3D plotting in mpl is unmaintained, so I don't recommend relying on it 
unless you can bring it up to date and maintain it.

After committing a bugfix to svn, the following works with svn mpl and 
does something like what you want (but might not work with whatever 
version of mpl you are using.)
----------------------------------
from pylab import *
from  matplotlib import axes3d
N = 30
x = 0.9*rand(N)
y = 0.9*rand(N)
z = rand(N)
c = rand(N)
area = pi*(10 * rand(N))**2 # 0 to 10 point radiuses
fig = gcf()
ax3d = axes3d.Axes3D(fig)
plt = fig.axes.append(ax3d)

ax3d.scatter(x,y,z,s=area, marker='^', c=c)

show()
-----------------------------------------

A more general problem is that a 3D scatter plot is ambiguous--how do 
you know where a point really is in 3D?  You would have to do something 
like mapping color to Z.  Is that what you want to do?

Eric

william ratcliff wrote:
> Is there a way to choose the color map for doing scatter plots using 
> Axes3D?  In the test_scatter() example in the class, there is a line 
> something like:
> 
> ax.scatter3D(xs,ys,zs, c='r')
> 
> I would like to plot points based on 3 dimensional coordinates specified 
> by xs,ys, zs, which works great.  However, I would like to color the 
> points with a third array, for example, cs which would either specify an 
> index in a color map, or even just an intensity of a given color.  Is 
> this possible within matplotlib?
> 
> Thanks,
> William
> 
> 
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