3.13+ and not hurt anyone
> unless there's a major development.
> >
> > Little rant finished. :)
> > ___
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> > To unsubscribe send an email to numpy
you have any concrete example that might be worth taking
> a look at in more detail? Either for performance or accuracy.
>
> --
> Robert Kern
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t;
> Cheers,
>
> Matthew
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t (which still
>> exists),
>
>
> What discrepancy?
>
> Cheers,
> Ralf
>
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> http
o merge PRs. And having to
> wait longer for new Python features is also annoying.
>
> Aaron Meurer
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woutH)
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Sand Point Way NE (206) 526-6329 fax
> > Seattle, WA 98115 (206) 526-6317 main reception
> >
> > chris.bar...@noaa.gov <mailto:chris.bar...@noaa.gov>
>
>
> Just an empty response since this ended up in my spam filter, and I am
> probably not the on
Matplotlib has also migrated to building wheels via github actions and it
has been working well.
Tom
On Mon, Nov 16, 2020, 17:48 Andrew Nelson wrote:
> 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
not sure it's clearer, the current NEP has a nice graphic and
>> > > literally says "a project with a major or minor version release in
>> > > November 2020 should support Python 3.7 and newer."). However happy
>> > > to adopt it if it makes others happy - in the end it comes down to
>> > > the same thing: it's recommended to drop Python 3.6 now.
>> > >
>> > > > My personal opinion is that somewhere in the range of 24-36
>> > > > months would be appropriate.
>> > >
>> > > +1
>> > >
>> > > Cheers,
>> > > Ralf
>> > >
>> > >
>> > >
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>> > > NumPy-Discussion@python.org
>> > > https://mail.python.org/mailman/listinfo/numpy-discussion
>> > >
>> >
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goal? So far it is convenient that all the repos that upload
> to https://anaconda.org/multibuild-wheels-staging are under one org to
> coordinate upload token use.
>
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are is
>> > used".
>> >
>> > Many thanks to all of the contributors who have put so much time and
>> > energy into NumPy. ✨ ❤️ 😃
>> >
>> > [1] https://github.com/gazprom-neft/petroflow
>> > [2] https://github.com/climate-strike/analysis
>> > [3] https://github.com/climate-strike/license
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>> >
>>
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below
for a link to the full job description and application instructions.
The timeline on this is rather short, so applications are due Jan 3.
https://discourse.matplotlib.org/t/now-hiring-matplotlib-research-software-engineering-fellow/20701
Tom and Hannah
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; see NEP 0 for more details.
Tom
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as there are many interested parties (from the other
projects) that may not be subscribed to the numpy mailing list.
Tom
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I suspect this is due to issues with sphinx 1.8.0. Matplotlib also has
this problem (see https://github.com/matplotlib/matplotlib/pull/12183).
Tom
On Mon, Sep 17, 2018 at 10:47 AM Matti Picus wrote:
> I can enter a search term (say `ndarray`) in
> www.numpy.org/devdocs/search.html, but the res
I think the NEP does a very good job of capturing the high-level issue
around duck arrays and will serve as a solid base to build future
discussions on.
With my Matplotlib and h5py hats on, I like the discussion about how down
stream projects need to work out their issues with the support of the N
/ twice, the
browser helpfully added (1) to the name, when I when to upload everything
twine got half way through and failed out on that file. I thought it had
done everything else, but it had actually only done everything up to that
file.
On Tue, Sep 18, 2018 at 8:43 PM Thomas Caswell wrote:
> Fo
Folks,
Happy to announce Matplotlib 3.0.0!
This is the first version of Matplotlib to only support Python 3.
If you need Python 2.7 support the 2.2.x LTS series will continue to
receive critical bug-fixes until 2020.
Highlights of this release include:
- GUI backend is selected at run-time ba
Yes, meant IntFlag :sheep:
On Sat, Mar 17, 2018 at 6:02 PM Hameer Abbasi
wrote:
>
> It would be nice if there was an IntEnum [1] that was taken is an input to
> `np.asarrayish` and `np.isarrayish` to require a combination of the groups
> of attributes/methods/semantics.
>
>
> Don’t you mean IntF
It would be nice if there was an IntEnum [1] that was taken is an input to
`np.asarrayish` and `np.isarrayish` to require a combination of the groups
of attributes/methods/semantics.
Tom
[1] https://docs.python.org/3/library/enum.html#intenum
On Sat, Mar 10, 2018 at 7:14 PM Marten van Kerkwijk <
Yes I like the name.
The primary use-case for Matplotlib is that our `hist` method can take in a
list of arrays and produces N histograms in one shot. Currently with 'auto'
we only use the first data set to sort out what the bins should be and then
re-use those for the rest of the data sets. This
As commented in the OP, this would be very useful for Matplotlib.
Tom
On Fri, Mar 9, 2018 at 1:42 PM Kirit Thadaka
wrote:
> Hi!
>
> I've created a PR to add a function called "histogram_bin_edges" which
> will allow a user to calculate the bins used by the histogram for some data
> without requ
This has recently been a major point point for Matplotlib for the
implementation of string-categoricals as well.
Having numpy go to object or fail on `np.asarray([1, 2, 'foo'])` would make
things much easier for us.
Tom
On Fri, Feb 9, 2018 at 2:22 AM Stephan Hoyer wrote:
> On Thu, Feb 8, 2018
I have been building numpy master with CPython master but am also using
cython master.
My not-pretty script for doing this is:
#! /usr/bin/bash
set -e
TARGET_ENV=bleeding
OSPATH=~/source/other_source/
pushd $OSPATH/cpython/
git pull
git clean -xfd
./configure
make -j 9
./python -m venv --copies
Folks,
Happy to announce Matplotlib 2.1.1
This is primarily a bug fix release, see
https://github.com/matplotlib/matplotlib/releases/tag/v2.1.1 for details.
The next planned release is a 2.2 feature release in January/February
2018.
Thank you to everyone who worked on this release!
Tom
___
I am in very supportive of this plan.
For Matplotlib the intention is to do a mpl2.2LTS early 2018 and a mpl3.0
(no major API breaks other than dropping py2 support) summer 2018 with the
same meaning of LTS.
I also had thought about bumping the minimum numpy version of Matplotlib to
the first py3
We are happy to announce the release of Matplotlib 2.1. This is the second
minor release in the Matplotlib 2.x series and the first release with major
new features since 1.5.
This release contains approximately 2 years worth of work by 275
contributors
across over 950 pull requests. Highlights fr
It seems major versions are in the air!
For matplotlib 2.0 we put together
http://matplotlib.org/users/dflt_style_changes.html for the style changes
which shows the new behavior, the old behavior, and how to get the old
behavior back.
Tom
On Sun, Sep 17, 2017 at 10:48 AM Ilhan Polat wrote:
>
Going with option 2 is probably the best option so that you can use pytest
fixtures and parameterization.
Might be worth looking at how Matplotlib re-arranged things on our master
branch to maintain back-compatibility with nose-specific tools that were
used by down-stream projects.
Tom
On Tue, J
Are you tied to ASCII files? HDF5 (via h5py or pytables) might be a
better storage format for what you are describing.
Tom
On Wed, Jul 5, 2017 at 8:42 AM wrote:
> Dear all
>
>
> I’m sorry if my question is too basic (not fully in relation to Numpy –
> while it is to build matrices and to work
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