matplotlib-users Mailing List for matplotlib

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....@fu... <
> mailto:o....@fu... <o....@fu...>>> 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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>

Hi,

I'm using the FigureCanvasGtkAgg as my canvas for graphs, but I notice
that the background colour of the canvas does not match that for the
rest of my application, and neither does the font. Is there a simple
way to get my graphs to respect the user selected GTK theme?

I'm using
Debian Squeeze/Wheezy/Sid
Python: 2.6.5
Matplotlib: SVN r8988
GTK: 2.20.1
PyGTK: 2.17.0

— Jason

given a recarray r, r.dtype.names contains a tuple with the column names.

It should be easy to do what you want using a loop.


briant100 wrote:
> 
> Hey John - currently using matplotlib.mlab import csv2rec functionality in
> a script.
> 
> Is there a tool or way to automate plotting of multiple y series contained
> in a csv data file (data in columns, header is first row, x axis is time,
> several y series) with varying column header names and varying numbers of
> columns depending on the individual data file?
> I particularly want to avoid manually typing individual series names -as
> this information is contained in the header row for each column of data it
> seems inefficient to have to type series names for plotting, only to have
> to retype series names for the next csv file which contains different
> column header names 
> 
> Plotfile came close, but doesnt seem to automatically  label individual
> series by column header 
> eg file formats (varying headers, and numbers of columns):
> 
> file 1
> elapsedtime,AS2data,AS45data,SE34data,VB56data
> 
> file 2
> elapsedtime,AS09data,VB24data
> 

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Hey John - currently using matplotlib.mlab import csv2rec functionality in a
script.

Is there a tool or way to automate plotting of multiple y series contained
in a csv data file (data in columns, header is first row, x axis is time,
several y series) with varying column header names and varying numbers of
columns depending on the individual data file?
I particularly want to avoid manually typing individual series names -as
this information is contained in the header row for each column of data it
seems inefficient to have to type series names for plotting, only to have to
retype series names for the next csv file which contains different column
header names 

Plotfile came close, but doesnt seem to automatically  label individual
series by column header 
eg file formats (varying headers, and numbers of columns):

file 1
elapsedtime,AS2data,AS45data,SE34data,VB56data

file 2
elapsedtime,AS09data,VB24data
  


John Hunter-4 wrote:
> 
> <<support for native plotting of python date and datetime
> objects <<support for loading CSV files (or general space/tab/comma
> delimited
> files) into numpy record arrays, and the type conversions (int, float,
> date, etc...) >><<The function assumes there is a
> header row, and these strings will be munged to give valid python
> attribute names.  It inspects the first checkrows lines after the
> header to try and infer the datatype and set the appropriate
> conversion function.  >>
> Here is an example (svn only)
> 
>   from matplotlib.mlab import csv2rec
>   from pylab import figure, show
> 
>   a = csv2rec('data/msft.csv')
>   fig = figure()
>   ax = fig.add_subplot(111)
>   ax.plot(a.date, a.adj_close, '-')
>   fig.autofmt_xdate()
>   show()
> 
> The autofmt_xdate is optional, but is a new function that does a few
> things you usually want in date plots: turns off tick labels in the
> upper subplots if any, rotates the tick labels on the lowest axes and
> right aligns them, and increases the bottom of the subplots adjust to
> make room for the rotated tick labels.
> 
> Here is what the dtype looks like from the example above.
> 
>   In [3]: !head -3 data/msft.csv
>   Date,Open,High,Low,Close,Volume,Adj. Close*
>   19-Sep-03,29.76,29.97,29.52,29.96,92433800,29.79
>   18-Sep-03,28.49,29.51,28.42,29.50,67268096,29.34
> 
>   In [4]: a = csv2rec('data/msft.csv')
> 
>   In [5]: a.dtype
>   Out[5]: dtype([('date', '|O4'), ('open', '<f8'), ('high', '<f8'),
> ('low', '<f8'), ('close', '<f8'),   ('volume', '<i4'), ('adj_close',
> '<f8')])
> 
>   In [6]: a.date[:2]
>   Out[6]: array([2003-09-19 00:00:00, 2003-09-18 00:00:00], dtype=object)
> 
> I'll probably add a few performance features to the csv2rec function,
> mainly to let you skip columns and supply conversion functions where
> desired because the autodate parser is pretty slow if you want to
> parse date strings, but this is enough to make it useful.  Another
> useful feature will be able to support customizable type dependent
> NULL value conversion (eg convert to numpy.nan for floats,
> '0000-00-00' for dates, etc...)
> 
> Record arrays are your friend; have fun!
> JDH
> 
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