got it, thanks.

I've fixed that typo in a PR I"m working on , too.

-CHB


On Mon, Sep 16, 2019 at 2:41 PM Ralf Gommers <ralf.gomm...@gmail.com> wrote:

>
>
> On Mon, Sep 16, 2019 at 1:42 PM Peter Andreas Entschev <pe...@entschev.com>
> wrote:
>
>> My answer to that: "NumPy". Reference: logo at the top of
>> https://numpy.org/neps/index.html .
>>
>
> Yes, NumPy is the right capitalization
>
>
>
>> In NEP-30 [1], I've used "NumPy" everywhere, except for references to
>> code, repos, etc., where "numpy" is used. I see there's one occurrence
>> of "Numpy", which was definitely a typo and I had not noticed it until
>> now, but I will address this on a future update, thanks for pointing
>> that out.
>>
>> [1] https://numpy.org/neps/nep-0030-duck-array-protocol.html
>>
>> On Mon, Sep 16, 2019 at 9:09 PM Chris Barker <chris.bar...@noaa.gov>
>> wrote:
>> >
>> > Trivial note:
>> >
>> > On the subject of naming things (spelling things??) -- should it be:
>> >
>> > numpy
>> > or
>> > Numpy
>> > or
>> > NumPy
>> > ?
>> >
>> > All three are in the draft NEP 30 ( mostly "NumPy", I noticed this when
>> reading/copy editing the NEP) . Is there an "official" capitalization?
>> >
>> > My preference, would be to use "numpy", and where practicable, use a
>> "computer" font -- i.e. ``numpy`` in RST.
>> >
>> > But if there is consensus already for anything else, that's fine, I'd
>> just like to know what it is.
>> >
>> > -CHB
>> >
>> >
>> >
>> > On Mon, Aug 12, 2019 at 4:02 AM Peter Andreas Entschev <
>> pe...@entschev.com> wrote:
>> >>
>> >> Apologies for the late reply. I've opened a new PR
>> >> https://github.com/numpy/numpy/pull/14257 with the changes requested
>> >> on clarifying the text. After reading the detailed description, I've
>> >> decided to add a subsection "Scope" to clarify the scope where NEP-30
>> >> would be useful. I think the inclusion of this new subsection
>> >> complements the "Detail description" forming a complete text w.r.t.
>> >> motivation of the NEP, but feel free to point out disagreements with
>> >> my suggestion. I've also added a new section "Usage" pointing out how
>> >> one would use duck array in replacement to np.asarray where relevant.
>> >>
>> >> Regarding the naming discussion, I must say I like the idea of keeping
>> >> the __array_ prefix, but it seems like that is going to be difficult
>> >> given that none of the existing ideas so far play very nicely with
>> >> that. So if the general consensus is to go with __numpy_like__, I
>> >> would also update the NEP to reflect that changes. FWIW, I
>> >> particularly neither like nor dislike __numpy_like__, but I don't have
>> >> any better suggestions than that or keeping the current naming.
>> >>
>> >> Best,
>> >> Peter
>> >>
>> >> On Thu, Aug 8, 2019 at 3:40 AM Stephan Hoyer <sho...@gmail.com> wrote:
>> >> >
>> >> >
>> >> >
>> >> > On Wed, Aug 7, 2019 at 6:18 PM Charles R Harris <
>> charlesr.har...@gmail.com> wrote:
>> >> >>
>> >> >>
>> >> >>
>> >> >> On Wed, Aug 7, 2019 at 7:10 PM Stephan Hoyer <sho...@gmail.com>
>> wrote:
>> >> >>>
>> >> >>> On Wed, Aug 7, 2019 at 5:11 PM Ralf Gommers <
>> ralf.gomm...@gmail.com> wrote:
>> >> >>>>
>> >> >>>>
>> >> >>>> On Mon, Aug 5, 2019 at 6:18 PM Stephan Hoyer <sho...@gmail.com>
>> wrote:
>> >> >>>>>
>> >> >>>>> On Mon, Aug 5, 2019 at 2:48 PM Ralf Gommers <
>> ralf.gomm...@gmail.com> wrote:
>> >> >>>>>
>> >> >>>>>>
>> >> >>>>>> The NEP currently does not say who this is meant for. Would you
>> expect libraries like SciPy to adopt it for example?
>> >> >>>>>>
>> >> >>>>>> The NEP also (understandably) punts on the question of when
>> something is a valid duck array. If you want this to be widely used, that
>> will need an answer or at least some rough guidance though. For example, we
>> would expect a duck array to have a mean() method, but probably not a ptp()
>> method. A library author who wants to use np.duckarray() needs to know,
>> because she can't test with all existing and future duck array
>> implementations.
>> >> >>>>>
>> >> >>>>>
>> >> >>>>> I think this is covered in NEP-22 already.
>> >> >>>>
>> >> >>>>
>> >> >>>> It's not really. We discussed this briefly in the community call
>> today, Peter said he will try to add some text.
>> >> >>>>
>> >> >>>> We should not add new functions to NumPy without indicating who
>> is supposed to use this, and what need it fills / problem it solves. It
>> seems pretty clear to me that it's mostly aimed at library authors rather
>> than end users. And also that mature libraries like SciPy may not
>> immediately adopt it, because it's too fuzzy - so it's new libraries first,
>> mature libraries after the dust has settled a bit (I think).
>> >> >>>
>> >> >>>
>> >> >>> I totally agree -- we definitely should clarify this in the
>> docstring and elsewhere in the docs. An example in the new doc page on
>> "Writing custom array containers" (
>> https://numpy.org/devdocs/user/basics.dispatch.html) would also probably
>> be appropriate.
>> >> >>>
>> >> >>>>>
>> >> >>>>> As discussed there, I don't think NumPy is in a good position to
>> pronounce decisive APIs at this time. I would welcome efforts to try, but I
>> don't think that's essential for now.
>> >> >>>>
>> >> >>>>
>> >> >>>> There's no need to pronounce a decisive API that fully covers
>> duck array. Note that RNumPy is an attempt in that direction (not a full
>> one, but way better than nothing). In the NEP/docs, at least saying
>> something along the lines of "if you implement this, we recommend the
>> following strategy: check if a function is present in Dask, CuPy and
>> Sparse. If so, it's reasonable to expect any duck array to work here. If
>> not, we suggest you indicate in your docstring what kinds of duck arrays
>> are accepted, or what properties they need to have". That's a spec by
>> implementation, which is less than ideal but better than saying nothing.
>> >> >>>
>> >> >>>
>> >> >>> OK, I agree here as well -- some guidance is better than nothing.
>> >> >>>
>> >> >>> Two other minor notes on this NEP, concerning naming:
>> >> >>> 1. We should have a brief note on why we settled on the name "duck
>> array". Namely, as discussed in NEP-22, we don't love the "duck" jargon,
>> but we couldn't come up with anything better since NumPy already uses
>> "array like" and "any array" for different purposes.
>> >> >>> 2. The protocol should use *something* more clearly namespaced as
>> NumPy specific than __duckarray__. All the other special protocols NumPy
>> defines start with "__array_". That suggests either __array_duckarray__
>> (sounds a little redundant) or __numpy_duckarray__ (which I like the look
>> of, but is a different from the existing protocols).
>> >> >>>
>> >> >>
>> >> >> `__numpy_like__` ?
>> >> >
>> >> >
>> >> >
>> >> > This could work, but I think we would also want to rename the NumPy
>> function itself to either np.like or np.numpy_like. The later is a little
>> redundant but definitely more self-descriptive than "duck array".
>> >> >
>> >> >>
>> >> >> Chuck
>> >> >> _______________________________________________
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>> >> >> NumPy-Discussion@python.org
>> >> >> https://mail.python.org/mailman/listinfo/numpy-discussion
>> >> >
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>> >
>> >
>> > --
>> >
>> > Christopher Barker, Ph.D.
>> > Oceanographer
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