On Thu, Jun 2, 2011 at 5:42 PM, <josef.p...@gmail.com> wrote: > On Wed, Jun 1, 2011 at 9:35 PM, David Cournapeau <courn...@gmail.com> wrote: >> On Thu, Jun 2, 2011 at 1:49 AM, Mark Miller <markperrymil...@gmail.com> >> wrote: >>> Not quite. Bincount is fine if you have a set of approximately >>> sequential numbers. But if you don't.... >> >> Even worse, it fails miserably if you sequential numbers but with a high >> shift. >> >> np.bincount([100000001, 100000002]) # will take a lof of memory >> >> Doing bincount with dict is faster in those cases. > > same with negative numbers, but in these cases I just subtract the min > and we are back to the fast bincount case
Indeed, you can also deal with large numbers which are not consecutive by using a lookup-table. All those methods are quite error-prone in general, and reallly, there is no reason why bincount could not handle the general case, cheers, David _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
