On Fri, Jul 11, 2008 at 11:04 AM, Lou Pecora <[EMAIL PROTECTED]> wrote:
> If your positions are static (I'm not clear on that from your message), > then you might want to check the technique of "slice searching". It only > requires one sort of the data for each dimension initially, then uses a > simple, but clever look up to find neighbors within some epsilon of a chosen > point. Speeds appear to be about equal to k-d trees. Programming is vastly > simpler than k-d trees, however. > This one is actually easy to implement in numpy using argsort. I'm not sure how much speed the integer comparisons buy as opposed to straight floating comparisons; they probably did it that way for the hardware implementation. It might be interesting to make a comparison. Chuck
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