Hi all,

I've added some functionality to my copy hexbin, and I thought I'd

bounce it off folks (esp. Michael) to see if it seems like a good idea

to add it to MPL.

Here's the beginning of the docstring of the new version. What I've

added is the optional argument "C" -- inspired by scatter's "c" argument.

call signature::

hexbin(x, y, C = None, gridsize = 100, bins = None,

xscale = 'linear', yscale = 'linear',

cmap=None, norm=None, vmin=None, vmax=None,

alpha=1.0, linewidths=None, edgecolors='none'

reduce_C_function = np.mean,

**kwargs)Make a hexagonal binning plot of *x* versus *y*, where *x*,

*y* are 1-D sequences of the same length, *N*. If *C* is None

(the default), this is a histogram of the number of occurences

of the observations at (x[i],y[i]).If *C* is specified, it specifies values at the coordinate

(x[i],y[i]). These values are accumulated for each hexagonal

bin and then reduced according to *reduce_C_function*, which

defaults to numpy's mean function (np.mean). (If *C* is

specified, it must also be a 1-D sequence of the same length

as *x* and *y*.)

What do you think? I've also implemented a simple demo making use of

this functionality and an image of the output of the demo. For my own

selfish reasons, I'd love if we could stick this in 0.98.3, but I'm also

happy to hold off to get the release out the door.

-Andrew

hexbin.patch (7.19 KB)