[Numpy-discussion] Bitwise operations and unsigned types

[Charles R Harris]

On Fri, Apr 6, 2012 at 3:57 AM, Nathaniel Smith <njs at pobox.com> wrote:

> On Fri, Apr 6, 2012 at 7:19 AM, Travis Oliphant <travis at continuum.io>
> wrote:
> > That is an interesting point of view.     I could see that point of view.
> >  But, was this discussed as a bug prior to this change occurring?
> >
> > I just heard from a very heavy user of NumPy that they are nervous about
> > upgrading because of little changes like this one.   I don't know if this
> > particular issue would affect them or not, but I will re-iterate my view
> > that we should be very careful of these kinds of changes.
>
> I agree -- these changes make me very nervous as well, especially
> since I haven't seen any short, simple description of what changed or
> what the rules actually are now (comparable to the old "scalars do not
> affect the type of arrays").
>
> But, I also want to speak up in favor in one respect, since real world
> data points are always good. I had some code that did
>  def do_something(a):
>    a = np.asarray(a)
>    a -= np.mean(a)
>    ...
> If someone happens to pass in an integer array, then this is totally
> broken -- np.mean(a) may be non-integral, and in 1.6, numpy silently
> discards the fractional part and performs the subtraction anyway,
> e.g.:
>
> In [4]: a
> Out[4]: array([0, 1, 2, 3])
>
> In [5]: a -= 1.5
>
> In [6]: a
> Out[6]: array([-1,  0,  0,  1])
>
> The bug was discovered when Skipper tried running my code against
> numpy master, and it errored out on the -=. So Mark's changes did
> catch one real bug that would have silently caused completely wrong
> numerical results!
>
>
> https://github.com/charlton/charlton/commit/d58c72529a5b33d06b49544bc3347c6480dc4512
>
> Yes, these things are trade offs between correctness and convenience. I
don't mind new warnings/errors so much, they may break old code but they
don't lead to wrong results. It's the unexpected and unnoticed successes
that are scary.

Chuck
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20120406/05323dfa/attachment.html>