The initial stage of the NumPy community survey project in partnership with
the students and faculty from the Master’s program in Survey Methodology at
the University of Michigan and the University of Maryland has been
Currently, we are looking for a volunteer to help with the back translation
of the Hindi version of the survey questionnaire (Hindi into English). If
you are available, or you know someone who would be interested to help,
please leave a comment here: https://github.com/numpy/numpy-surveys/issues/1
Every good wish,
On behalf of the NumPy team I am pleased to announce that
NumPy 1.19.0rc2 has been released. This NumPy release supports Python
3.6-3.8 and is marked by the removal of much technical debt: support for
Python 2 has been removed, many deprecations have been expired, and
documentation has been improved. The polishing of the random module
continues apace with bug fixes and better usability from Cython. Perhaps
the most interesting thing for users will be the availability of wheels for
aarch64 and PyPY.
Downstream developers should use Cython >= 0.29.16 for Python 3.8 support
and OpenBLAS >= 3.7 to avoid wrong results on the Skylake architecture. The
NumPy Wheels for this release can be downloaded from PyPI
<https://pypi.org/project/numpy/1.19.0rc2/>, source archives and release
notes are available from Github
A total of 124 people contributed to this release. People with a "+" by
names contributed a patch for the first time.
- Alex Henrie
- Alexandre de Siqueira +
- Andras Deak
- Andrea Sangalli +
- Andreas Klöckner +
- Andrei Shirobokov +
- Anirudh Subramanian +
- Anne Bonner
- Anton Ritter-Gogerly +
- Benjamin Trendelkamp-Schroer +
- Bharat Raghunathan
- Brandt Bucher +
- Brian Wignall
- Bui Duc Minh +
- Changqing Li +
- Charles Harris
- Chris Barker
- Chris Holland +
- Christian Kastner +
- Chunlin +
- Chunlin Fang +
- Damien Caliste +
- Dan Allan
- Daniel Hrisca
- Daniel Povey +
- Dustan Levenstein +
- Emmanuelle Gouillart +
- Eric Larson
- Eric M. Bray
- Eric Mariasis +
- Eric Wieser
- Erik Welch +
- Fabio Zeiser +
- Gabriel Gerlero +
- Ganesh Kathiresan +
- Gengxin Xie +
- Guilherme Leobas
- Guillaume Peillex +
- Hameer Abbasi
- Hao Jin +
- Harshal Prakash Patankar +
- Heshy Roskes +
- Himanshu Garg +
- Huon Wilson +
- John Han +
- John Kirkham
- Jon Dufresne
- Jon Morris +
- Josh Wilson
- Justus Magin
- Kai Striega
- Kerem Hallaç +
- Kevin Sheppard
- Kirill Zinovjev +
- Marcin Podhajski +
- Mark Harfouche
- Marten van Kerkwijk
- Martin Michlmayr +
- Masashi Kishimoto +
- Mathieu Lamarre
- Matt Hancock +
- MatteoRaso +
- Matthew Harrigan
- Matthias Bussonnier
- Matti Picus
- Max Balandat +
- Maximilian Konrad +
- Maxwell Aladago
- Maxwell Bileschi +
- Melissa Weber Mendonça +
- Michael Felt
- Mike Taves
- Nico Schlömer
- Pan Jan +
- Paul Rougieux +
- Pauli Virtanen
- Peter Andreas Entschev
- Petre-Flaviu Gostin +
- Pierre de Buyl
- Piotr Gaiński +
- Przemyslaw Bartosik +
- Raghuveer Devulapalli
- Rakesh Vasudevan +
- Ralf Gommers
- RenaRuirui +
- Roman Yurchak
- Ross Barnowski +
- Ryan +
- Ryan Soklaski
- Sanjeev Kumar +
- SanthoshBala18 +
- Sayed Adel +
- Sebastian Berg
- Seth Troisi
- Sha Liu +
- Siba Smarak Panigrahi +
- Simon Gasse +
- Stephan Hoyer
- Steve Dower +
- Thomas A Caswell
- Till Hoffmann +
- Tim Hoffmann
- Tina Oberoi +
- Tirth Patel
- Tyler Reddy
- Warren Weckesser
- Wojciech Rzadkowski +
- Xavier Thomas +
- Yilin LI +
- Zac Hatfield-Dodds +
- Zé Vinícius +
- @Adam +
- @Anthony +
- @Jim +
- @bartosz-grabowski +
- @dojafrat +
- @gamboon +
- @jfbu +
- @keremh +
- @mayeut +
- @ndunnewind +
- @nglinh +
- @shreepads +
- @sslivkoff +
Dear numpy community,
My apologies for repeated in-list and cross-list posts!
I'd like to remind everybody that the 2020 John Hunter Excellence in
Plotting Contest submission deadline is June 01 -- only a few days away. We
welcome and look forward to your submissions!
In memory of John Hunter, we are pleased to announce the John Hunter
Excellence in Plotting Contest for 2020. This open competition aims to
highlight the importance of data visualization to scientific progress and
showcase the capabilities of open source software.
Participants are invited to submit scientific plots to be judged by a
panel. The winning entries will be announced and displayed at SciPy 2020 or
announced in the John Hunter Excellence in Plotting Contest website and
John Hunter’s family are graciously sponsoring cash prizes for the winners
in the following amounts:
1st prize: $1000
2nd prize: $750
3rd prize: $500
Entries must be submitted by June 1st to the form at
Winners will be announced at Scipy 2020 or publicly on the John Hunter
Excellence in Plotting Contest website and youtube channel
Participants do not need to attend the Scipy conference.
Entries may take the definition of “visualization” rather broadly.
Entries may be, for example, a traditional printed plot, an interactive
visualization for the web, a dashboard, or an animation.
Source code for the plot must be provided, in the form of Python code
and/or a Jupyter notebook, along with a rendering of the plot in a widely
used format. The rendering may be, for example, PDF for print, standalone
original data can not be shared for reasons of size or licensing, "fake"
data may be substituted, along with an image of the plot using real data.
Each entry must include a 300-500 word abstract describing the plot and
its importance for a general scientific audience.
Entries will be judged on their clarity, innovation and aesthetics, but
most importantly for their effectiveness in communicating a real-world
problem. Entrants are encouraged to submit plots that were used during the
course of research or work, rather than merely being hypothetical.
SciPy and the John Hunter Excellence in Plotting Contest organizers
reserves the right to display any and all entries, whether prize-winning or
not, at the conference, use in any materials or on its website, with
attribution to the original author(s).
Past entries can be found at https://jhepc.github.io/
Questions regarding the contest can be sent to jhepc.organizers(a)gmail.com
John Hunter Excellence in Plotting Contest Co-Chairs
This is Ryan Cooper (ME professor at University of Connecticut). I've been using Numpy in my mechanical engineering courses for years now, and I'd like to build resources for newcomers to Numpy.
Here is my proposed contribution:
Advise engineering students here at UConn to build How-to notebooks for Numpy applications. This would give the students some great experience communicating concepts and procedures to a broader community and it would help future users see how to use Numpy in different applications.
Some How-to's that I had in mind would be:
* Saving and loading Numpy arrays
* Doing fast fourier transform (FFT) on time-series data to find natural frequencies
* Solving linear sets of equations for circuits or another linear system with linear algebra
* using eigenvalues for natural frequency calculations
I'm open to other suggestions. These are some of the applications that I have current students doing in engineering work.
My question is: Would these How-to's be appopriate for the "Numpy Tutorials" (https://github.com/numpy/numpy-tutorials) repo?
My personal opinion is that How-to's are easier to organize and curate (for Numpy) and easier to write (for students).
Ryan C. Cooper, Ph. D.
University of Connecticut
Mechanical Engineering Department
Engineering II, room 314
191 Auditorium rd
Storrs, CT 06269
just curious, has anyone reservations about extending the ndarray
struct (and the void scalar one)?
The reason is that, I am starting to dislike the way we handle the
Due to issues with backward compatibility, we cannot use the "right"
way to free the buffer information. Because of that, the way we solve
it is by storing lists of pointers in a dictionary...
To me this seems a bit complicating, and is annoying since it adds a
dictionary lookup overhead to every single array deletion (and
inserting for every buffer creation). Also, it looks a bit like a
memory leak in some cases (although that probably only annoys me and
only when running valgrind).
It seems that it would be much simpler to tag the buffer-info on to the
array object itself. Which, however, would require extending the array
object by a single pointer .
Extending is in theory an ABI break if anyone subclasses ndarray from C
(extending the struct) and does not very carefully anticipate the
possibility. I am not even sure we support that, but its hard to be
 The size difference should not matter IMO, and with cythons
memoryviews buffers are not an uncommon feature in any case, for the
void scalar it is a bit bigger, but they are also very rare.
(I thought of using weak references, but the CPython API seems not very
fleshed out, or at least not documented, so not sure about that).
The NumPy web team is excited to announce the launch of the newly
redesigned numpy.org. To transform the website into a comprehensive, yet
user-centric, resource of all things NumPy was a primary focus of this
months-long effort. We thank Joe LaChance, Ralf Gommers, Shaloo Shalini,
Shekhar Prasad Rajak, Ross Barnowski, and Mars Lee for their extensive
contributions to the project.
The new site features a curated collection of NumPy related educational
resources for every user level, an overview of the entire Python scientific
computing ecosystem, and several case studies highlighting the importance
of the library to the many advances in scientific research as well as the
industry in recent years. The “Install” and “Get Help” pages offer advice
on how to find answers to installation and usage questions, while those who
are looking to connect with others within our large and diverse community
will find the “Community” page very helpful.
The new website will be updated on a regular basis with news about the
NumPy project development milestones, community initiatives and events.
Visitors are encouraged to explore the website and sign up for the
Next, the NumPy web team will focus on updating graphics and project
identity (a new logo is coming!), adding an installation widget and
translations, better integrating the project documentation via the new
Sphinx theme, and improving the interactive terminal experience. Also, we
are looking to expand our portfolio of case studies and would appreciate
any assistance in this matter.
NumPy web team
There will be a NumPy Community meeting Wednesday May 27th at 1pm
Pacific Time (20:00 UTC). Everyone is invited and encouraged to join in
and edit the work-in-progress meeting topics and notes:
Why does numpy produce a runtime warning (invalid value encountered in log)
when taking the log of a negative number? I noticed that if you coerce the
argument to complex by adding 0j to the negative number, the expected
result is produced (i.e. ln(-1) = pi*i).
I was surprised I couldn't find a discussion on this, as I would have
expected others to have come across this before. Packages like Matlab
handle negative numbers automatically by doing the complex conversion.