On Tue, 10 Nov 2009 16:07:32 -0800, Christopher Barker <chris.bar...@noaa.gov> wrote: > Hi all, > > I have a bunch of points in 2-d space, and I need to find out which > pairs of points are within a certain distance of one-another (regular > old Euclidean norm).
How big is your set of points? > > scipy.spatial.KDTree.query_ball_tree() seems like it's built for this. > > However, I'm a bit confused. The first argument is a kdtree, but I'm > calling it as a method of a kdtree -- I want to know which points in the > tree I already have are closer that some r from each-other. > > If I call it as: > > tree.query_ball_tree(tree, r) > > I get a big list, that has all the points in it (some of them paired up > with close neighbors.) It appears I'm getting the distances between all > the points in the tree and itself, as though they were different trees. > > This is slow, takes a bunch of memory, and I then have to parse out the > list to find the ones that are paired up. > > Is there a way to get just the close ones from the single tree? > > thanks, > > -Chris -- Peter Schmidtke ---------------------- PhD Student at the Molecular Modeling and Bioinformatics Group Dep. Physical Chemistry Faculty of Pharmacy University of Barcelona _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion