On 04/09/06, Sebastian Haase haase@msg.ucsf.edu wrote:
Thanks for the reply - but read what the doc says:
N.around.__doc__
'Round 'a' to the given number of decimal places. Rounding behaviour is equivalent to Python.
Return 'a' if the array is not floating point. Round both the real and imaginary parts separately if the array is complex. 'it is *not* done this way in Python:
round(.5)
1.0
round(1.5)
2.0
round(2.5)
3.0
( the round obj. method is missing this doc string )
Um, well, the doc is wrong. Numpy should *not* always follow python's lead, and in partciular it's explicit that Numeric's floating point is closer to IEEE floating-point behaviour than python's - compare, for example 1./0. and array(1.)/0.
I really think we should stick to what the doc string say - everybody expects x.5 to round up !!
Not everybody. This (admittedly odd) behaviour wasn't decided on because it was more efficient to implement, it was decided on because a group of very smart numerical analysts agreed that it was the best way to avoid surprising naive users with biased results. (Non-naive users can normally pick from any of several other rounding modes if they want.)
A better question to ask is, "Can I change numpy's rounding behaviour for my programs?" (And, more generally, "can I set all the various floating-point options that the IEEE standard and my processor both support?") I don't know the answer to that one, but it does seem to be a goal that numpy is trying for (hence, for example, the difference between numpy float scalars and python floats).
A. M. Archibald