Mailman 3 April 2023 - NumPy-Discussion

Introduction and Inquiry about GSOD Project
by Disha Jain 13 Apr '23

13 Apr '23

Dear Mam/Sir, I hope this email finds you well. My name is Disha Jain, and I am a React developer and blogger based in India. I recently came across the Google Season of Docs (GSOD) project, and I was immediately intrigued by the great work your organization is doing in improving open-source documentation. As someone who is passionate about contributing to open-source projects, I am writing to you today to introduce myself and inquire about the possibility of participating in the GSOD program with your organization. I have had experience in writing technical blog on React, and I believe that my skills and expertise would be a valuable addition to your team. I am reaching out to you today because I would like to learn more about your project and your expectations from a GSOD participant. I understand that you must receive a lot of emails, so I would appreciate it if you could take a few minutes to respond to my inquiry. I have taken the time to look through your project's website and read through some of your existing documentation. I find your project's approach to serve more content to Honda community very innovative, and I would love to contribute to this aspect of your work. Please let me know if there is anything else I can do to learn more about your project, such as reading specific documentation, attending an online meeting, or talking to some members of your team. Below I am adding my link- https://disha.hashnode.dev/ <https://disha.hashnode.dev/> My Linkedin id- https://www.linkedin.com/in/disha-jain-90a554229 <https://www.linkedin.com/in/disha-jain-90a554229> Thank you for your time, and I look forward to hearing back from you. Best regards, Disha Jain

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Documentation team meeting - Monday 10 April at 4 PM UTC
by Mukulika Pahari 10 Apr '23

10 Apr '23

Hi all! Our next Documentation Team meeting will happen on *Monday, April 10* at ***4PM UTC***. We now alternate the meeting times to be a bit more inclusive. This means that we'll have a meeting at 12pm UTC every 28 days, and a meeting at 4pm UTC every 28 days. 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! * You can also visit https://scientific-python.org/calendars to add the NumPy community calendar as an .ics file to your preferred calendar manager. * Best wishes, Mukulika

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NumPy 2.0 meeting - Monday, April 3rd, 3 - 7pm UTC
by Inessa Pawson 08 Apr '23

08 Apr '23

Hi, everyone! The preparation for NumPy 2.0 release is currently underway. The NumPy project leadership would like to invite you all to join us on Monday, April 3rd, 3 - 7pm UTC for the meeting where the NumPy maintainers will present the scope of the planned work for this release and hold in-depth discussions on every proposed feature. For details of the meeting agenda, visit: https://docs.google.com/document/d/1vNDBlnVCJM-Nv7xF02Re4qk_5rR9uAUi0ih6K3b…. Please keep in mind that it hasn’t been finalized yet. Join us via Zoom: https://numfocus-org.zoom.us/j/87080449579?pwd=dmt5dktCT2l1NG5ZNGFvb3dKdUNI… . -- Cheers, Inessa Inessa Pawson Contributor Experience Lead | NumPy https://numpy.org/ GitHub: inessapawson

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ufunc should warn when argument `where` is specified and `out` is default None.
by p.j.lenihan1＠leeds.ac.uk 06 Apr '23

06 Apr '23

My argument is that `where` makes sense unless `out` is default `None`, in which case it simply obscures the creation of a partially uninitialised array. The casual numpy user accessing through the public API likely only wants garbage values if they have explicitly asked for them using `empty_like`. If they have decided not to pass `out`, it probably means they expect a partially transformed copy of the input array and have overlooked the note in the docstring. Example: User creates a function that log transforms values where log is defined . ``` def safe_log(val, out): return np.log(val, where=np.greater(val, 0), out=out) ``` User suddenly decides that they don't want to specify `out` every time, making `safe_log` unsafe. ``` def safe_log(val, out=None): return np.log(val, where=np.greater(val, 0), out=out) ```

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Fortran-style support in ctypeslib.as_array()?
by monte.b.hoover＠gmail.com 06 Apr '23

06 Apr '23

Would it be okay to add an argument to ctypeslib.as_array() that allowed specifying that a pointer references column-major memory layout? Currently if we use ndarray.ctypes.data_as() to get a pointer to a Fortran-ordered array and then we use ctypeslib.as_array() to read that same array back in, we don't have a way of doing the round trip correctly. For example: >>> import ctypes as ct >>> a = np.arange(6).reshape(2,3) >>> a = np.asfortranarray(a) >>> a array([[0, 1, 2], [3, 4, 5]]) >>> a_ptr = a.ctypes.data_as(ct.POINTER(ct.c_int)) >>> b = np.ctypeslib.as_array(a_ptr, shape=a.shape) >>> b array([[0, 3, 1], [4, 2, 5]]) The proposed function signature would be something like: numpy.ctypeslib.as_array(obj, shape=None, order='None'), with order{‘C’, ‘F’}, optional Thanks, Monte

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How to fix this problem? np.arange(0,20.01,0.01)
by siderique＠gmail.com 04 Apr '23

04 Apr '23

The last element of "np.arange(0,20.01,0.01)" is 20.01 in my python result. Is this numpy error ?

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