You're exactly right. That does fix it. Unfortunately, it means I have to 
refactor some of my code because the Pyside slot doesn't currently have access 
to the original data, but that's not a huge deal.

Thanks,
Ray

On Feb 18, 2012, at 4:35 AM, Jerzy Karczmarczuk wrote:

> Ray Osborn:
>> 
>> OK - it turns out I can reproduce it in a simple ipython session using 
>> ipython --pylab=qt. 
>> 
>> I set up an image plot as follows:
>> 
>> import numpy as np
>> import matplotlib.pyplot as plt
>> from matplotlib.image import NonUniformImage
>> 
>> x=y=np.linspace(0,2*np.pi,101)
>> X,Y=np.meshgrid(x,y)
>> z=sin(X)*sin(Y)
>> 
>> ax=plt.gca()
>> extent = (x[0],x[-1],y[0],y[-1])
>> im = NonUniformImage(ax, extent=extent, origin=None)
>> im.set_data(x,y,z)
>> 
>> ax.images.append(im)
>> ax.set_xlim(x[0],x[-1])
>> ax.set_ylim(y[0],y[-1])
>> 
>> plt.colorbar(im)
>> 
>> plt.gcf().canvas.draw()
>> 
>> 
>> After that, I try to change the color scale using:
>> 
>> im.set_clim(0,0.5)
>> plt.gcf().canvas.draw()
>> 
>> The colorbar changes scale, but the plot is untouched. Is that the expected 
>> behavior?
>> 
>> Thanks,
>> Ray
> 
> Try, perhaps, after set_clim, to reinstall the data:
> 
> im.set_data(x,y,z)
> plt.gcf().canvas.draw()
> 
> =
> 
> Jerzy Karczmarczuk
> 
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-- 
Ray Osborn
Materials Science Division
Argonne National Laboratory
Argonne, IL 60439, USA
Phone: +1 (630) 252-9011
Email: rosb...@anl.gov




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Virtualization & Cloud Management Using Capacity Planning
Cloud computing makes use of virtualization - but cloud computing 
also focuses on allowing computing to be delivered as a service.
http://www.accelacomm.com/jaw/sfnl/114/51521223/
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