpy here: >>> >>> https://github.com/numpy/numpy/pull/76 >>> >>> I get the same results (no leaks) running your wx, tk and agg scripts >>> (with the Windows-specific stuff removed). >>> >>> FWIW, I have wxPython 2.8.11.0 and Tkinter rev 81008. >>> >>> So the variables are the platform and the version of Python. Perhaps >>> it's one of those two things? >>> >>> Mike >> Consider the following: >> >> matplotlib 1.0.1, numpy 1.5.1, python 2.7.1, wxPython 2.8.11.0, >> Windows XP SP3 >> >> - 1 hour >> - Plotted 3601 times, about 1Hz >> - Memory usage increased by about 1.16MB (41.39 - 40.23), or >> about 0.33K per redraw >> >> It seems the same memory leak exists. Given you don't have this issue >> on Linux with the same Python configuration, I can only assume it is >> related to some Windows specific code somewhere. I'll run for a longer >> period of time just in case, but I don't expect the results to be >> different. > One way to rule out Windows-specific code may be to run with the Agg > backend only (without wx). Have you plotted the memory growth? This > amount of memory growth is well within the pool allocation sizes that > Python routinely uses. Does the value of len(gc.get_objects()) grow > over time? >
New results follows. matplotlib 1.0.1, numpy 1.5.1, python 2.7.1, wxPython 2.8.11.0, Windows XP SP3 agg - 3601 redraws (1 hour), about 1Hz - Memory usage: 28.79 - 27.57 = 1.22 MB - len(gc.get_objects()): 23424 at beginning and end - Plot of memory growth: roughly linear, increasing with slope of 0.26KB tkagg - 3601 redraws (1 hour), about 1Hz - Memory usage: 33.22 - 33.32 = -0.1 MB - len(gc.get_objects()): 24182 at beginning and end - Plot of memory growth: very irregular (up and down), but a line fit has a slope of about 0.025KB (I could run longer and see if slope approaches 0) wxagg - 3601 redraws (1 hour), about 1Hz - Memory usage: 43.28 - 41.80 = 1.5 MB - len(gc.get_objects()): 41473 at beginning and end - Plot of memory growth: roughly linear, increasing with slope of 0.32KB ------------------------------------------------------------------------------ Benefiting from Server Virtualization: Beyond Initial Workload Consolidation -- Increasing the use of server virtualization is a top priority.Virtualization can reduce costs, simplify management, and improve application availability and disaster protection. Learn more about boosting the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
