On Tue, Jul 15, 2008 at 5:37 PM, Ryan May <[EMAIL PROTECTED]> wrote:
> I welcome any comments/criticism to help improve this.
Hey Ryan,
I have looked at this code briefly and have a few minor comments. I
think Eric, who did the bulk of the current quiver implementation, and
as an oceanographer is in a field much closer to yours than mine, will
provide more useful feedback and should ultimately handle the patch
submission.
My first comment is that the code looks very good -- it is well
thought out and commented, and t is definitely suitable for inclusion
in the main line. Certainly the Barbs class can live in the
collections module. You note in the driver code that you are worried
about pollution of the axes namespace by including a domain specific
method, and this is a reasonable worry, but the axes namespace is
currently so polluted with plotting methods that it is a small worry.
I think it would be fine for you to rework your code into a patch
which provides the Barbs collection in matplotlib.collections, an Axes
method, and a pyplot interface function (with a pylab module level
docstring entry). The overloading of the Axes namespace is not ideal,
but it's what we've got.
My second comment has to do with your comment at the end of the example:
#Showing colormapping with uniform grid. Unfortunately, only the flags
#on barbs get colormapped this way.
On a cursory read of the code, it looks like you have implemented
everything as a single poly collection, and the reason the flags only
get colored is that the varicolored is black. It seems like there are
two solutions: write your class as a combination of poly collection
(for the flags) and line collection (for the barbs) and colormap both
(there are some line collection colormapping examples in the examples
subdir courtesy of Eric). The 2nd alternative, which I haven't
explored, is to set the edgecolor equal to the facecolor and support
colormapping of the edgecolors.
Overall this is very promising, and I wish you the best trying to make
mpl serviceble to the meteorology community. Jeff Whitaker has done a
phenomenal job with basemap providing extensions for those needing
cartographic projections as a toolkit. Depending on how far you want
to go with meteorological support, we can include the changes in the
mainline or fold them into a toolkit if they become hyper-specialized.
JDH
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