On 04/09/06, Sebastian Haase <[EMAIL PROTECTED]> 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 ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
