On Fri, Jan 4, 2013 at 5:25 PM, Andrew Collette <andrew.colle...@gmail.com> wrote: > I agree the current behavior is confusing. Regardless of the details > of what to do, I suppose my main objection is that, to me, it's really > unexpected that adding a number to an array could result in an > exception.
I think the main objection to the 1.5 behaviour was that it violated "Errors should never pass silently." (from 'import this'). Granted there are tons of places where numpy violates this but this is the one we're thinking about right now... Okay, here's another idea I'll throw out, maybe it's a good compromise: 1) We go back to the 1.5 behaviour. 2) If this produces a rollover/overflow/etc., we signal that using the standard mechanisms (whatever is configured via np.seterr). So by default things like np.maximum(np.array([1, 2, 3], dtype=uint8), 256) would succeed (and produce [1, 2, 3] with dtype uint8), but also issue a warning that 256 had rolled over to become 0. Alternatively those who want to be paranoid could call np.seterr(overflow="raise") and then it would be an error. -n _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
