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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