Brian Larsen wrote:
> Hello all, 
> 
> several of my colleagues and I are 99% sure we are making the change from IDL 
> to python-matplotlib.  I have just one issue that I am trying to work out 
> that I need to solve.  We are so far really impressed and looking forward to 
> the change.
> 
> I have seen discussion on this list about imagesc and imshow but none of them 
> have quite answered the questions.  In IDL we spent way too much time writing 
> an clone that is still not full featured:
> http://people.bu.edu/balarsen/IDLdoc/imagesc.html
> 
> I have data of probability distributions which have an X and Y array 
> associated with the axes of the 2-d distribution (image).  What I don't see 
> how to do in any easy fashion is plot this data in a imshow() manner with the 
> axes correct (which are unevenly distributed and need to be plotted on a log 
> axes).  
> 
> This can be done with contourf(X,Y,Z) but this has a few issues:
> - I dont see how to do a log axes on a contour
> - contour is the wrong plot as the inherent smoothing that a contour does is 
> highly undesirable.
> 
> Using matlab imagesc one can easily make plots similar to:
> http://img269.yfrog.com/i/2dprob.png/
> Imagine taking the above plot and make the "pixels" different sizes so that 
> each "pixel" has identical counting statistics.  Now assume that one wanted 
> the Y-axis to be plotted in log.
> 
> Anyone have any thoughts or toy examples?

I am not sure I understand exactly what you want to do, but it sounds 
like pcolormesh would do it.  e.g. with ipython -pylab:

ax = gca()
ax.set_yscale('log')
x = np.arange(10)**1.5
y = np.arange(20)**1.8
z = x[1:] * y[1:, np.newaxis]
pcolormesh(x, y, z)
axis('tight')

Note that with x and y, which can be 1-D or 2-D, you are specifying the 
grid boundaries, not the pixel centers.

Eric



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