I was just working with a student to do this.  It is straightforward  
(using norms, as Eric suggests), but not short.  I think it would be  
good to include wrappers for creating these norms to MPL.

The advantage is then it works for everything: pcolor, scatter, etc.

-Rob

On Jan 31, 2008, at 12:07 AM, Eric Firing wrote:

> Jordan,
>
> This sounds useful, but I think it can be implemented without any new
> plot type, simply by using a different sort of norm to do the
> colormapping.  I need to add this anyway, and I have a prototype.   
> It is
> very simple.  I will get it in within the next few days, and then you
> can see whether it meets your needs.
>
> Eric
>
> Jordan Dawe wrote:
>> So I have a (slightly) new plot type I would like to add to the
>> matplotlib codebase, and I'd like to ask A) if people would be
>> interested in the patch and B) what the best way to implement it  
>> would be.
>>
>> I am currently calling the plot type "pcontourf"--it's essentially a
>> pcolor, but instead of a continuous color spectra of value, it plots
>> discrete levels of data like contourf does.  I find this kind of plot
>> useful for model output--it displays the model grid, and also  
>> emphasizes
>> data transitions, for example, between the negative and positive  
>> areas
>> of a plot, better than pcolor.  Essentially it is just a contourf
>> wrapper that, instead of calling contourf with values at the  
>> 'center' of
>> a grid cell, calls contourf with points at the edges of the grid  
>> cell so
>> you end up with rectangular areas.
>>
>> If someone is actually interested in clean this up and put it into  
>> svn,
>> my next question is where in the codebase would be the best place  
>> to put
>> it so I can make a clean diff file?  pyplot.py?  I don't quite
>> understand how the matplotlib module hierarchy works.
>>
>> Jordan
>>
>>
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----
Rob Hetland, Associate Professor
Dept. of Oceanography, Texas A&M University
http://pong.tamu.edu/~rob
phone: 979-458-0096, fax: 979-845-6331



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