There was an discussion about this on the c.l.p a while ago. Using a sort will scale like O(n log n) or worse, whereas using a set (hash table) will scale like amortized O(n). How to use a Python set to get a unique collection of objects I'll leave to your imagination.
Sturla Molden > On Mon, Dec 15, 2008 at 18:24, Daran Rife <dr...@ucar.edu> wrote: >> How about a solution inspired by recipe 18.1 in the Python Cookbook, >> 2nd Ed: >> >> import numpy as np >> >> a = [(x0,y0), (x1,y1), ...] >> l = a.tolist() >> l.sort() >> unique = [x for i, x in enumerate(l) if not i or x != b[l-1]] >> a_unique = np.asarray(unique) >> >> Performance of this approach should be highly scalable. > > That basic idea is what unique1d() does; however, it uses numpy > primitives to keep the heavy lifting in C instead of Python. > > -- > Robert Kern > > "I have come to believe that the whole world is an enigma, a harmless > enigma that is made terrible by our own mad attempt to interpret it as > though it had an underlying truth." > -- Umberto Eco > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
