Mailman 3 March 2020 - NumPy-Discussion

Study on annotating implementation and design choices, and of technical debt
by Fiorella Zampetti March 17, 2020

March 17, 2020

Dear all, As software engineering research teams at the University of Sannio (Italy) and Eindhoven University of Technology (The Netherlands) we are interested in investigating the protocol used by developers while they have to annotate implementation and design choices during their normal development activities. More specifically, we are looking at whether, where and what kind of annotations developers usually use trying to be focused more on those annotations mainly aimed at highlighting that the code is not in the right shape (e.g., comments for annotating delayed or intended work activities such as TODO, FIXME, hack, workaround, etc). In the latter case, we are looking at what is the content of the above annotations, as well as how they usually behave while evolving the code that has been previously annotated. When answering the survey, in case your annotation practices are different in different open source projects you may contribute, please refer to how you behave for the projects where you have been contacted. Filling out the survey will take about 5 minutes. Please note that your identity and personal data will not be disclosed, while we plan to use the aggregated results and anonymized responses as part of a scientific publication. If you have any questions about the questionnaire or our research, please do not hesitate to contact us. You can find the survey link here: https://forms.gle/NQULdWRVvXYeMc1r6 Thanks and regards, Fiorella Zampetti (fzampetti(a)unisannio.it) Gianmarco Fucci (gianmarcofucci94(a)gmail.com) Alexander Serebrenik (a.serebrenik(a)tue.nl) Massimiliano Di Penta (dipenta(a)unisannio.it)

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Announcing the 2020 John Hunter Excellence in Plotting Contest
by Madicken Munk March 17, 2020

March 17, 2020

Dear all, 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 youtube channel. 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 https://forms.gle/SrexmkDwiAmDc7ej7 - Winners will be announced at Scipy 2020 in Austin, TX 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 HTML and Javascript for an interactive plot, or MPEG-4 for a video. If the 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 Madicken Munk Nelle Varoquaux

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Opportunities for a NumPy sprint in Japan
by David Cournapeau March 17, 2020

March 17, 2020

Hi there, My current employer is organizing regular "hack weeks" where engineers can work on the projects of their choice. My team is using a lot of pydata tools, including numpy, so contributing to NumPy would be natural. Before I decide to add NumPy as a project, I want to make sure it does not create more burden for the maintainers, the goal is to help the project, and for my team's members to help them contributing to OSS in "proper way". I would have time to prepare the hack week, making sure we prepare good PRs, and even use this time to actually review existing PRs myself. While I have been away from the project for a long time, I should still be able to review code, help my team building / testing / debugging, etc. Does that sound useful ? The first hack week would be held from 23th to 27th March, in Tokyo. Everybody would be remote because of the coronavirus, so except for time difference, if it makes sense, people outside of my employer could join. regards, David

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Documentation Team Meetings - all are welcome!
by Melissa Mendonça March 15, 2020

March 15, 2020

Hello all, As part of NumPy's recent focus on documentation writing and improvement (see NEP 44), we are proposing a regular meeting for the Documentation Team to discuss possible content, ideas and general planning. A small group had been participating in these meetings (which started as part of the Google Season of Docs project) but the idea is to recruit more people who might be interested in documentation writing and the creation of educational materials using NumPy. For now, the meetings will take place every three weeks, on mondays 3PM UTC. If you wish to join on Zoom, you need to use this link https://zoom.us/j/420005230 Here's the permanent hackmd document with the meeting notes: https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg <https://www.google.com/url?q=https%3A%2F%2Fhackmd.io%2FoB_boakvRqKR-_2jRV-Q…> Hope to see you around! - Melissa

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Handle type convertion in C API
by Benoit Gschwind March 11, 2020

March 11, 2020

Hello, I writing a python binding of one of our library. The binding intend to vectorize the function call. for exemple: double foo(double, double) will be bound to a python: <numpy.array of double> module.foo(<numpy.array>, <numpy.array>) and the function foo will be called like : for (int i = 0; i < size; ++i) outarr[i] = foo(inarr0[i], inarr[1]); My question is about how can I handle type conversion of input array, preferably in efficient manner, given that each input array may require different input type. Currently I basically enforce the type and no type conversion is performed. But I would like relax it. I thought of several possibility starting from the obvious solution consisting on recasting in the inner loop that would give: for (int i = 0; i < size; ++i) if (inarr[i] need recast) in0 = recast(inarr[i]) else in0 = inarr[i] [... same for all inputs parameter ...] outarr[i] = foo(in0, in1, ...); This solution is memory efficient, but not actually computationally efficient. The second solution is to copy&recast the entire inputs arrays, but in that case it's not memory efficient. And my final thought is to mix the first and the second by chunking the second method, i.e. converting N input in a raw, then applying the function to them en so on until all the array is processed. Thus my questions are: - there is another way to do what I want? - there is an existing or recommended way to do it? And a side question, I use the PyArray_FROM_OTF, but I do not understand well it's semantic. If I pass a python list, it is converted to the desired type and requirement; when I pass a non-continuous array it is converted to the continuous one; but when I pass a numpy array of another type than the one specified I do not get the conversion. There is a function that do the conversion unconditionally? Did I missed something ? Thank you by advance for your help Best regards

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NumPy Development Meeting - Triage Focus
by Sebastian Berg March 10, 2020

March 10, 2020

Hi all, (Note that the US has switched to daylight saving time) Our bi-weekly triage-focused NumPy development meeting is tomorrow (Wednesday, Februrary 26) at 11 am 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 or simply discussed briefly. Just comment on it so we can label it, or add your PR/issue to this weeks topics for discussion. Best regards Sebastian

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NumPy Community Meeting Wednesday, March 4
by Sebastian Berg March 3, 2020

March 3, 2020

Hi all, There will be a NumPy Community meeting Wednesday March 4 at 11 am Pacific Time. Everyone is invited and encouraged to join in and edit the work-in-progress meeting topics and notes: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both Best wishes Sebastian

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Proposal to accept NEP #44: Restructuring the NumPy Documentation
by Melissa Mendonça March 2, 2020

March 2, 2020

Hi all, I am proposing the acceptance of NEP 44 - Restructuring the NumPy Documentation. https://numpy.org/neps/nep-0044-restructuring-numpy-docs.html There were some comments about reorganizing the text to make it clearer, and some rewording regarding Reference Guides, developer "under-the-hoods" documentation and the possible mechanism for community contributions in the form of new tutorials or how-tos. Overall I believe we have answered all comments and there were no other points of concern. If there are no substantive objections within 7 days from this email, then the NEP will be accepted; see NEP 0 for more details: see http://www.numpy.org/neps/nep-0000.html Thanks for the comments! Looking forward to start working on this :) -- Melissa Weber Mendonça

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