[Numpy-discussion] divmod(1.0, 0.0) bug

[Anirudh Subramanian]

Thanks for your inputs, Brock and Stephan.

> (However, note that the backwards compatibility policy you link to is
only a draft, not officially accepted.)

Yes, I didn't realize that. Thanks for pointing that out. In practice from
the little I have seen, I find the NEP very close to what is being followed
in numpy.

Anirudh

On Fri, May 8, 2020 at 5:14 PM Stephan Hoyer <shoyer at gmail.com> wrote:

> On Fri, May 8, 2020 at 4:10 PM Brock Mendel <jbrockmendel at gmail.com>
> wrote:
>
>> FWIW in pandas we post-process floordiv (and divmod) ops to get the
>> "Expected Result" behavior from the OP.
>>
>>
>> On Fri, May 8, 2020 at 11:56 AM Anirudh Subramanian <
>> anirudh2290 at gmail.com> wrote:
>>
>>> Hi all,
>>>
>>> There has been a discussion about divmod (1.0, 0.0) bug here :
>>> https://github.com/numpy/numpy/issues/14900 and
>>> https://github.com/numpy/numpy/pull/16161 .
>>>
>>> *SUMMARY*
>>>
>>> Currently divmod(1.0, 0.0) sets the "Invalid error" and returns (nan,
>>> nan). This is not consistent with IEEE 754
>>> <https://en.wikipedia.org/wiki/IEEE_754> standard which says that
>>> 1.0/0.0 divisions should return inf and raise dividebyzero error. Although
>>> this may not apply to divmod, it should apply to floor_divide and mod.
>>> I have summarized in the table below, summarizing current state and
>>> expected state.
>>>
>>> Operator Warning message Expected warning Result Expected Result
>>> np.divmod Invalid error invalid and dividebyzero ?? nan, nan inf, nan
>>> np.fmod(1.0, 0.0) Invalid error Invalid nan nan
>>> np.floor_divide(1.0, 0.0) Invalid error Dividebyzero nan inf
>>> np.remainder(1.0, 0.0) Invalid error Invalid nan nan
>>>
>>>
>>> For remainder and fmod above, according to the standard, it is supposed
>>> to raise invalid error. We need to change the code to also raise
>>> dividebyzero error for floor_divide.
>>>
>>> The question is what to do for np.divmod (since this is not defined by
>>> standard). My opinion is in this case we need to set both dividebyzero and
>>> invalid error flags since its a combination of these two operations.
>>>
>>> *USER IMPACT*
>>>
>>> This is going to cause a breaking change/silent incorrect results to
>>> atleast some users who are either doing one or two of the following:
>>> 1. expecting nans from their output and check isnan but not isinf in
>>> their code and accordingly do further computations.
>>> 2. who currently call raise only on invalid and not dividebyzero errors
>>> for any of  the above listed operations.
>>>
>>> Considering this we can try one of the two things:
>>> 1. Create a futurewarning for every divmod(1.0, 0.0) path. This may be
>>> very noisy and I cannot think of an action for a user to take to suppress
>>> this.
>>> 2. Since bug fixes are exempt from backwards compatibility policy
>>> <https://numpy.org/neps/nep-0023-backwards-compatibility.html> just
>>> notify in the release notes, maybe after a couple of releases. (More
>>> Impactful)
>>>
>>
> I agree, I think these behaviors could be considered bugs and fixed
> without warning. (However, note that the backwards compatibility policy you
> link to is only a draft, not officially accepted.)
>
> My guess is that these code paths have been rarely exercised, because
> floor division and divmod are most useful for integers.
>
>
>>
>>> *OTHER ISSUES?*
>>>
>>> Depending on the compiler, and if it implements annex F of the C
>>> standard, it may not support 1.0/0.0 operation and may crash. Also this is
>>> the case for true_divide also, so we wont be breaking more users than we
>>> currently are.
>>>
>>> Would like to hear your thoughts about this!
>>>
>>> Anirudh
>>>
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