[Numpy-discussion] Bitwise operations and unsigned types
Sat Apr 7 07:43:21 CDT 2012
On Fri, Apr 6, 2012 at 3:50 PM, Charles R Harris
> On Fri, Apr 6, 2012 at 3:57 AM, Nathaniel Smith <email@example.com> wrote:
>> On Fri, Apr 6, 2012 at 7:19 AM, Travis Oliphant <firstname.lastname@example.org>
>> > That is an interesting point of view. I could see that point of
>> > 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
>> > 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,
>> In : a
>> Out: array([0, 1, 2, 3])
>> In : a -= 1.5
>> In : a
>> Out: 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!
As a second datapoint, it did catch real bugs in scikit-learn too. On the
other hand, it required a workaround in ndimage.
>> 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.
We discussed reverting the unsafe casting behavior for 1.7 in the thread I
linked to above. Do we still want to do this? As far as I can tell it
didn't really cause problems so far.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion