[matplotlib-devel] question about imshow's support for masked arrays
I am experimenting with numpy masked arrays, and have a question about how imshow handles them: from numpy import ma from pylab import colorbar, imshow, show a=ma.array([[1,2,3],[4,5,6]],mask=[[0,0,1],[0,0,0]], fill_value=0) imshow(a, interpolation='nearest') colorbar() show() With svn matplotlib, the missing value is treated as if identical to the maximum value. I thought imshow would instead respect the masked array's fill_value property by calling fix_invalid, and perhaps defaulting to the min() or max() if fill_value is the default 99. What is the intended behavior? Relatedly, it looks like imshow and other functions like contour are badly confused by NaNs, I thought they were supported? Thanks, Darren -- ___ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
Re: [matplotlib-devel] question about imshow's support for masked arrays
Darren Dale wrote: > I am experimenting with numpy masked arrays, and have a question about > how imshow handles them: > > from numpy import ma > from pylab import colorbar, imshow, show > > a=ma.array([[1,2,3],[4,5,6]],mask=[[0,0,1],[0,0,0]], fill_value=0) > imshow(a, interpolation='nearest') > colorbar() > show() > > With svn matplotlib, the missing value is treated as if identical to the > maximum value. I thought imshow would instead respect the masked array's I don't see this with my installation from svn. > fill_value property by calling fix_invalid, and perhaps defaulting to > the min() or max() if fill_value is the default 99. What is the > intended behavior? What I see with your example is a white square for the masked value; actually, it is transparent, with alpha = 0. This is the intended default; if it is masked, don't paint anything. It is set in Colormap.__init__ and can be overridden by Colormap.set_bad(). There is no intention to use the masked array fill value. > > Relatedly, it looks like imshow and other functions like contour are > badly confused by NaNs, I thought they were supported? I suspect we really should run the Z inputs through masked_invalid, especially for contour. The performance hit is minimal as a fraction of the total time. I will do this for contour. imshow has to be handled more carefully, so I don't want to do it in a hurry. One of the general cleanups needed in mpl is clarity and consistency in argument validation. Part of this is a matter of clarity about API levels; we don't want to have to do full validation and acceptance of all possible input variations at every level. Eric > > Thanks, > Darren -- ___ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
Re: [matplotlib-devel] question about imshow's support for masked arrays
On Wed, Mar 25, 2009 at 3:02 PM, Eric Firing wrote: > Darren Dale wrote: > >> I am experimenting with numpy masked arrays, and have a question about how >> imshow handles them: >> >> from numpy import ma >> from pylab import colorbar, imshow, show >> >> a=ma.array([[1,2,3],[4,5,6]],mask=[[0,0,1],[0,0,0]], fill_value=0) >> imshow(a, interpolation='nearest') >> colorbar() >> show() >> >> With svn matplotlib, the missing value is treated as if identical to the >> maximum value. I thought imshow would instead respect the masked array's >> > I don't see this with my installation from svn. > >> fill_value property by calling fix_invalid, and perhaps defaulting to the >> min() or max() if fill_value is the default 99. What is the intended >> behavior? >> > > What I see with your example is a white square for the masked value; > actually, it is transparent, with alpha = 0. This is the intended default; > if it is masked, don't paint anything. It is set in Colormap.__init__ and > can be overridden by Colormap.set_bad(). > I was using a greyscale colormap that painted the max value white, and I confused no paint with max value. Personally, I think black would have been a better default, but no matter. Thank you for the clarification. > > There is no intention to use the masked array fill value. > > >> Relatedly, it looks like imshow and other functions like contour are badly >> confused by NaNs, I thought they were supported? >> > > I suspect we really should run the Z inputs through masked_invalid, > especially for contour. The performance hit is minimal as a fraction of the > total time. I will do this for contour. imshow has to be handled more > carefully, so I don't want to do it in a hurry. > Ok. Darren -- ___ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
[matplotlib-devel] AxesGrid toolkit 0.1a
Hi list, I packaged some of python modules that I have been using as a mpl toolkit. They are mostly helper classes to display images more conveniently. Note that I put some of them in the matplotlib as examples. http://dl.getdropbox.com/u/178748/AxesGrid/htdocs/index.html It consists of pure python modules, so the installation should be straight forward. But I guess you need the svn version of mpl. > python setup.py install While the code is currently poorly documented, and may not be suitable for normal users, I'm releasing it in a hope that some others find this useful. I tried to wrote a short summary of modules included. Although it is far from complete (and written in poor english), I hope this gives you some idea what you can do with this toolkit. http://dl.getdropbox.com/u/178748/AxesGrid/htdocs/users/overview.html Regards, -JJ -- ___ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
