[Numpy-discussion] round(numpy.float64(0.0)) is a numpy.float64

[josef.pktd at gmail.com]

On Mon, Mar 26, 2018 at 10:29 PM, Robert Kern <robert.kern at gmail.com> wrote:
> On Mon, Mar 26, 2018 at 6:28 PM, Nathaniel Smith <njs at pobox.com> wrote:
>>
>> On Mon, Mar 26, 2018 at 6:24 PM, Nathaniel Smith <njs at pobox.com> wrote:
>> > Even knowing that, it's still confusing that round(np.float64(0.0))
>> > isn't the same as round(0.0). The reason is a Python 2 / Python 3
>> > thing: in Python 2, round returns a float, while on Python 3, it
>> > returns an integer – but numpy still uses the python 2 behavior
>> > everywhere.
>> >
>> > I'm not sure if it's possible or worthwhile to change this. If we'd
>> > changed it when we first added python 3 support then it would have
>> > been easy (and obviously a good idea), but at this point it might be
>> > tricky?
>>
>> Oh right, and I forgot: part of the reason it's tricky is that it
>> really would have to return a Python 'int', *not* any of numpy's
>> integer types, because floats have a much larger range than numpy
>> integers, e.g.:
>
> I don't think that's the tricky part. We don't have to change anything but
> our implementation of Python 3's __round__() special method for np.generic
> scalar types, which would be straightforward. The only issue, besides
> backwards compatibility, is that it would introduce a new inconsistency
> between scalars and arrays (which can't use the Python ints). However,
> that's "paid for" by the increased compatibility with the rest of Python.
> For a special method that is used for to interoperate with a Python builtin
> function, that's probably the more important consistency to worry about.
>
> As for the backwards compatibility concern, I don't think it would matter
> much. Everyone who has written code that expects round(np.float64(...)) to
> return a np.float64 is probably already wrapping that with int() anyways.
> Anyone who really wants to keep the scalar type of the output same as the
> input can use np.around().

same would need to apply for ceil, floor, trunc, I guess.

However, np.round has a decimal argument that I use pretty often and
that needs to return a float

>>> np.round(5.33333, 2)
5.3300000000000001

Python makes the return type conditional on whether ndigits is used or not
AFAICS.
>>> round(5.33333, 0)
5.0
>>> round(5.33333)
5

(I'm currently using Python 3.4.4)

Josef

>
> --
> Robert Kern
>
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