On Tue, Nov 10, 2009 at 8:17 PM, Christopher Barker <chris.bar...@noaa.gov> wrote: > James Bergstra wrote: >> In some cases a brute-force approach is also good. > > true. > >> If r is a matrix of shape Nx2: >> >> (r*r).sum(axis=1) -2 * numpy.dot(r, r.T) + >> (r*r).sum(axis=1).reshape((r.shape[0], 1)) < thresh**2 >> >> It's brute force, but it takes advantage of fast matrix multiplication. > > I'm more concerned about memory -- doesn't this use N^2 memory? Which > could be an issue here.
Yes, this uses N^2 time and space. It's not a good algorithm when N is large. -- http://www-etud.iro.umontreal.ca/~bergstrj _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
