Whoops! A hasty cut-and-paste from my IDLE session. This should read: import numpy as np
a = [(x0,y0), (x1,y1), ...] # A numpy array, but could be a list l = a.tolist() l.sort() unique = [x for i, x in enumerate(l) if not i or x != l[i-1]] # <---- a_unique = np.asarray(unique) Daran -- On Dec 15, 2008, at 5:24 PM, Daran Rife 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. > > Daran > > -- > > > Hi, > > I the following problem: I have a relatively long array of points > [(x0,y0), (x1,y1), ...]. Apparently, I have some duplicate entries, > which > prevents the Delaunay triangulation algorithm from completing its > task. > > Question, is there an efficent way, of getting rid of the duplicate > entries? > All I can think of involves loops. > > Thanks and regards, > Hanno _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion