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From: Eric F. <ef...@ha...> - 2012-10-02 20:09:47
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On 2012/10/02 9:21 AM, Michael Aye wrote: >>>>>>> >>>>>> How nice of you to ask! ;) >>>>>> Indeed: I had the case that image arrays inside an ImageGrid where >> shown with some white overhead area around, e.g. for an image of 100 >> pixels on the x-axis, the imshow resulted in an x-axis that went from >> -10 to 110. I was looking for a simple way to suppress that behavior >> and let imshow instead use the exact image extent. I believe that the >> plot command has such a flag, hasn't it? (I.e. to use the exact xdata >> range and not try to beautify the plot? >>>>>> >>>>>> Michael >>>>>> >>>>> >>>>> Is the 'extent' keyword what you're looking for? >>>>> >>>> >>>> No, because it needs detail. I was looking for a boolean switch that >> basically says: Respect the data, not beauty. >>> >>> I don't understand what you mean by 'beauty'. If your image is 100 >>> pixels wide and 50 pixels tall, what is it about extent=[0,100,0,50] >>> that doesn't do what you want? >>> >> As I wrote, that's not what is happening. I get extent=[-10,110,0,50]. >> >> >> Which version of matplotlib are you using? Also, are you on a 32-bit >> machine or a 64-bit machine. This might be related to a bug we have >> seen recently. > > I am using mpl 1.1.0 from EPD 7.3-2 on a 64-bit Mac OSX. > > Thanks for the effort Damon. I should have been starting with an > example script from the beginning. > I believe the problem appears only for subplots in the case of sharex > =sharey = True: Aha! This is a real bug. It may take a bit of work to track it down. Would you enter it, with this test script, as a github issue, please? Thank you. Eric > > from matplotlib.pyplot import show, subplots > from numpy import arange, array > > arr = arange(10000).reshape(100,100) > l = [arr,arr,arr,arr] > narr = array(l) > > fig, axes = subplots(2,2,sharex=True,sharey=True) > > for ax,im in zip(axes.flatten(),narr): > ax.imshow(im) > > show() > > One can see that all the 4 axes show the array with an extent of > [-10,110, 0, 100] here. > > Michael > > >> >> Ben Root >> >> ------------------------------------------------------------------------------ >> Don't let slow site performance ruin your business. Deploy New Relic APM >> Deploy New Relic app performance management and know exactly >> what is happening inside your Ruby, Python, PHP, Java, and .NET app >> Try New Relic at no cost today and get our sweet Data Nerd shirt too! >> http://p.sf.net/sfu/newrelic-dev2dev >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > > > ------------------------------------------------------------------------------ > Don't let slow site performance ruin your business. Deploy New Relic APM > Deploy New Relic app performance management and know exactly > what is happening inside your Ruby, Python, PHP, Java, and .NET app > Try New Relic at no cost today and get our sweet Data Nerd shirt too! > http://p.sf.net/sfu/newrelic-dev2dev > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > |