Mailman 3 May 2022 - NumPy-Discussion

ENH: Support Random Unit Vector
by saroad2＠gmail.com May 17, 2022

May 17, 2022

### Proposed new feature or change: Description ======== Often you want to randomize a "direction" that doesn't have "size". This can be useful when: * You want to randomize the direction of an NPC walk developing in a 2D or 3D games, where its speed is a predefined constant. * You're developing particles simulation with all particles moving in random directions * etc. This random direction should be an `n`th dimensional unit vector which is randomize **uniformly** from the unit sphere. That … [View More]

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NumPy Development Meeting Wednesday - Triage Focus
by Sebastian Berg May 17, 2022

May 17, 2022

Hi all, Our bi-weekly triage-focused NumPy development meeting is Wednesday, May 18th at 16:00 UTC (9:00am 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 issues or PRs that you feel should be prioritized, discussed, or reviewed. A calendar to can be found at: https://scientific-python.org/calendars/ please make sure to not import the static `ics` but the url. Best regards Sebastian

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Interesting security project
by Charles R Harris May 14, 2022

May 14, 2022

Hi All, There is a project underway to secure open source software <https://venturebeat.com/2022/05/13/how-much-will-it-cost-to-secure-open-sou…>. This doesn't affect us (yet), but is of interest as it shows the growing importance of open source. Chuck

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Fixing/changing structured dtype casting safety, promotion, and comparisons
by Sebastian Berg May 11, 2022

May 11, 2022

Hi all, This was probably announced before, but I wanted to mention it again, with https://github.com/numpy/numpy/pull/19226 as the last step the casting safety, promotion, and comparisons of structured (void) dtypes will be updated to fix some bugs and fit better with changes that happened a few years ago already. The most interesting change is probably to comparisons: It is now possible to compare sturctured dtypes when included dtypes mismatch: arr1 = np.array([1, 2, 3], dtype="i,i") … [View More]

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[Feature Request] Add alias of np.concatenate as np.concat
by Iordanis Fostiropoulos May 10, 2022

May 10, 2022

In regard to Feature Request: https://github.com/numpy/numpy/issues/16469 It was suggested to sent to the mailing list. I think I can make a strong point as to why the support for this naming convention would make sense. Such as it would follow other frameworks that often work alongside numpy such as tensorflow. For backward compatibility, it can simply be an alias to np.concatenate I often convert portions of code from tf to np, it is as simple as changing the base module from tf to np. e.g. … [View More]

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NumPy community meeting – Wednesday, March 30th, 2022 at 18:00 (6 pm) UTC
by Inessa Pawson May 9, 2022

May 9, 2022

Our next NumPy community meeting is scheduled for Wednesday, March 30th at 18:00 (6 pm) UTC. Join us via Zoom: https://berkeley.zoom.us/j/762261535 As always, everyone is welcome and encouraged to attend. To add to the meeting agenda the topics you’d like to discuss, follow the link: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both Cheers, Inessa Inessa Pawson Contributor Experience Lead | NumPy

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Automatic formatters for only changed lines
by Trevor Gross May 8, 2022

May 8, 2022

Hey all, Matti pointed out to me that discussion of an autoformatter has come up before, with the decision that an entire codebase rewrite would be undesirable (ref: https://mail.python.org/pipermail/scipy-dev/2020-January/023927.html). As a result, tools/linter.py was added to only validate the changed lines. There is better support for autoformatters that only work on changed lines now, and I'd like to propose adding one. I already have a pre-commit demo implemented here, with an example … [View More]

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ndarray repr - put shape & type first
by Ilya Kamenshchikov May 7, 2022

May 7, 2022

Hello, I wanted to discuss a pain point I've experienced while debugging numpy code. When dealing with e.g. transformed image arrays or other non-trivial ndarrays in debugger, I'm swamped by a bunch of numbers in their repr that don't help me at all. What I really care about is *shape and dtype*, as they are essentially what distinguishes complete type of numpy arrays. Example of not helpful output: ``` array([[[0.49113064, 0.42102904, 0.62108876], [0.25435884, 0.18665439, 0.53790145],… [View More]

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Numpy-related jobs, grants, etc
by Renato Fabbri May 4, 2022

May 4, 2022

This is not only for me, but a question for the community in general. Do we have an open knowledge base of budget (interested companies or individuals, public funding) for developing numpy-related packages? Explaining a bit with a specific case... In the last few years, I have many times thought about the possibility of working with Numpy: finding payment for developing libraries using Numpy or even Numpy internals. Especially, I have written a music python library (called 'music' on PyPI). It … [View More]

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Discussion: History & Possible Deprecation/Removal of numpy.linalg.{eig(), eigvals()}?
by Leo Fang May 3, 2022

May 3, 2022

Hi, I am catching up with an assigned task that I slipped. I am wondering a few things about the numpy.linalg.eig() API (eigvals() is also included in this discussion, but for simplicity let's focus on eig()). AFAIU the purpose of eig() is for handling general eigen-systems which have left and right eigenvectors (that could differ beyond transpose/conjugate). For this, I have two questions: 1. What's the history of NumPy adding this eig() routine? My guess would be NumPy added it because … [View More]

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Types in pure Python sources
by Sergei Lebedev May 3, 2022

May 3, 2022

Hi everyone, I've noticed that NumPy currently users separate type stub files for specifying types for both pure Python and native modules. For example the (untyped) implementation of np.core._asarray is in [1], but the types are in [2]. This works fine for type checkers, and if anything, improves type checking performance, because type stubs are much smaller than their pure Python counterparts. It does, however, create problems for IDEs which now have to either work with untyped APIs or … [View More]

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NumPy Development Meeting Wednesday - Triage Focus
by Sebastian Berg May 3, 2022

May 3, 2022

Hi all, Our bi-weekly triage-focused NumPy development meeting is Wednesday, May 4th at 16:00 UTC (9:00am 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 issues or PRs that you feel should be prioritized, discussed, or reviewed. A calendar to can be found at: https://scientific-python.org/calendars/ please make sure to not import the static `ics` but the url. Best regards Sebastian

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