matplotlib/basemap — pull request #124 by barronh (2013-09-11 17:38:07+00:00)
Title: Convenience Modifications to Basemap for LCC

Jeff,

As we discussed in Nov 2011, there are a few convenience modifications that would make basemap much easier for parts of the air quality communit. I have forked, and made the updates. As a reminder, I've copied my original email to you.

I am a huge fan of basemap and I am getting great feedback about the
quality of the figures it produces. Well done! I have some ideas to
make using the LCC projection easier, and I am not sure the right
forum for discussing these with you, so I resorted to email.

I often work with LCC projections and I have an idea for how to make
that easier (at least for my datasets). I'll start by describing my
usage so that if there is an better solution that what I am
suggesting, you can tell me.

I often have the X/Y origin in LCC meters, dX/dY in meters, n rows,
ncols, as well as the reference lat/lon etc. Currently I believe that
matplotlib can create an LCC domain by specifying the lon/lat corners
or the reference lat/lon and width/height. In the case where you can
calculate the corners in LCC meters, you would have to generate a
projection and take an inverse solution for the corners approach. For
the width/height approach, there is a symetric assumption that is
often not valid for nested regional meteorology datasets.

At least for LCC, you can use the same type of logic that you used in
your width/height approach. As long as you have llcrnrx/llcrnry and
either width/height or urcrnrx/urcrnry, you can create the LCC
project. I have modified my __init__.py file to do just this. I have
attached the __init__.py file from version 1.0 for your review.
Currently, I just update my code whenever I download a new version,
but I thought that my edits might have broader appeal.