Jeremy,
The pcolor function can take a vmin and a vmax parameter if you wish to
control the colorscaling. In addition, you can use a special array
structure called a "masked array" to have pcolor ignore "special" values.
Assuming your data is 'vals':
vals_masked = numpy.ma.masked_array(vals, vals == 0.0)
Note that depending on your situation, doing an equality with with a
floating point value probably isn't very reliable, so be sure to test and
modify to suit your needs. 'vals_masked' can then be passed to pcolor
instead of vals.
I hope this helps,
Ben Root
On Wed, Jun 30, 2010 at 9:39 AM, Jeremy Conlin <jlcon...@gmail.com> wrote:
> I am trying to plot some data over a mesh using the plot_surface
> method. However when I plot my data, everything is the same color
> when I expected to get a nice rainbow of colors as in the example:
> http://matplotlib.sourceforge.net/examples/mplot3d/surface3d_demo.html
>
> I have attached a simple script to show what I did as well as the
> result. Essentially, I just copied the above demo, but put my own
> data in. I think the problem arises because I have "holes" in my
> data, or areas where the data is zero. These zeros throw the scaling
> off so I tried to eliminate their effect, but this messed everything
> up.
>
> Essentially my question is: how can I get a nice color distribution
> while at the same time avoid the extreme scaling issues associated
> with some data being zero (while all the other data is ~16)?
>
> Thanks,
> Jeremy
>
>
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