Hi everybody,
Thanks to  Chouser's finger tree data structure, it makes it very simple to
keep some elements in a tree/sequence and efficiently maintain values by
some associative operation on all the elements of the collection .. I guess
chouser himself has given series of talks on that. However, I am trying to
see if I can do something like that for two-dimensional data.

For example,
 let us say I have points spread on XY plane, and two axes each parallel to
one of the coordinate axes. So, this would divide the data/points among the
4 quadrants. Now I would like to be able to efficiently divide the data
using the two axes at random and x's and y's and obtain the value of the
associative operation on the elements of each quadrant. for now it could
simply be the sum of the points coordinate wise..

While I have thought of a few options to make it work for two dimensions but
nothing seems right .. I would love to hear what others might have to say
about this.
Thanks
Sunil.

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