hi all, long time no connect.
i have a data-centric app (i.e., no visualization, sadly), but part of
what it needs to do is take two 3D data sets (float x, float y, float
value) and construct a set of tuples, each of which contains an element
in data set 1, and the elements in data set 2 that are closer to it than
to any other point in data set 1.
i'd prefer to adopt an existing data model rather than write my own,
and of course visad came to mind.
something, somewhere in the code knows how to do nearest-neighbor calcs
for interpolation; i don't see anything about voronoi diagrams, but
there's delaunay class hierarchy, so i'm at least partway there.
has anybody done this kind of thing with the visad data model? or can
you suggest another avenue i should take?
i do have an out: the data sets are small enough (say, 20 in one and
25,000 in the other) that brute force will serve -- i can compute
500,000 euclidean distances and sort them out in a few seconds. but that
would be aesthetically displeasing!
thanks in advance,
-- rw
The wizards come back. The wizards come back, extremely cranky.
--Clay Shirky, "A Group Is Its Own Worst Enemy"
