Perhaps I missed this but I didn’t see: what happens when both
__array_ufunc__ and __array_function__ are defined? I might want to do this
to for example add support for functions like concatenate or stack to a
class that already has an __array_ufunc__ defines.
This is mentioned in the section “N
Perhaps I missed this but I didn’t see: what happens when both
__array_ufunc__ and __array_function__ are defined? I might want to do this
to for example add support for functions like concatenate or stack to a
class that already has an __array_ufunc__ defines.
On Sat, Jun 2, 2018 at 5:56 PM Steph
Matthew Rocklin and I have written NEP-18, which proposes a new dispatch
mechanism for NumPy's high level API:
http://www.numpy.org/neps/nep-0018-array-function-protocol.html
There has already been a little bit of scattered discussion on the pull
request (https://github.com/numpy/numpy/pull/11189)
As promised distressingly many months ago, I have written up a NEP about
relaxing the stream-compatibility policy that we currently have.
https://github.com/numpy/numpy/pull/11229
https://github.com/rkern/numpy/blob/nep/rng/doc/neps/nep-0019-rng-policy.rst
I particularly invite comment on the two
