Hi Nathan,
To deal with your immediate problem of not wanting to see the deprecation
warnings you can continue to use matplotlib.delaunay and suppress the
warnings using e.g.
http://docs.python.org/2/library/warnings.html#temporarily-suppressing-warnings.
This will be OK for a year or two, but eventually we will completely remove
matplotlib.delaunay. It will however give you time to come up with a
solution.
The short answer is
1) replace all use of matplotlib.delaunay.Triangulation with
matplotlib.tri.Triangulation, and
2) use some other form of interpolation than natural neighbour!
Matplotlib has linear and cubic triangular grid interpolators (
http://matplotlib.org/dev/api/tri_api.html); if these are acceptable your
code changes should be minimal. scipy.interpolate has a few more options
(but no natural neighbour) which will be a little more work. Even if you
were to like the natgrid approach I would steer you away from it as I can
see us removing it completely from matplotlib sometime in the future.
Alternatively you could incorporate the matplotlib.delaunay code into your
project and hence carry on using it as you are, but this would be madness
as you would have to deal with the building of a C python extension, plus
the delaunay code is 'not very robust'. You will no doubt have observed
this to be the case, and it is the reason why matplotlib and scipy have
moved away from it to use qhull instead.
I expect we will add more triangular grid interpolators to matplotlib in
due course and I am happy to receive suggestions on this. However, this
will not include natural neighbour. Natural neighbour interpolation is
specific to delaunay triangulation, and as we also support user-specified
triangulations I am only interested in interpolation that covers all
triangulations.
I hope this has been of some help, but I fear not...
Ian Thomas
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