On Fri, 13 Jun 2025 at 16:43, Ralf Gommers via NumPy-Discussion <
numpy-discussion@python.org> wrote:
>
> For 2FA and repository/PyPI access, we'll start making changes soon. Note
> that GitHub has recently made changes to its 2FA settings that ask for
> action from many people: on https://github.
On Wed, Apr 30, 2025, 08:41 Charles R Harris via NumPy-Discussion <
numpy-discussion@python.org> wrote:
> Just thought I'd pass this along for discussion.
>
> Chuck
>
> -- Forwarded message -
> From:
> Date: Tue, Apr 29, 2025 at 4:09 PM
> Subject: Research Opportunity: Can we moni
Thanks for everyone's help, I'll look into those links matti.
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>
> Wow, that would be a pretty serious optimization bug to override Kahan
> summation. Are you speaking of some theoretical future version of the
> interpreter, or of the current state of things?
>
I just wanted to know how the current interpreter worked.
_
On Fri, 20 Dec 2024 at 18:23, Andrew Nelson wrote:
> Wow, that would be a pretty serious optimization bug to override Kahan
>> summation. Are you speaking of some theoretical future version of the
>> interpreter, or of the current state of things?
>>
>
> I just wan
esentation by doing the following:
```
dx = (x0 + h) - x0
```
Or is there a risk that the Python interpreter would prematurely optimize
that to give:
```
dx = h
```
--
_
Dr. And
On Mon, 28 Oct 2024 at 15:06, Andrew Nelson wrote:
> Hi all,
> is there a canonical way of serialising Generators
>
Specifically I'm interested in a safe way (i.e. no pickle) of
saving/restoring Generator state via HDF5 file storage.
___
Hi all,
is there a canonical way of serialising Generators (not via pickle). Would
the following be reasonable for saving and restoring state:
```
def serialize_rng(rng):
klass = rng.bit_generator.state['bit_generator']
entropy = rng.bit_generator.seed_seq.entropy
return klass, entropy
On Wed, 2 Oct 2024 at 22:09, Usha Gayatri via NumPy-Discussion <
numpy-discussion@python.org> wrote:
> I am working on a Jupyter notebook in Anaconda Navigator. I have done some
> projects in 2021, 2022,2023 and 2024. When I run my old project which was
> created in 2021. it is giving errors.I am
>
> I made the second PR for full wheel with openblas. It is reviewed, but
> rejected as solution with linaro built openblas is not good enough, so I am
> investigating alternate options for cross compiling openblas.
> While I am working on this I have one question about the wheel without
> OpenBLA
release.
regards,
Andrew.
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My git config is:
[remote "origin"]
url = https://github.com/andyfaff/numpy.git
fetch = +refs/heads/*:refs/remotes/origin/*
[remote "numpy"]
url = https://github.com/numpy/numpy.git
fetch = +refs/heads/*:refs/remotes/numpy/*
[branch "main"]
remote =
On Mon, 5 Aug 2024 at 10:34, Charles R Harris
wrote:
>
> On Sun, Aug 4, 2024 at 4:25 PM Andrew Nelson wrote:
>
>> Hi all,
>> for some reason my fork has got way out of date and is missing commits
>> from back to April. I'm not sure if my fork got messed up, or w
Hi all,
for some reason my fork has got way out of date and is missing commits from
back to April. I'm not sure if my fork got messed up, or whether the numpy
repo history has been affected.
Is anyone else experiencing problems?
--
_
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>
>
>>
>> - the seed/SeedSequence that was used to construct the BitGenerator
>>
>
> >>> rng = np.random.default_rng()
> >>> rng.bit_generator.seed_seq
> SeedSequence(
> entropy=186013007116029215180532390504704448637,
> )
>
> In some older versions of numpy, the attribute was semi-private as
>
,
but it would sure be nice to figure out how to replicate the BitGenerator
without having to do that.
I'm thinking of something like:
```
rng = np.random.default_rng(190828902908)
rng.uniform(size=(100,))
# 190828902908
print(rng.initial_seed)
```
--
_
On Thu, Jul 11, 2024, 22:08 slobodan.miletic--- via NumPy-Discussion <
numpy-discussion@python.org> wrote:
> Hi,
>
> I am writing on behalf of my team from Endava company. Our task is to work
> with opensource community, and setup multiple applications for use on win11
> arm64 machines.
> One of t
Hi all,
in case you weren't aware there are now cp313 numpy nightly wheels
available on https://anaconda.org/scientific-python-nightly-wheels/numpy.
This should help with downstream testing pipelines.
A.
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I'm not sure if we've discussed this yet. I propose we start making nightly
wheels for cp313 just after numpy2.0 gets officially released. That way
there's no churn in the wheel infra. Note that there's already a 3.13dev
job in CI.
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On Mon, 9 Oct 2023 at 23:50, Matthew Brett wrote:
> Hi,
>
> On Mon, Oct 9, 2023 at 11:49 AM Andrew Nelson wrote:
> Could you say more about why you consider:
> np.mean(x, dropna=True)
> to be less clear in intent than:
> np.nanmean(x)
> ? Is it just that someone could
On Mon, 9 Oct 2023 at 20:34, wrote:
> Surely you can do this for all functions of eg.nan*. Why separate them is
> the only thing that distinguishes them. Setting the parameter seems to be
> more handy and user-friendly. Well for me it's seems better to do it right
> away in NumPy 2.0
>
I think
On Mon, 9 Oct 2023 at 16:36, Jerome Kieffer wrote:
> On Fri, 06 Oct 2023 19:17:22 -
> norbertpiotraduc...@gmail.com wrote:
>
> > Hi,
> > I have an idea to change the numpy.percentile. Think numpy.percentile
> and numpy.nanpercentyl are the same features, and the only difference is
> that nump
On Mon, 21 Aug 2023 at 18:39, Ralf Gommers wrote:
> Hi all,
>
> On behalf of the steering council, I am very happy to announce that Andrew
> is joining the Maintainers team. Andrew has been contributing to our CI
> setup in particular for the past year, and has contributed for example the
> Cirru
On Wed, Aug 16, 2023, 23:48 Benjamin Root wrote:
> With regards to scheduling wheel builds (and this may already be
> completely obvious), but numpy should consider a scheduled build time that
> comes reasonably before scipy's scheduled build time so that there is a
> quicker turn-around time wit
On Wed, 16 Aug 2023 at 10:51, Andrew Nelson wrote:
> There's a scipy issue on this that discusses how to reduce usage,
> https://github.com/scipy/scipy/issues/19006.
>
> Main points:
>
> - at the moment CI is run on PR and on Merge. Convert to only running on
> PR comm
There's a scipy issue on this that discusses how to reduce usage,
https://github.com/scipy/scipy/issues/19006.
Main points:
- at the moment CI is run on PR and on Merge. Convert to only running on PR
commits. I've just submitted a PR to do this for numpy.
- add a manual trigger. Simple to achieve
The array-api documentation (
https://data-apis.org/array-api/latest/API_specification/generated/array_api.asarray.html#array_api.asarray)
for `asarray` has a copy keyword, the numpy version doesn't. Is there a
plan to add such a keyword to no.asarray?
I guess this is part of a general question,
What is the effect of these changes for transcendental functions in the
complex plane?
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On Wed, 21 Dec 2022 at 20:40, Matti Picus wrote:
> Maybe we should have a scientific-python wide discussion of what
> platforms we wish to support, like NEP 29 for python versions. The NEP
> should include some mechanism for adding new platforms. It doesn't make
> sense to me to be testing someth
On Wed, 21 Dec 2022 at 07:29, Andrew Nelson wrote:
> In https://github.com/scipy/scipy/issues/17630 we're seeing some issues
> (amongst others) with the scipy test suite that uses numpy==1.24.0 on
> musllinux.
>
> I was wondering if numpy would like to add a musllinux CI entr
akin to
https://github.com/scipy/scipy/blob/main/ci/cirrus_general_ci.yml be
created. It's relatively easy to do with cirrus-ci.
I can make the PR if there is appetite.
_
Dr. And
On Thu, 8 Sept 2022, 19:42 Sebastian Berg,
wrote:
>
> TL;DR: NumPy scalars representation is e.g. `34.3` instead of
> `float32(34.3)`. So the representation is missing the type
> information. What are your thoughts on changing that?
> From the Python documentation on repr:
>From the Python
ested). I would expect numpy wheels to take less time to build.
I think it would be a relatively minor modification of the
.github/workflows/wheels script.
cheers,
Andrew.
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Might be a 'warmup' of the timeit module?
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Member address
Is there a way to figure out which files are not touched by any open PR?
That way numpy might be able to do a lot more than an incremental code
alignment.
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On Tue, 19 Oct 2021 at 09:41, Matthew Brett wrote:
>
> Is it possible you have a funny option in a pytest configuration file
> somewhere?
>
Thanks for the tip. Yes, I had a directory called test in the CWD, which
probably confused things. The tests run now.
Sorry for the noise.
_
I realised that I hadn't installed hypothesis. Now things are a little
different (the number of tests detected), but still not working:
```
conda create -n test -c defaults python=3.10
conda activate test
pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple numpy
pip install pytest
On Mon, 18 Oct 2021, 23:44 Charles R Harris,
wrote
> ```
>>
>
> Thanks for testing. Are you on Intel or Arm?
>
Intel
>
>
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On Mon, 18 Oct 2021 at 07:50, Charles R Harris
wrote:
> Hi All,
> It would be nice if someone could test the nightly universal2 wheels for
> Mac, they can be installed with
>
> pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple
> numpy
>
> Chuck
>
Seems to pip install ok onto
> I'd say we may perhaps want to do this, but only if and when it becomes
much easier - for example once we have migrated all our wheel build infra
to GitHub Actions and cibuildwheel
I've been really impressed with cibuildwheel. It works well on my project,
so I'd be interested to see how it goes
On Thu, 16 Sep 2021, 03:25 george trojan, wrote:
>
> I just wrote the following code:
>
> twb = scipy.optimize.fsolve(phi, tdb, args=(tdb, p, w, hd_tdb, hg_tdb),
> xtol=1e-8)
> tdb, p, w, hd_tdb, hg_tdb
> twb.shape
> print("wet-bulb temperature {:.5f} [deg K]".format(float(twb)))
>
> The output i
> > ___
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> > NumPy-Discussion@python.org
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On Thu, 15 Apr 2021 at 07:15, Robert Kern wrote:
> On Wed, Apr 14, 2021 at 4:37 PM Joachim Wuttke
> wrote:
>
>> Regarding numpy, I'd propose a bolder measure:
>> To let savetxt(fname, X, ...) store exactly the same information in
>> compressed and uncompressed files, always invoke gzip with mtim
For my project (refnx) I solely use GH Actions to test and make wheels. In
my workflow (
https://github.com/refnx/refnx/blob/master/.github/workflows/pythonpackage.yml)
I make a 3.7/3.8/3.9 matrix across Linux/macOS/Windows. First of all I make
the wheels for all those combos, then install the whee
Python 3.9 beta is ~ May 18
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On Mon, 4 May 2020, 07:26 Charles R Harris,
wrote:
> Hi All,
>
> The NumPy "nightly" wheel builds, actually built weekly on Sunday
> mornings, have moved to
> https://anaconda.org/scipy-wheels-nightly/numpy/files. They can be
> installed/downloaded using pip:
>
That's awesome, thank you. Would
Well done, that's a sizeable grant and has the ability to really move
things along.
On Fri, 15 Nov 2019, 13:35 Stefan van der Walt,
wrote:
> Hi Ralf,
>
> On Thu, Nov 14, 2019, at 15:42, Ralf Gommers wrote:
>
> I'm very pleased to announce that NumPy and OpenBLAS have received a joint
> grant for
2]
> https://developers.google.com/season-of-docs/docs/participants/project-numpy
> [3]
> https://developers.google.com/season-of-docs/docs/participants/project-scipy
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On Tue, 3 Jul 2018 at 09:31, Charles R Harris
wrote:
>
> ISTR that some parallel processing applications sent pickled arrays around
> to different processes, I don't know if that is still the case, but if so,
> no copy might be a big gain for them.
>
That is very much correct. One example is u
On Tue, 26 Jun 2018 at 17:12, Eric Wieser
wrote:
> > I don't think it should be relegated to the "officially discouraged"
> ghetto of `.legacy_index`
>
> The way I read it, the new spelling lof that would be the explicit but not
> discouraged `image.vindex[rr, cc]`.
>
If I'm understanding correc
On Tue, 26 Jun 2018 at 16:24, Juan Nunez-Iglesias
wrote:
> > Plain indexing arr[...] should return an error for ambiguous cases.
> [...] This includes every use of vectorized indexing with multiple integer
> arrays.
>
> This line concerns me. In scikit-image, we often do:
>
> rr, cc = coords.T #
Other factors hindering new contributors:
1) Being unfamiliar with git. e.g. knowing that you have to fork numpy
first, then clone from your fork, then create a feature branch. That's just
the """straightforward bit""". It's hell the first time you have to rebase
something/correct commit messages/
On 30 January 2018 at 17:22, Andrew Nelson wrote:
> Hi all,
> I have a matrix multiplication that I'd like to optimize.
>
> I have a matrix `a` (dtype=complex) with shape (N, M, 2, 2). I'd like to
> do the following multiplication:
>
> a[:, 0] @ a[:, 1] @ ...
d M>=2. So for each row do M-1 matrix multiplications of 2x2 matrices.
The output should have shape (N, 2, 2).
What would be the best way of going about this?
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Something similar was mentioned at
https://github.com/scipy/scipy/issues/8325.
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-1.14.0
This doesn't seem to be an issue on our travis tests, only the windows
tests. Is this a bug?
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> The same warning would have been issued from the same place in each of
the variations you tried.
That's not the case, I tried with np.min([1, 2, 3, np.nan]) in a fresh
interpreter and no warning was raised.
Furthermore on my work computer (conda python3.6.2 with pip installed
numpy) I can't get
Further to my last message, why is the warning only raised once?
```
>>> import numpy as np
>>> np.min([1, np.nan])
/Users/andrew/miniconda3/envs/dev3/lib/python3.6/site-packages/numpy/core/_methods.py:29:
RuntimeWarning: invalid value encountered in reduce
return umr_minimum(a, axis, None, out,
ncountered in reduce
return umr_minimum(a, axis, None, out, keepdims)
nan
>>> np.min([1, 2, np.nan])
nan
>>> np.min([np.nan, 1, 2])
nan
>>> np.min([np.nan, 1])
nan
Why is there a RuntimeWarning for the first example, but not the others? Is
this expected beh
> I think the consistency between bool([]) and
bool(array([])) is worth preserving
I'm with Eric Firing on this one. Empty sequences are False in Python.
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