On Thu, Apr 25, 2019 at 6:04 PM Stephan Hoyer wrote:
> On Thu, Apr 25, 2019 at 12:46 PM Marten van Kerkwijk <
> m.h.vankerkw...@gmail.com> wrote:
>
>
> It would be nice, though, if we could end up with also option 4 being
>> available, if only because code that just can assume ndarray will be
On Fri, Apr 26, 2019 at 12:04 AM Stephan Hoyer wrote:
> On Thu, Apr 25, 2019 at 12:46 PM Marten van Kerkwijk <
> m.h.vankerkw...@gmail.com> wrote:
>
>> It seems we are adding to the wishlist! I see four so far:
>> 1. Exposed in API, can be overridden with __array_ufunc__
>> 2. One that converts
On Thu, Apr 25, 2019 at 12:46 PM Marten van Kerkwijk <
m.h.vankerkw...@gmail.com> wrote:
> It seems we are adding to the wishlist! I see four so far:
> 1. Exposed in API, can be overridden with __array_ufunc__
> 2. One that converts everything to ndarray (or subclass); essentially the
> current
> What's __array_dtype__? That string doesn't seem to appear in the
> numpy source, and google has no hits…
This was a proposed protocol for dispatching over user-defined dtype objects, I
think Stephan and a few others wrote up a mock at SciPy 2018.
Best Regards,
Hameer Abbasi
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On Thu, Apr 25, 2019 at 1:30 PM Hameer Abbasi wrote:
> Although, in general, I agree with Stephan’s design goals, I agree with
> Marten that the number of protocols are getting larger and may get out of
> hand if not handled properly. There’s even one Marten forgot to mention:
>
On Thu, Apr 25, 2019 at 10:10 AM Stephan Hoyer wrote:
>
> On Wed, Apr 24, 2019 at 9:56 PM Nathaniel Smith wrote:
>>
>> When you say "numpy array specific" and
>> "__numpy_(nd)array_implementation__", that sounds to me like you're
>> trying to say "just step 3, skipping steps 1 and 2"? Step 3 is
> On Thursday, Apr 25, 2019 at 9:45 PM, Marten van Kerkwijk
> mailto:m.h.vankerkw...@gmail.com)> wrote:
> It seems we are adding to the wishlist! I see four so far:
> 1. Exposed in API, can be overridden with __array_ufunc__
> 2. One that converts everything to ndarray (or subclass); essentially
On Sat, Apr 20, 2019 at 12:41 PM Ralf Gommers
wrote:
>
>
> On Thu, Apr 18, 2019 at 10:03 PM Joe Harrington
> wrote:
>
>
>> 3. There's such a thing as a share-in-savings contract at NASA, in which
>> you calculate a savings, such as from avoided costs of licensing IDL or
>> Matlab, and say
It seems we are adding to the wishlist! I see four so far:
1. Exposed in API, can be overridden with __array_ufunc__
2. One that converts everything to ndarray (or subclass); essentially the
current implementation;
3. One that does asduckarray
4. One that assumes all arguments are arrays.
Maybe
On Wed, Apr 24, 2019 at 9:56 PM Nathaniel Smith wrote:
> When you say "numpy array specific" and
> "__numpy_(nd)array_implementation__", that sounds to me like you're
> trying to say "just step 3, skipping steps 1 and 2"? Step 3 is the one
> that operates on ndarrays...
>
My thinking was that
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