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

[Brock Mendel]

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)
>
> *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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