I'm getting a generally lukewarm not negative response. Should we put it to
a vote?
- Joe
On Fri, Feb 12, 2021, 16:06 Robert Kern wrote:
> On Fri, Feb 12, 2021 at 3:42 PM Ralf Gommers
> wrote:
>
>>
>> On Fri, Feb 12, 2021 at 9:21 PM Robert Kern
>> wrote:
>>
>>> On Fri, Feb 12, 2021 at 1:47
On Tue, 2021-02-16 at 12:40 +0100, Friedrich Romstedt wrote:
> Hi Lev,
>
> Am Di., 16. Feb. 2021 um 11:50 Uhr schrieb Lev Maximov <
> lev.maxi...@gmail.com>:
> >
> > I've reproduced the error you've described and got rid of it
> > without valgrind.
> > Those two lines are enough to avoid the
Hello again,
Am Mo., 15. Feb. 2021 um 16:57 Uhr schrieb Sebastian Berg
:
>
> On Mon, 2021-02-15 at 10:12 +0100, Friedrich Romstedt wrote:
> > Last week I updated my example code to be more slim. There now
> > exists
> > a single-file extension module:
> >
On Tue, Feb 16, 2021 at 10:20 AM PIERRE AUGIER <
pierre.aug...@univ-grenoble-alpes.fr> wrote:
> Hi,
>
> When Numpy 1.20 was released, I discovered numpy.typing and its
> documentation https://numpy.org/doc/stable/reference/typing.html
>
> I know that it is very new but I'm a bit lost. A good API
Hi Lev,
Am Di., 16. Feb. 2021 um 11:50 Uhr schrieb Lev Maximov :
>
> I've reproduced the error you've described and got rid of it without valgrind.
> Those two lines are enough to avoid the segfault.
Okay, good to know, I'll try it! Thanks for looking into it.
> But feel free to find it
Hi,
When Numpy 1.20 was released, I discovered numpy.typing and its documentation
https://numpy.org/doc/stable/reference/typing.html
I know that it is very new but I'm a bit lost. A good API to describe Array
type would be useful not only for type checkers but also for Python
accelerators
I've reproduced the error you've described and got rid of it without
valgrind.
Those two lines are enough to avoid the segfault.
But feel free to find it yourself :)
Best regards,
Lev
On Tue, Feb 16, 2021 at 5:02 PM Friedrich Romstedt <
friedrichromst...@gmail.com> wrote:
> Hello again,
>
> Am
Hi all,
In https://github.com/numpy/numpy/issues/18407 it was reported that
there is a regression for `np.array()` and friends in NumPy 1.20 for
code such as:
np.array(["1234"], dtype=("U1", 4))
# NumPy 1.20: array(['1', '1', '1', '1'], dtype='>> np.array(["1234"], dtype="(4)U1,i")
On Tue, Feb 16, 2021 at 3:13 PM Sebastian Berg
wrote:
> Hi all,
>
> In https://github.com/numpy/numpy/issues/18407 it was reported that
> there is a regression for `np.array()` and friends in NumPy 1.20 for
> code such as:
>
> np.array(["1234"], dtype=("U1", 4))
> # NumPy 1.20:
Hi all,
There will be a NumPy Community meeting Wednesday February 17th at 12pm
Pacific Time (20:00 UTC). Everyone is invited and encouraged to
join in and edit the work-in-progress meeting topics and notes at:
https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both
Best wishes
Sebastian
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