I am using "pmap -pid" on Linux and Task manager on Windows. Memory usage is
comparable on both operating systems so I think the memory consumption
information is accurate.
> ------------ Pôvodná správa ------------
> Od: Michael Droettboom <md...@stsci.edu>
> Predmet: Re: [Matplotlib-users] imshow memory problem
> Dátum: 18.5.2010 16:18:23
> ----------------------------------------
> What are you using to calculate memory usage? I feel the only truly
> reliable tool is something instrumented like "valgrind --tool=massif".
>
> ============================================================================
> BUILDING MATPLOTLIB
> matplotlib: 1.0.svn
> python: 2.5.2 (r252:60911, May 7 2008, 12:40:32) [GCC
> 3.4.6 20060404 (Red Hat 3.4.6-9)]
> platform: linux2
>
> REQUIRED DEPENDENCIES
> numpy: 2.0.0.dev8055
> freetype2: 9.16.3
>
> OPTIONAL BACKEND DEPENDENCIES
> libpng: 1.2.37
> Tkinter: Tkinter: 50704, Tk: 8.4, Tcl: 8.4
> wxPython: 2.8.6.1
> * WxAgg extension not required for wxPython >= 2.8
> Gtk+: gtk+: 2.10.9, glib: 2.16.1, pygtk: 2.10.4,
> pygobject: 2.13.1
> Mac OS X native: no
> Qt: Qt: 3.3.3, PyQt: 3.17.2
> Qt4: Qt: 4.6.2, PyQt4: 4.7.3
> Cairo: 1.4.0
>
> OPTIONAL DATE/TIMEZONE DEPENDENCIES
> datetime: present, version unknown
> dateutil: 1.4.1
> pytz: 2008c
>
> OPTIONAL USETEX DEPENDENCIES
> dvipng: 1.12
> ghostscript: 7.07
> latex: 3.1415926
> pdftops: 3.00
>
> verbose-helpful:
>
> $HOME=/home/mdroe
> CONFIGDIR=/home/mdroe/.matplotlib
> matplotlib data path
> /home/mdroe/usr/lib/python2.5/site-packages/matplotlib/mpl-data
> loaded rc file /home/mdroe/.matplotlib/matplotlibrc
> matplotlib version 1.0.svn
> verbose.level helpful
> interactive is False
> units is False
> platform is linux2
> Using fontManager instance from /home/mdroe/.matplotlib/fontList.cache
> backend GTKAgg version 2.10.4
> findfont: Matching
> :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=medium
>
> to Bitstream Vera Sans
> (/home/mdroe/usr/lib/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/Vera.ttf)
>
> with score of 0.000000
>
>
> Tomáš Faragó wrote:
> > Thanks for replying Mike,
> > I tried it on Linux as well but I ran into the same problem. Perhaps
> > it has something to do with other needed libraries (GTK+, etc.). Can
> > you please tell me your libraries versions? I mean GTK+, pygtk, etc.
> > Also output produced by --verbose-helpful could be useful. Thank you.
> > Tomas.
> >
> >
> >> ------------ Pôvodná správa ------------
> >> Od: Michael Droettboom <md...@stsci.edu>
> >> Predmet: Re: [Matplotlib-users] imshow memory problem
> >> Dátum: 17.5.2010 16:48:55
> >> ----------------------------------------
> >> On Linux, I only see about an extra 24kb being used when the canvas
> >> is added to a window vs. not adding it (i.e. commenting out the
> >> window.add(canvas) line).
> >>
> >> In general, here's the memory usage to be expected from imshow (if
> >> it's a floating-point, not-rgb(a) array as you have here):
> >>
> >> The original data: 4-bytes-per-pixel for float32 or 8-bytes-per-pixel
> >> for float64 (in your example the array is float64).
> >> Intermediate float data: *if* the original is not float64, then an
> >> intermediate float64 is created (not the case here)
> >> The colorized data: 4-bytes-per-pixel at original array size
> >> The sized data: 4-bytes-per-pixel at the scaled figure size
> >>
> >> I hope I'm not forgetting anything, but the point is that to support
> >> high-speed rendering of plots, the memory usage is much greater than
> >> the data itself. If your data is truly large, the usual technique is
> >> to decimate or downsample it before passing it to matplotlib, as
> >> you're not going to see more data points than pixels on your display
> >> anyway.
> >>
> >> Mike
> >>
> >> Tomáš Faragó wrote:
> >> > Hello,
> >> > I am writing a GUI using GTK+ library. I have a question about axes
> >> class
> >> imshow method memory consumtion. If I pass the imshow an array, the
> >> resulting
> >> memory consuption is approximatelly 46 times greater than the array
> >> size. If I
> >> do not add the canvas to a window (in a code below), the memory
> >> consuption is
> >> "only" 8 times greater. Any tips on how to reduce the memory
> >> consuption would be
> >> very appreciated and any explanation of how much memmory imshow
> >> allocates too.
> >> Configuration and script are below.
> >> >
> >> > os: Windowx XP
> >> > matplotlib version: 0.99.1
> >> > downloaded from: sourceforge.net
> >> >
> >> > script:
> >> > from matplotlib.figure import Figure
> >> > from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg
> >> > from pylab import rand
> >> > import gtk
> >> >
> >> > window = gtk.Window()
> >> > window.connect("destroy", gtk.main_quit)
> >> >
> >> > figure = Figure(figsize=(8,6), dpi=72)
> >> > canvas = FigureCanvasGTKAgg(figure)
> >> > axes = figure.add_subplot(111)
> >> >
> >> > window.add(canvas)
> >> >
> >> > axes.imshow(rand(1024,1024))
> >> > canvas.draw()
> >> > window.show_all()
> >> >
> >> > gtk.main()
> >> >
> >> > verbose-helpful output:
> >> > $HOME=C:\Documents and Settings\Sensej
> >> > CONFIGDIR=C:\Documents and Settings\Sensej\.matplotlib
> >> > matplotlib data path C:\Python26\lib\site-packages\matplotlib\mpl-data
> >> > loaded rc file
> >> C:\Python26\lib\site-packages\matplotlib\mpl-data\matplotlibrc
> >> > matplotlib version 0.99.1
> >> > verbose.level helpful
> >> > interactive is False
> >> > units is False
> >> > platform is win32
> >> > Using fontManager instance from C:\Documents and
> >> Settings\Sensej\.matplotlib\fontList.cache
> >> > backend GTKAgg version 2.12.1
> >> > findfont: Matching
> >>
> :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=medium
>
> >>
> >> to Bitstream Vera Sans
> >> (C:\Python26\lib\site-packages\matplotlib\mpl-data\fonts\ttf\Vera.ttf)
> >> with
> >> score of 0.000000
> >> >
> >> > Thank you,
> >> > Tomas.
> >> >
> >> >
> >>
> ------------------------------------------------------------------------------
>
> >>
> >> >
> >> > _______________________________________________
> >> > Matplotlib-users mailing list
> >> > Matplotlib-users@lists.sourceforge.net
> >> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >> >
> >> --
> >> Michael Droettboom
> >> Science Software Branch
> >> Operations and Engineering Division
> >> Space Telescope Science Institute
> >> Operated by AURA for NASA
> >>
> >>
> >>
> >>
>
> --
> Michael Droettboom
> Science Software Branch
> Operations and Engineering Division
> Space Telescope Science Institute
> Operated by AURA for NASA
>
>
>
>
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