NumPy has had a way to add a call to a user-supplied function whenever
allocating via PyDataMem_SetEventHook [0]. Python added the tracemalloc
[1] functionality which make this redundant. NumPy also added memory
alloc/free overriding in NEP 49 [2] which will be part of the 1.22
release. I propo
Hi all!
Our next Newcomer’s Meeting is Tomorrow, Thursday November 18, at 4pm UTC.
This is an informal meeting to ask questions, get to know other people and
(hopefully) figure out ways to contribute to NumPy.
Feel free to join if you are lurking around but found it hard to start
contributing -
I think a separate ndenumerate() in the masked array namespace would make a
lot of sense. This is much less risky than changing np.ndenumerate().
On Wed, Nov 17, 2021 at 11:54 AM Andras Deak wrote:
> On Wed, Nov 17, 2021 at 8:35 PM Sebastian Berg
> wrote:
>
>> On Wed, 2021-11-17 at 19:49 +0100,
On Wed, Nov 17, 2021 at 8:35 PM Sebastian Berg
wrote:
> On Wed, 2021-11-17 at 19:49 +0100, Andras Deak wrote:
> > On Wed, Nov 17, 2021 at 7:39 PM Sebastian Berg
> >
> > wrote:
> >
> > > Hi all,
> > >
> > > the `np.ndenumerate` does not work well for masked arrays (like
> > > many
> > > main name
On Wed, 2021-11-17 at 19:49 +0100, Andras Deak wrote:
> On Wed, Nov 17, 2021 at 7:39 PM Sebastian Berg
>
> wrote:
>
> > Hi all,
> >
> > the `np.ndenumerate` does not work well for masked arrays (like
> > many
> > main namespace functions, it simply ignores/drops the mask).
> >
> > There is a PR
On Wed, Nov 17, 2021 at 7:39 PM Sebastian Berg
wrote:
> Hi all,
>
> the `np.ndenumerate` does not work well for masked arrays (like many
> main namespace functions, it simply ignores/drops the mask).
>
> There is a PR (https://github.com/numpy/numpy/pull/20020) to add a
> version of it to `np.ma`
Hi all,
the `np.ndenumerate` does not work well for masked arrays (like many
main namespace functions, it simply ignores/drops the mask).
There is a PR (https://github.com/numpy/numpy/pull/20020) to add a
version of it to `np.ma` (masked array specific). And we thought it
seemed reasonable and w
(Apologies for the cross-posting, if you follow more than one of these
lists, you may see this multiple times.)
Hi all,
I'd like to solicit the feedback of maintainers of NumPy, SciPy,
scikit-learn, and scikit-image, and other interested community members on
this blog post and proposed design to
Hi all,
Our bi-weekly triage-focused NumPy development meeting is Wednesday,
November 17rd at 16:30 UTC (8:30am Pacific Time).
Everyone is invited to join in and edit the work-in-progress meeting
topics and notes:
https://hackmd.io/68i_JvOYQfy9ERiHgXMPvg
I encourage everyone to notify us of issue
Thanks for the heads up Stefan,
I don't have time right now, but I'll definitely take a look at the recording
later.
From: Stefan van der Walt
Sent: 16 November 2021 20:10
To: Discussion of Numerical Python
Subject: [Numpy-discussion] Tensor typing meeting (15 No
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