No dia Sábado, 14 de Janeiro de 2012, Benjamin rootben.r...@ou.edu escreveu: > > > On Saturday, January 14, 2012, Thiago Franco de Moraes < totonixs...@gmail.com> wrote: >> Hi all, >> >> I have the following problem: >> >> Given a array with dimension Nx3, where N is generally greater than >> 1.000.000, for each item in this array I have to calculate its density, >> Where its density is the number of items from the same array with >> distance less than a given r. The items are the rows from the array. >> >> I was not able to think a solution to this using one or two functions of >> Numpy. Then I wrote this code http://pastebin.com/iQV0bMNy . The problem >> it so slow. So I tried to implement it in Cython, here the result >> http://pastebin.com/zTywzjyM , but it is very slow yet. >> >> Is there a better and faster way of doing that? Is there something in my >> Cython implementation I can do to perform better? >> >> Thanks! > > Have you looked at scipy.spatial.KDTree? It can efficiently load up a data structure that lets you easily determine the spatial relationship between datapoints. > > Ben Root
Thanks, Ben, I'm going to do that.
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