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I have been looking for a fast and efficient implementation of finding natural neighbors of a given point (from a set of points in a 2D plane) particularly preferred if written in python. So far, what I have been doing is to use scipy.spatial.Delaunay to find the Delaunay triangulation simplices and creating the adjacency matrix from the resulting graph.

Is there any better way to perform this?

I have managed to get it done with the scipy package scipy.spatial.Delaunay. My approach was to first obtain a delaunay triangulation of the set of points in the 2 dimensional set of points. And then, generate an adjacency matrix with the generated graph from this triangulation.

This is inefficient, but does the job. Any quicker approaches around?

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Maybe you should have a look at: http://www.pyngl.ucar.edu/Functions/Ngl.natgrid.shtml

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