On 02/02/2011 03:08 PM, Robert Abiad wrote: > On 2/2/2011 3:59 PM, Christoph Gohlke wrote: >> On 2/2/2011 3:33 PM, Robert Abiad wrote: >>> Hello All, >>> >>> I'm very new to python, so bear with me. >>> >>> I'd like to use python to do my image processing, but I'm running into >>> behavior that doesn't make >>> sense to me. I'm using Windows 7 Pro (64-bit) with 4 gigs of memory, >>> python 2.6.6, and the newest >>> versions of ipython, pyfits, matplotlib (1.0.1), numpy (1.5.1), scipy. I'm >>> loading in a fits file >>> that's 26 MB (~16 Mpixels). When I load my image in ImageJ, I can see >>> memory usage go up by 50MB, >>> but when I try displaying the image using imshow(), my memory usage goes up >>> by around 500MB, each >>> time. If I close the figure and replot it, imshow() crashes. I don't know >>> if I'm doing something >>> wrong, or if it's a new or known bug. I tried the same thing on Linux and >>> got the same result. >>> Here's a transcript. >>> >>> Welcome to pylab, a matplotlib-based Python environment. >>> For more information, type 'help(pylab)'. >>> >>> In [1]: import pyfits >>> >>> In [2]: from Tkinter import * >>> >>> In [3]: import tkFileDialog >>> >>> In [4]: image=pyfits.getdata(tkFileDialog.askopenfilename()) >>> >>> In [5]: imshow(image) >>> Out[5]:<matplotlib.image.AxesImage object at 0x03BCA170> >>> >>> In [6]: close() >>> >>> In [7]: imshow(image,origin='lower') >>> Out[7]:<matplotlib.image.AxesImage object at 0x0440E170> >>> >>> In [8]: close() >>> >>> In [9]: imshow(image[100:3600,100:3600],origin='lower') >>> Out[9]:<matplotlib.image.AxesImage object at 0x045D9FB0> >>> >>> In [10]: Exception in Tkinter callback >>> Traceback (most recent call last): >>> File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 1410, in __call__ >>> return self.func(*args) >>> File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 495, in callit >>> func(*args) >>> File >>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py", >>> line 263, in >>> idle_draw >>> self.draw() >>> File >>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py", >>> line 248, in draw >>> FigureCanvasAgg.draw(self) >>> File >>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_agg.py", >>> line 394, in draw >>> self.figure.draw(self.renderer) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line >>> 55, in draw_wrapper >>> draw(artist, renderer, *args, **kwargs) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\figure.py", line >>> 798, in draw >>> func(*args) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line >>> 55, in draw_wrapper >>> draw(artist, renderer, *args, **kwargs) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\axes.py", line >>> 1946, in draw >>> a.draw(renderer) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line >>> 55, in draw_wrapper >>> draw(artist, renderer, *args, **kwargs) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line >>> 354, in draw >>> im = self.make_image(renderer.get_image_magnification()) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line >>> 569, in make_image >>> transformed_viewLim) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line >>> 201, in _get_unsampled_image >>> x = self.to_rgba(self._A, self._alpha) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\cm.py", line 193, >>> in to_rgba >>> x = self.norm(x) >>> File "C:\app\Python2.6\lib\site-packages\matplotlib\colors.py", line >>> 820, in __call__ >>> result = (val-vmin) / (vmax-vmin) >>> File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line >>> 3673, in __div__ >>> return divide(self, other) >>> File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line >>> 1077, in __call__ >>> m |= filled(domain(da, db), True) >>> File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 772, >>> in __call__ >>> return umath.absolute(a) * self.tolerance>= umath.absolute(b) >>> MemoryError >>> >>> >>> Thanks for any help, >>> -robert >>> >> >> >> These are previous discussions on the issue: >> >> <http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg14727.html> >> <http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg19815.html> >> <http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg19614.html> >> >> Christoph >> > > The first 2 discussions lead to suggestions of more memory on a 64-bit > installation, but that > doesn't seem like a great solution. I use other image processing software > (ImageJ and IDL) and > neither has any trouble with my images. As I mentioned ImageJ uses 1/10th > the memory for the same > display, or about 1 byte of memory for 1 byte of image. I think matplotlib > should aim for the same. > I also think it should free up memory when the image is closed, but maybe > I'm not doing the right > thing. Is there something else I should be doing to free up memory? > > Things are even worse with plot. > > I'll file a bug report as Benjamin suggests.
Please file it in the "enhancement" category, not as a "bug". The difficulty that mpl has with images is the result of a design decision long ago; as Christoph notes, mpl works primarily with float64 rgba, which is horribly memory inefficient, but is very general and works fine so long as the image is not too large. uint8 is already used in some circumstances. I don't know how hard it would be to simply switch to uint8 for images, or to make that an option, perhaps for all color specification. It may involve getting into arcana of the extension code and the agg library, which is a daunting prospect for most of us, certainly for me. I agree entirely that a major reduction in memory usage would be good; patches, or a mpl branch to achieve that, are welcome. Eric > > -robert > > ------------------------------------------------------------------------------ > Special Offer-- Download ArcSight Logger for FREE (a $49 USD value)! > Finally, a world-class log management solution at an even better price-free! > Download using promo code Free_Logger_4_Dev2Dev. Offer expires > February 28th, so secure your free ArcSight Logger TODAY! > http://p.sf.net/sfu/arcsight-sfd2d > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ Special Offer-- Download ArcSight Logger for FREE (a $49 USD value)! Finally, a world-class log management solution at an even better price-free! Download using promo code Free_Logger_4_Dev2Dev. Offer expires February 28th, so secure your free ArcSight Logger TODAY! http://p.sf.net/sfu/arcsight-sfd2d _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
