Thanks, Mike, for responding to my question!
I’ve pulled the latest HEAD from github (1.1.0) and test it withe the latest wx (2.8.12 from few days ago) and added your patch from pull 89. I’m afraid the leak is still the same. I also tried to use “your” version from github, which already has the patch, but it didn’t effect the leak. The problem occures on all PCs I checked, some with winXP and one or two running Win7 OS.
I was somewhat inaccurate in a previous email. I did add a single axes to the original script in the line:
self._price_ax = self.fig.add_subplot(111)
But now replaced it with the line:
self.fig.add_axes([0.075,0.1,0.75,0.85])
from the original script and the problem remains. Basically redrawing a canvas with a single axes and nothing more on it grows the memory by more than 100k per second.
Any ideas on what else can I check? workaround?
I’ll appreciate it if anyone else can try and reproduce it.
Oren
···
Re: [Matplotlib-users] Memory leakage in matplotlib 1.0.1 with wx 2.8.11.0
Michael Droettboom
Thu, 21 Apr 2011 09:58:10 -0700
The repository is now on github, so if you want the very latest, you ``should get it from here:[https://github.com/matplotlib/matplotlib](https://github.com/matplotlib/matplotlib) (We haven't done a terribly good job of advertising that change).
I'm not seeing any leak myself with your script with matplotlib HEAD ``plus this pull request:[https://github.com/matplotlib/matplotlib/pull/89](https://github.com/matplotlib/matplotlib/pull/89) so we may be getting to the bottom of this type of leak. Mike On 04/20/2011 05:18 PM, Oren Gampel wrote:
I have now tested this with version 1.1.0svn from the trunk of the dev ``repository. I believe this version contains Michael Droettboo's patch ``for pyCXX. ( ``[https://sourceforge.net/tracker/index.php?func=detail&aid=3115633&group_id=3180&atid=103180](https://sourceforge.net/tracker/index.php?func=detail&aid=3115633&group_id=3180&atid=103180) ``<[https://sourceforge.net/tracker/index.php?func=detail&aid=3115633&group_id=3180&atid=103180](https://sourceforge.net/tracker/index.php?func=detail&aid=3115633&group_id=3180&atid=103180)> ``) ``Unfortunately the leak is still evident in the small script I've ``attached. Again, please note that this script has no axes, plots, or ``drawn components, only an empty canvas that is being redrawn and ``causes the memory growth.Any ideas how to resolve this or further debug this? Thanks for your help, Oren
On Mon, Apr 11, 2011 at 6:37 PM, Oren Gampel <o...@...3526... ``<mailto:o...@...3526...>> wrote:I'm having a memory leakage using matplotlib 1.0.1 with wx 2.8.11.0, on windows XP. To reproduce, I used the sample from here: [http://matplotlib.sourceforge.net/examples/animation/dynamic_image_wxagg2.html](http://matplotlib.sourceforge.net/examples/animation/dynamic_image_wxagg2.html) and deleted most of the significant lines (see below). I only create a canvas but I don't create any axes, nor plot any data. The only thing I do is draw() on a timer event. This makes my process grow about 6Mbyte per minute. Is this reproduced in other environments? Any ideas on how to resolve this? Thanks, Oren """ Copyright (C) 2003-2005 Jeremy O'Donoghue and others License: This work is licensed under the PSF. A copy should be included with this source code, and is also available at [http://www.python.org/psf/license.html](http://www.python.org/psf/license.html) """ import sys, time, os, gc import matplotlib matplotlib.use('WXAgg') from matplotlib import rcParams import numpy as npy import [matplotlib.cm](http://matplotlib.cm) <[http://matplotlib.cm](http://matplotlib.cm/)> as cm from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg from matplotlib.backends.backend_wx import NavigationToolbar2Wx from matplotlib.figure import Figure from wx import * TIMER_ID = NewId() class PlotFigure(Frame): def __init__(self): Frame.__init__(self, None, -1, "Test embedded wxFigure") self.fig = Figure((1,1), 50, facecolor='.95') self.canvas = FigureCanvasWxAgg(self, -1, self.fig) # Now put all into a sizer sizer = wx.BoxSizer(wx.VERTICAL) # This way of adding to sizer allows resizing sizer.Add(self.canvas, 1, wx.LEFT|wx.TOP|wx.GROW) self.SetSizer(sizer) self.Fit() self._price_ax = self.fig.add_subplot(111) wx.EVT_TIMER(self, TIMER_ID, self.onTimer) self.t = wx.Timer(self, TIMER_ID) self.t.Start(1000) def onTimer(self, evt): self.canvas.draw() if __name__ == '__main__': app = PySimpleApp() frame = PlotFigure() # Initialise the timer - wxPython requires this to be connected to # the receiving event handler t = Timer(frame, TIMER_ID) t.Start(100) frame.Show() app.MainLoop() ------------------------------------------------------------------------------ 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](http://p.sf.net/sfu/vmware-sfdev2dev) _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net [https://lists.sourceforge.net/lists/listinfo/matplotlib-users](https://lists.sourceforge.net/lists/listinfo/matplotlib-users)