Mailman 3 June 2024 - NumPy-Discussion

ANN: numexpr 2.10.1 released!
by Francesc Alted June 20, 2024

June 20, 2024

========================= Announcing NumExpr 2.10.1 ========================= Hi everyone, NumExpr 2.10.1 continues to stabilize the support for NumPy 2.0.0. Also, the default number of 'safe' threads has been upgraded to 16 (instead of previous 8). Finally, preliminary support for Python 3.13; thanks to Karolina Surma. Project documentation is available at: http://numexpr.readthedocs.io/ Changes from 2.10.0 to 2.10.1 ----------------------------- - The default number of 'safe' threads has been upgraded to 16 (instead of previous 8). That means that if your CPU has > 16 cores, the default is to use 16. You can always override this with the "NUMEXPR_MAX_THREADS" environment variable. - NumPy 1.23 is now the minimum supported. - Preliminary support for Python 3.13. Thanks to Karolina Surma. - Fix tests on nthreads detection (closes: #479). Thanks to @avalentino. - The build process has been modernized and now uses the `pyproject.toml` file for more of the configuration options. What's Numexpr? --------------- Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. It has multi-threaded capabilities, as well as support for Intel's MKL (Math Kernel Library), which allows an extremely fast evaluation of transcendental functions (sin, cos, tan, exp, log...) while squeezing the last drop of performance out of your multi-core processors. Look here for a some benchmarks of numexpr using MKL: https://github.com/pydata/numexpr/wiki/NumexprMKL Its only dependency is NumPy (MKL is optional), so it works well as an easy-to-deploy, easy-to-use, computational engine for projects that don't want to adopt other solutions requiring more heavy dependencies. Where I can find Numexpr? ------------------------- The project is hosted at GitHub in: https://github.com/pydata/numexpr You can get the packages from PyPI as well (but not for RC releases): http://pypi.python.org/pypi/numexpr Documentation is hosted at: http://numexpr.readthedocs.io/en/latest/ Share your experience --------------------- Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy data!

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NumPy 2.0.0 released
by Charles R Harris June 17, 2024

June 17, 2024

Hi All On behalf of the NumPy team, I'm pleased to announce the release of NumPy 2.0.0rc2. NumPy 2.0.0 is the first major release since 2006. It is the result of 11 months of development since the last feature release and is the work of 198 contributors spread over 1041 pull requests. It contains a large number of exciting new features as well as changes to both the Python and C APIs. This major release includes breaking changes that could not happen in a regular minor (feature) release - including an ABI break, changes to type promotion rules, and API changes which may not have been emitting deprecation warnings in 1.26.x. Key documents related to how to adapt to changes in NumPy 2.0 include: - The release notes on Github <https://github.com/numpy/numpy/releases/tag/v2.0.0> - The numpy-2-migration-guide <https://numpy.org/devdocs/numpy_2_0_migration_guide.html> - The numpy 2.0-specific advice in for downstream package authors <https://numpy.org/devdocs/dev/depending_on_numpy.html> Highlights include: - A new variable-length string dtype, StringDType, and a new `numpy.strings` namespace with performant ufuncs for string operations. - Support for float32 and long double in all `numpy.fft` functions. - Support for the array API standard in the main numpy namespace. - MacOS Accelerate support and binary wheels for macOS >=14. - A new tracing and introspection API. - Performance improvements. - Python API improvements. - C API improvements. This release supports Python 3.9-3.12. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/2.0.0>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v2.0.0>. *Contributors* A total of 212 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @Algorithmist-Girl + - @DWesl - @Illviljan - @Searchingdays - @ellaella12 + - @liang3zy22 + - @matoro + - @mcp292 + - @mgunyho + - @msavinash + - @mykykh + - @pojaghi + - @pratiklp00 + - @stefan6419846 + - @undermyumbrella1 + - Aaron Meurer - Aditi Saluja + - Adrin Jalali + - Agriya Khetarpal + - Albert Steppi + - Alex Cabrera + - Alexander Grund - Andrea Bianchi + - Andreas Florath + - Andrew Ardill + - Andrew Ho + - Andrew Nelson - Andrey Rybakov + - Ankur Singh + - Anton Prosekin + - Antony Lee - Arun Kannawadi + - Bas van Beek - Ben Woodruff + - Bharat Raghunathan - Bhavya Alekhya + - Brandon Smith + - Brian Walshe + - Brigitta Sipőcz - Brock Mendel - Carl Meyer + - Charles Bousseau + - Charles Harris - Chris Sidebottom - Christian Lorentzen - Christian Veenhuis - Christoph Reiter - Christopher Sidebottom - Clément Robert - Cédric Hannotier - Cobalt Yang + - Gonçalo Bárias + - D.J. Ramones + - DanShatford + - Daniel Li + - Daniel Vanzo - Daval Parmar - Developer-Ecosystem-Engineering - Dhruv Rawat + - Dimitri Papadopoulos Orfanos - Edward E - Edward Yang + - Eisuke Kawashima + - Eliah Kagan + - Élie Goudout + - Elliott Sales de Andrade - Emil Olszewski + - Emily Hunt + - Éric Piel + - Eric Wieser - Eric Xie + - Even Rouault + - Evgeni Burovski - Filipe Laíns + - Francisco Sousa + - Ganesh Kathiresan - Gonçalo Bárias + - Gonzalo Tornaría + - Hans Meine - Heberto Mayorquin + - Heinz-Alexander Fuetterer + - Hood Chatham - Hugo van Kemenade - Ivan A. Melnikov + - Jacob M. Casey + - Jake Lishman + - Jake VanderPlas - James Oliver + - Jan Wassenberg + - Janukan Sivajeyan + - Johann Rohwer + - Johannes Kaisinger + - John Muradeli + - Joris Van den Bossche - Justus Magin - Jyn Spring 琴春 - Kai Striega - Kevin Sheppard - Kevin Wu + - Khawaja Junaid + - Kit Lee + - Kristian Minchev + - Kristoffer Pedersen + - Kuan-Wei Chiu + - Lane Votapka + - Larry Bradley - Leo Singer - Liang Yan + - Linus Sommer + - Logan Thomas - Lucas Colley + - Luiz Eduardo Amaral + - Lukas Geiger - Lysandros Nikolaou + - Maanas Arora + - Maharshi Basu + - Mahder Gebremedhin + - Marcel Bargull + - Marcel Loose + - Mark Mentovai + - Mark Ryan + - Marten van Kerkwijk - Mateusz Sokół - Matt Haberland - Matt Thompson + - Matthew Barber - Matthew Thompson + - Matthias Bussonnier - Matthias Koeppe - Matthias Schaufelberger + - Matti Picus - Maxwell Aladago - Maya Anderson + - Melissa Weber Mendonça - Meng Xiangzhuo + - Michael Kiffer - Miki Watanabe (渡邉美希) - Milan Curcic + - Miles Cranmer - Miro Hrončok + - Mohamed E. BRIKI + - Mohaned Qunaibit + - Mohit Kumar + - Muhammed Muhsin + - Mukulika Pahari - Munira Alduraibi + - Namami Shanker - Nathan Goldbaum - Nyakku Shigure + - Ola x Nilsson + - Olivier Mattelaer + - Olivier Grisel - Omid Rajaei - Pablo Losada + - Pamphile Roy - Paul Reece + - Pedro Kaj Kjellerup Nacht + - Peiyuan Liu + - Peter Hawkins - Pierre - Pieter Eendebak - Quentin Barthélemy + - Raghuveer Devulapalli - Ralf Gommers - Randy Eckenrode + - Raquel Braunschweig + - Richard Howe + - Robert Kern - Rohit Goswami - Romain Geissler + - Ronald van Elburg + - Ross Barnowski - Sam James + - Sam Van Kooten + - Samuel Albanie + - Sarah Wang + - Sarah Zwiep + - Sarah-Yifei-Wang + - Sarthak Dawar + - Sayantika Banik - Sayed Adel - Sean Cheah + - Sebastian Berg - Serge Guelton - Shalini Roy + - Shen Zhou - Shubhal Gupta + - Stefan van der Walt - Stefano Rivera + - Takumasa N. + - Taras Tsugrii - Thomas A Caswell - Thomas Grainger + - Thomas Li - Tim Hoffmann - Tim Paine + - Timo Röhling + - Trey Woodlief + - Tyler Reddy - Victor Tang + - Vladimir Fokow + - Warren Weckesser - Warrick Ball + - Will Ayd - William Andrea + - William Ayd + - Xiangyi Wang + - Yash Pethe + - Yuki K - Zach Brugh + - Zach Rottman + - Zolisa Bleki Cheers, Charles Harris

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ANN: DataLab v0.16
by Pierre Raybaut June 17, 2024

June 17, 2024

Hello everyone, We're thrilled to announce the release of DataLab v0.16! https://datalab-platform.com DataLab is an open-source platform for scientific and technical data processing and visualization, based on NumPy, SciPy, ... and Qt. It's extendable with plugins, and works seamlessly as a complementary tool with your IDE (e.g. Spyder, VSCode, ...) and Project Jupyter notebooks. The main idea behind DataLab is to propose in a single software not only a no-code solution for processing and visualizing signals and images, but also a **simple yet powerful self-consistent platform** that is highly extendable with plugins, macros or directly by remote-control (from your favorite IDE or Jupyter Notebook). So, with DataLab, you have the best of both worlds: no-code solution for quick data processing, and Python code solution for more advanced processing with your own Python scripts and libraries. 💥 New Features: - Major user interface overhaul: reorganized menus and toolbars, new icons, ... - New validation process for testing processing features from a mathematical point of view - Signal processing: offset correction, power spectrum, PSD, frequency filters, windowing, ... - Image processing: thresholding, intensity profile along a segment, ... More information on the new features and improvements can be found in the release notes: https://datalab-platform.com/en/contributing/changelog.html 💡 You have a project or a use case in mind? You want to contribute? We'd love to hear from you! So please, don't hesitate to contact us or to open an issue on our GitHub project for any request or question. Thank you for taking the time to read my announcement. Looking forward to your thoughts. Best, Pierre Raybaut

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Generate documentation for the 2.0.0 release
by Charles R Harris June 16, 2024

June 16, 2024

Hi All, Could someone running Python < 3.12 generate the documentation for the NumPy 2.0.0 release. My native Python is 3.12, which works fine except that there is no distutils. Trying to run the build under 3.11, after hard coding the Python version in the doc/Makefile, runs into various problems, and there are probably some subtle Python version mismatches buried in the scripts somewhere that I don't want to spend time chasing down at the moment. Chuck

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Next NumPy Newcomers' Hour - June 13th, 2023 at 12 PM UTC
by Ganesh Kathiresan June 10, 2024

June 10, 2024

Our next Newcomers' Hour will be held this Thursday, 13th, 2023 at 12 PM UTC, Stop by to ask questions, share your progress, celebrate success, or just to say hi. To add to the meeting agenda the topics you’d like to discuss, follow the link: https://hackmd.io/3f3otyyuTte3FU9y3QzsLg?both. Join the meeting via Zoom: https://us06web.zoom.us/j/82563808729?pwd=ZFU3Z2dMcXBGb05YemRsaGE1OW5nQT09. Thanks, Ganesh

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Unexpected return values for np.mod with x2=np.inf and similar
by jesse.livezey＠gmail.com June 10, 2024

June 10, 2024

Hi all, I ran into an odd edge-case with np.mod and was wondering if this is the expected behavior, and if so why. This is on a fresh install of python 3.10.14 with numpy 1.26.4 from conda-forge. >>> import numpy as np # I have a hard time coming up with a rationale for why 2 of these produce non-inf values and the other 2 produce inf values. >>> np.mod(1., np.inf) 1.0 >>> np.mod(1., -np.inf) -inf >>> np.mod(-1., -np.inf) -1.0 >>> np.mod(-1., np.inf) inf # these are possibly sensible although the signed zero pattern is unexpected to me. >>> np.mod(0., np.inf) 0.0 >>> np.mod(0., -np.inf) -0.0 >>> np.mod(-0., -np.inf) -0.0 >>> np.mod(-0., np.inf) 0.0 Any ideas why these are the return values? I had a hard time tracking down where in the numpy source np.mod was coming from. Jesse

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ENH: Adds cross2d to core and linalg (with API compatibility) #26640
by Ben Woodruff June 8, 2024

June 8, 2024

At the community meeting on Wednesday, we discussed adding `cross2d` as a new function, partly because of the deprecation of 2d arrays in `cross` (two issues are linked in the PR). Whether or not this is the right approach to take is something we want to have a bigger discussion about. One option discussed was adding both `cross2d` and `linalg.cross2d`. Another was just adding Array API compatible `linalg.cross2d`. Another was referring users to using `linalg.det` (though the return value is always floats which could be an issue). I volunteered to write the functions (partly as an exercise to learn the ins and outs of NumPy) and submitted the new functions as a PR. See https://github.com/numpy/numpy/pull/26640. I'm not offended at all if we decide on another route. We did discuss at the meeting that we need to provide some kind of alternative for people who use `cross` currently. One of the examples I updated for `cross` in the PR shows an option to pad 2D vectors and then use `cross`, though this will most likely be computationally much slower than `cross2d`.

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ENH: Add more default arguments to various functions
by Carlos Martin June 4, 2024

June 4, 2024

Suggestion: Add the following default arguments to the following functions: - https://numpy.org/doc/stable/reference/generated/numpy.zeros.html: shape=() - https://numpy.org/doc/stable/reference/generated/numpy.ones.html: shape=() - https://numpy.org/doc/stable/reference/generated/numpy.empty.html: shape=() - https://numpy.org/doc/stable/reference/generated/numpy.heaviside.html: x2=0.5 Feel free to add more examples.

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next Documentation team meeting + poll for future meeting times
by Mukulika Pahari June 3, 2024

June 3, 2024

Hi all, Our next Documentation Team meeting will happen on *Monday, May 20* at *11PM UTC*. ** Since we have requests to revisit the meeting time, please tell us your availability for future meetings here - https://www.when2meet.com/?25066561-WcODg ** All are welcome - you don't need to already be a contributor to join. If you have questions or are curious about what we're doing, we'll be happy to meet you! If you wish to join on Zoom, use this (updated) link: https://numfocus-org.zoom.us/j/85016474448?pwd=TWEvaWJ1SklyVEpwNXUrcHV1YmFJQ... Here's the permanent hackmd document with the meeting notes (still being updated): https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg Hope to see you around! Best wishes, Mukulika

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