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

(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

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> ) 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...@futuretech.co.il <mailto:o...@futuretech.co.il>> 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
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

"""
import sys, time, os, gc

import matplotlib
matplotlib.use('WXAgg')

from matplotlib import rcParams
import numpy as npy

import 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()



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