On Sat, Mar 10, 2018 at 4:27 AM, Matthew Rocklin wrote:
> I'm very glad to see this discussion.
>
> I think that coming up with a single definition of array-like may be
> difficult, and that we might end up wanting to embrace duck typing instead.
>
> It seems to me that different array-like classe
Hi,
I have discovered what I believe is a bug with array slicing involving 3D (and
higher) dimension arrays. When slicing a 3D array by a single value for axis 0,
all values for axis 1, and a list to slice axis 2, the dimensionality of the
resulting 2D array is flipped. However, slicing more t
ke, 2018-03-21 kello 20:40 +, Michael Himes kirjoitti:
> I have discovered what I believe is a bug with array slicing
> involving 3D (and higher) dimension arrays. When slicing a 3D array
> by a single value for axis 0, all values for axis 1, and a list to
> slice axis 2, the dimensionality of
I think that with your comments in mind, it may just be best to embrace
duck typing, like Matthew suggested. I propose the following workflow:
- __array_concatenate__ and similar "protocol" functions return
NotImplemented if they won't work.
- "Base functions" that can be called directly
ke, 2018-03-21 kello 20:40 +, Michael Himes kirjoitti:
> I have discovered what I believe is a bug with array slicing
> involving 3D (and higher) dimension arrays. When slicing a 3D array
> by a single value for axis 0, all values for axis 1, and a list to
> slice axis 2, the dimensionality of
This NEP draft has some more hints/explanations if you are interested:
https://github.com/seberg/numpy/blob/5becd12914d0402967205579d6f59a9815
1e0d98/doc/neps/indexing.rst#examples
Plus, it tries to avoid the word "subspace" hehehe.
- Sebastian
On Thu, 2018-03-22 at 10:41 +0100, Pauli Virtanen
|Hello all, PR #9998 (https://github.com/numpy/numpy/pull/9998/) proposes
an update to the nditer API, both C and python. The issue (link) is that |||sometimes nditer uses temp arrays via the "writeback" mechanism, the
data is copied back to the original arrays "when finished". However
"when fin
Hello all, PR #9998 (https://github.com/numpy/numpy/pull/9998/) proposes
an update to the nditer API, both C and python. The issue
(https://github.com/numpy/numpy/issues/9714) is that sometimes nditer
uses temp arrays via the "writeback" mechanism, the data is copied back
to the original arrays
Hello,
Is it normal, expected and desired that :
round(numpy.float64(0.0)) is a numpy.float64
while
round(numpy.float(0.0)) is an integer?
I find it disturbing and misleading. What do you think? Has it already been
discussed somewhere else?
Best regards,
Olivier
_
numpy.float is an alias to the python float builtin.
https://github.com/numpy/numpy/issues/3998
On Thu, Mar 22, 2018 at 2:26 PM Olivier wrote:
> Hello,
>
>
> Is it normal, expected and desired that :
>
>
> round(numpy.float64(0.0)) is a numpy.float64
>
>
> while
>
> round(numpy.flo
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