[Numpy-discussion] Changed behavior of np.gradient

Nathaniel Smith njs at pobox.com
Tue Oct 14 13:50:24 EDT 2014


On 14 Oct 2014 18:29, "Charles R Harris" <charlesr.harris at gmail.com> wrote:
>
>
>
> On Tue, Oct 14, 2014 at 10:57 AM, Nathaniel Smith <njs at pobox.com> wrote:
>>
>> On 4 Oct 2014 22:17, "Stéfan van der Walt" <stefan at sun.ac.za> wrote:
>> >
>> > On Oct 4, 2014 10:14 PM, "Derek Homeier" <
derek at astro.physik.uni-goettingen.de> wrote:
>> > >
>> > > +1 for an order=2 or maxorder=2 flag
>> >
>> > If you parameterize that flag, users will want to change its value
(above two). Perhaps rather use a boolean flag such as "second_order" or
"high_order", unless it seems feasible to include additional orders in the
future.
>>
>> Predicting the future is hard :-). And in particular high_order= would
create all kinds of confusion if in the future we added 3rd order
approximations but high_order=True continued to mean 2nd order because of
compatibility. I like maxorder (or max_order would be more pep8ish I guess)
because it leaves our options open. (Similar to how it's often better to
have a kwarg that can take two possible string values than to have a
boolean kwarg. It makes current code more explicit and makes future
enhancements easier.)
>
>
> I think maxorder is a bit misleading. The both versions are second order
in the interior while at the ends the old is first order and the new is
second order. Maybe edge_order?

Ah, that makes sense. edge_order makes more sense to me too then - and we
can always add interior_order to complement it later, if appropriate.

The other thing to decide on is the default. Is the 2nd order version
generally preferred (modulo compatibility)? If so then it might make sense
to keep it the default, given that there are already numpy's in the wild
with that version, so we can't fully guarantee compatibility even if we
wanted to. But what do others think?

-n
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