Mailman 3 May 2020 - NumPy-Discussion

mixed mode arithmetic
by Neal Becker July 11, 2023

July 11, 2023

I've been browsing the numpy source. I'm wondering about mixed-mode arithmetic on arrays. I believe the way numpy handles this is that it never does mixed arithmetic, but instead converts arrays to a common type. Arguably, that might be efficient for a mix of say, double and float. Maybe not. But for a mix of complex and a scalar type (say, CDouble * Double), it's clearly suboptimal in efficiency. So, do I understand this correctly? If so, is that something we should improve?

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Invalid value encoutered : how to prevent numpy.where to do this?
by Eric Emsellem Feb. 18, 2023

Feb. 18, 2023

Dear all, I have a code using lots of "numpy.where" to make some constrained calculations as in: data = arange(10) result = np.where(data == 0, 0., 1./data) # or data1 = arange(10) data2 = arange(10)+1.0 result = np.where(data1 > data2, np.sqrt(data1-data2), np.sqrt(data2-data2)) which then produces warnings like: /usr/bin/ipython:1: RuntimeWarning: invalid value encountered in sqrt or for the first example: /usr/bin/ipython:1: RuntimeWarning: divide by zero encountered in divide How … [View More]

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Re: [Numpy-discussion] example reading binary Fortran file
by Neil Martinsen-Burrell July 22, 2021

July 22, 2021

David Froger <david.froger.info <at> gmail.com> writes: > Hy,My question is about reading Fortran binary file (oh no this question > again...) I've posted this before, but I finally got it cleaned up for the Cookbook. For this purpose I use a subclass of file that has methods for reading unformatted Fortran data. See http://www.scipy.org/Cookbook/FortranIO/FortranFile. I'd gladly see this in numpy or scipy somewhere, but I'm not sure where it belongs. > program … [View More]makeArray > implicit none > integer,parameter:: nx=10,ny=20 > real(4),dimension(nx,ny):: ux,uy,p > integer :: i,j > open(11,file='uxuyp.bin',form='unformatted') > do i = 1,nx > do j = 1,ny > ux(i,j) = real(i*j) > uy(i,j) = real(i)/real(j) > p (i,j) = real(i) + real(j) > enddo > enddo > write(11) ux,uy > write(11) p > close(11) > end program makeArray When I run the above program compiled with gfortran on my Intel Mac, I can read it back with:: >>> import numpy as np >>> from fortranfile import FortranFile >>> f=FortranFile('uxuyp.bin', endian='<') >>> uxuy = f.readReals(prec='f') # 'f' for default reals >>> len(uxuy) 400 >>> ux = np.array(uxuy[:200]).reshape((20,10)).T >>> uy = np.array(uxuy[200:]).reshape((20,10)).T >>> p = f.readReals('f').reshape((20,10)).T >>> ux array([[ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20.], [ 2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24., 26., 28., 30., 32., 34., 36., 38., 40.], [ 3., 6., 9., 12., 15., 18., 21., 24., 27., 30., 33., 36., 39., 42., 45., 48., 51., 54., 57., 60.], [ 4., 8., 12., 16., 20., 24., 28., 32., 36., 40., 44., 48., 52., 56., 60., 64., 68., 72., 76., 80.], [ 5., 10., 15., 20., 25., 30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80., 85., 90., 95., 100.], [ 6., 12., 18., 24., 30., 36., 42., 48., 54., 60., 66., 72., 78., 84., 90., 96., 102., 108., 114., 120.], [ 7.,Proxy-Connection: keep-alive Cache-Control: max-age=0 14., 21., 28., 35., 42., 49., 56., 63., 70., 77., 84., 91., 98., 105., 112., 119., 126., 133., 140.], [ 8., 16., 24., 32., 40., 48., 56., 64., 72., 80., 88., 96., 104., 112., 120., 128., 136., 144., 152., 160.], [ 9., 18., 27., 36., 45., 54., 63., 72., 81., 90., 99., 108., 117., 126., 135., 144., 153., 162., 171., 180.], [ 10., 20., 30., 40., 50., 60., 70., 80., 90., 100., 110., 120., 130., 140., 150., 160., 170., 180., 190., 200.]]) >>> uy array([[ 1. , 0.5 , 0.33333334, 0.25 , 0.2 , 0.16666667, 0.14285715, 0.125 , 0.11111111, 0.1 , 0.09090909, 0.08333334, 0.07692308, 0.07142857, 0.06666667, 0.0625 , 0.05882353, 0.05555556, 0.05263158, 0.05 ], [ 2. , 1. , 0.66666669, 0.5 , 0.40000001, 0.33333334, 0.2857143 , 0.25 , 0.22222222, 0.2 , 0.18181819, 0.16666667, 0.15384616, 0.14285715, 0.13333334, 0.125 , 0.11764706, 0.11111111, 0.10526316, 0.1 ], [ 3. , 1.5 , 1. , 0.75 , 0.60000002, 0.5 , 0.42857143, 0.375 , 0.33333334, 0.30000001, 0.27272728, 0.25 , 0.23076923, 0.21428572, 0.2 , 0.1875 , 0.17647059, 0.16666667, 0.15789473, 0.15000001], [ 4. , 2. , 1.33333337, 1. , 0.80000001, 0.66666669, 0.5714286 , 0.5 , 0.44444445, 0.40000001, 0.36363637, 0.33333334, 0.30769232, 0.2857143 , 0.26666668, 0.25 , 0.23529412, 0.22222222, 0.21052632, 0.2 ], [ 5. , 2.5 , 1.66666663, 1.25 , 1. , 0.83333331, 0.71428573, 0.625 , 0.55555558, 0.5 , 0.45454547, 0.41666666, 0.38461539, 0.35714287, 0.33333334, 0.3125 , 0.29411766, 0.27777779, 0.2631579 , 0.25 ], [ 6. , 3. , 2. , 1.5 , 1.20000005, 1. , 0.85714287, 0.75 , 0.66666669, 0.60000002, 0.54545456, 0.5 , 0.46153846, 0.42857143, 0.40000001, 0.375 , 0.35294119, 0.33333334, 0.31578946, 0.30000001], [ 7. , 3.5 , 2.33333325, 1.75 , 1.39999998, 1.16666663, 1. , 0.875 , 0.77777779, 0.69999999, 0.63636363, 0.58333331, 0.53846157, 0.5 , 0.46666667, 0.4375 , 0.41176471, 0.3888889 , 0.36842105, 0.34999999], [ 8. , 4. , 2.66666675, 2. , 1.60000002, 1.33333337, 1.14285719, 1. , 0.8888889 , 0.80000001, 0.72727275, 0.66666669, 0.61538464, 0.5714286 , 0.53333336, 0.5 , 0.47058824, 0.44444445, 0.42105263, 0.40000001], [ 9. , 4.5 , 3. , 2.25 , 1.79999995, 1.5 , 1.28571427, 1.125 , 1. , 0.89999998, 0.81818181, 0.75 , 0.69230771, 0.64285713, 0.60000002, 0.5625 , 0.52941179, 0.5 , 0.47368422, 0.44999999], [ 10. , 5. , 3.33333325, 2.5 , 2. , 1.66666663, 1.42857146, 1.25 , 1.11111116, 1. , 0.90909094, 0.83333331, 0.76923078, 0.71428573, 0.66666669, 0.625 , 0.58823532, 0.55555558, 0.52631581, 0.5 ]]) >>> p array([[ 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21.], [ 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22.], [ 4., 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23.], [ 5., 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24.], [ 6., 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25.], [ 7., 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26.], [ 8., 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27.], [ 9., 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.], [ 10., 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29.], [ 11., 12., 13., 14., 15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30.]]) Note that you have to provide the shape information for ux and uy because fortran writes them together as a stream of 400 numbers. -Neil [View Less]

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help translating Hindi into English
by Inessa Pawson June 18, 2020

June 18, 2020

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 successfully completed. 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: … [View More]

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(no subject)
by Charles R Harris June 3, 2020

June 3, 2020

Hi All, 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 … [View More]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 <https://github.com/numpy/numpy/releases/tag/v1.19.0rc2>. *Contributors* A total of 124 people contributed to this release. People with a "+" by their 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 + Cheers, Charles Harris [View Less]

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Reminder: June 01 Deadline for the 2020 John Hunter Excellence in Plotting contest!
by Madicken Munk June 1, 2020

June 1, 2020

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 … [View More]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 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 [View Less]

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Numpy Documentation: How-to content
by Cooper, Ryan May 31, 2020

May 31, 2020

Greetings, 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 … [View More]

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ANN: SciPy 1.5.0rc1 -- please test
by Tyler Reddy May 30, 2020

May 30, 2020

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Hi all, On behalf of the SciPy development team I'm pleased to announce the release candidate SciPy 1.5.0rc1. Please help us test this pre-release. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.5.0rc1 <https://github.com/scipy/scipy/releases/tag/v1.4.0rc1> One of a few ways to install the release candidate with pip: pip install scipy==1.5.0rc1 ==========… [View More]

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Is it OK to extend the ndarray structure?
by Sebastian Berg May 27, 2020

May 27, 2020

Hi all, 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 buffer interface. 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 … [View More]

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new numpy.org is live
by Inessa Pawson May 26, 2020

May 26, 2020

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 … [View More]

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NumPy Community Meeting Wednesday
by Sebastian Berg May 26, 2020

May 26, 2020

Hi all, 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: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both Best wishes Sebastian

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log of negative real numbers -> RuntimeWarning: invalid value encountered in log
by Brian Racey May 25, 2020

May 25, 2020

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.

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Call for Reviewers
by Anirudh Subramanian May 22, 2020

May 22, 2020

Hi all, This topic was brought up in the triage meeting today. Numpy is seeing a huge surge in the number of PRs (current open PRs: 253) which could means two things: 1. Increase in volume of incoming PRs 2. Not enough reviewers to review the PRs. One thing that was discussed in the meeting was to add a stale label : "61 - Stale" which has already been added by Sebastian. The community needs some help here and I think you can help irrespective of your level of experience with the numpy … [View More]

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Re: [Numpy-discussion] Call for Reviewers
by ChunLin Fang May 22, 2020

May 22, 2020

Hi all, I've reviewed and submitted several Numpy PRs before, Glad to have the right to add tags.my github id is Qiyu8 <https://github.com/Qiyu8>. Thanks, ChunLin Fang

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Participation in GSoD 2020
by Sayak Kundu May 21, 2020

May 21, 2020

Hi everyone, I am Sayak Kundu. I am a student at IIIT Hyderabad. This email is regarding the participation in Google Season of DOcs 2020 as a technical writer. I am interested in *High-level restructuring and end-user focus*. I have experience with Numpy and Scipy and have used them across many of my projects for Multivariate Analysis, Data Science, Machine Learning, etc. I have also worked with the Internet Archive for past 1 year on their Google Action and Alexa Skill as a developer and this … [View More]

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Some details related to project ideas for GSoD 2020
by Apoorva May 20, 2020

May 20, 2020

Dear Sir/Ma’am, I’m writing to seek information regarding the project ideas for GSoD. As it was mentioned in the “Project Ideas” that the technical writer can also develop a “How-to” tutorial, can it be for beginners as well or is NumPy targeting professionals or seasoned developers only? I would be grateful if I could get a reply for the same. With warm regards, Apoorva. Sent from Mail for Windows 10

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Re: [Numpy-discussion] Using nditer + external_loop to Always Iterate by Column
by William Ayd May 19, 2020

May 19, 2020

Thanks Hameer for the suggestion. I perhaps should have clarified that this is a small example for something larger, where I am iterating over a sequence of arrays, computing some reduction on the first and writing to the second. I am hoping to keep it all contained within one nditer. Thanks Eric for the suggestion. Notwithstanding the bug that would seem to be promising. I’ll do a little more research and see what I can find.

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NumPy Development Meeting Tomorrow - Triage Focus
by Sebastian Berg May 19, 2020

May 19, 2020

Hi all, Our bi-weekly triage-focused NumPy development meeting is tomorrow (Wednesday, May 20th) at 11 am Pacific Time (18:00 UTC). 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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Re: [Numpy-discussion] Using nditer + external_loop to Always Iterate by Column
by William Ayd May 19, 2020

May 19, 2020

I am trying to use the nditer to traverse each column of a 2D array, returning the column as a 1D array. Consulting the docs, I found this example which works perfectly fine: In [65]: a = np.arange(6).reshape(2,3) In [66]: for x in np.nditer(a, flags=['external_loop'], order='F'): ...: print(x, end=' ') ...: … [View More]

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help translating into Russian
by Inessa Pawson May 19, 2020

May 19, 2020

Our collaboration with the students and faculty from the Master’s program in Survey Methodology at the University of Michigan and the University of Maryland is underway. We are looking for a volunteer to translate the survey questionnaire into Russian. 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, *Inessa Pawson * Executive Director Albus Code

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NumPy 1.19. 0rc1 Release
by Charles R Harris May 18, 2020

May 18, 2020

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.19.0rc1 has been released. This NumPy release 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 … [View More]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/1.19.0rc1/>, source archives and release notes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.19.0rc1>. *Contributors* A total of 118 people contributed to this release. People with a "+" by their 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 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 - 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 - Till Hoffmann + - Tim Hoffmann - Tina Oberoi + - Tirth Patel - Tyler Reddy - Warren Weckesser - Xavier Thomas + - Yilin LI + - Zac Hatfield-Dodds + - Zé Vinícius + - @Adam + - @Anthony + - @Jim + - @bartosz-grabowski + - @dojafrat + - @gamboon + - @jfbu + - @keremh + - @mayeut + - @ndunnewind + - @nglinh + - @shreepads + - @sslivkoff + Cheers, Charles Harris [View Less]

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Reg: GSoD project discussion
by PRUBHTEJ SINGH May 17, 2020

May 17, 2020

Greetings I have interest in contributing to the project titled:"High level restructuring and end user focus". Kindly request you to guide me for the same . Hoping to hear from you soon Regards Prubhtej Singh

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Documentation Team Meeting - Monday April 6
by Melissa Mendonça May 15, 2020

May 15, 2020

Hi all, This is a reminder that we're having a Documentation Team Meeting next monday, April 6th, at 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! ** You can click this link to get the correct time at your timezone: https://www.timeanddate.com/worldclock/fixedtime.html?msg=NumPy+Documentati… - Melissa

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Google Season of Docs proposals and information
by Melissa Mendonça May 15, 2020

May 15, 2020

Hello all, especially those who recently joined and are interested in our Google Season of Docs projects. It is great to hear from you! For now, all the information you need about the program is in the official GSoD website (https://developers.google.com/season-of-docs), and in our proposal ( https://github.com/numpy/numpy/wiki/Google-Season-of-Docs-2020-Project-Ideas). If you are interested, I would advise working on the following: - Familiarizing yourself with the NumPy docs and the … [View More]

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NumPy wheels for pypy and aarch64.
by Charles R Harris May 15, 2020

May 15, 2020

Hi All, Just a note that NumPy wheels for both pypy and aarch64 are now available in the nightly builds. Chuck

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GSoD Project External tutorial content curation and adaptation
by Siddhartha Kapoor May 15, 2020

May 15, 2020

I was going through the project titled "External tutorial content curation and adaptation" with mentors as Melissa Mendonca Weber, Ralf Gommers. I propose we can do the following - 1. Gather all the info about external tutorials in the form of videos, blogs, etc. any content that can help a user understand numpy would be taken. 2. Categorise all the content into different types, i.e. Video, 3rd party documentation, blogs, etc. 3. Obtain the required permissions to source the content. After … [View More]

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Histogram or other issues
by Alex Rockhill May 15, 2020

May 15, 2020

Hey does anyone forsee any issues with histogram or anything else for this PR: https://github.com/numpy/numpy/pull/16248? <https://urldefense.com/v3/__https://github.com/numpy/numpy/pull/16248?__;!!…> Thanks, Alex Rockhill

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Application Pre-requisites
by Hmrishav Bandyopadhyay May 13, 2020

May 13, 2020

Hi, I am Hmrishav Bandyopadhyay, an Undergrad at Jadavpur University, India. One of the application pre-requisites for applying to GSOD under numpy require me to have technical writing experience. Being a student, I have not had any professional technical writing job or internship per-se but I have been writing tutorials and such in Towards Data Science(Medium) for some time now, most of which have been curated by the website. Does this make me eligible for applying to numpy? Any help or … [View More]

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Reg: GSoD-2020-Participation
by PRUBHTEJ SINGH May 13, 2020

May 13, 2020

Greetings, I am interested in contributing towards NumPy's documentation , but I'm still a bit confused on where to start. Request your guidance on the same .Hoping to hear from you soon. Regards Prubhtej Singh

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Google Season of Docs 2020 - New NumPy Community Member
by Themistoklis Spanoudis May 13, 2020

May 13, 2020

Hello everyone! I am very excited to introduce myself to the NumPy community! I am Themistoklis Spanoudis, I come from Greece and I have recently finished my 5-year (Integrated Masters) Degree in Mechanical Engineering at Aristotle University of Thessaloniki. I am very happy to see that NumPy has been selected for Google Season of Docs 2020, because I love scientific computing and Python and I would really like to contribute in one of your GSoD projects. Specifically, what caught my … [View More]attention is “Creating high-level documentation, such as Tutorials and How-Tos, covering topics that are missing from the official documentation”. I have a pretty clear idea on where I would like to make this project go, but first let me share a few things about my background. My first introduction to scientific computing came during the first year of my studies through a semester course on this topic, based on MATLAB. During that semester I had a lot of course assignments that eventually got me hooked with scientific computing. My journey in this area continued with me getting to know NumPy and Python and choosing a plethora of courses during the following years of my studies that included computational assignments. During those years I built programs that range from Structural Finite Element Analysis, Fatigue Analysis and Lagrangian Dynamics to Statistical Quality Control, Operations Research and Supply Chain Optimization. Moreover, last year I completed my Master Thesis during a 6-month full-time position at Airbus Helicopters in Germany, during which I had the chance to work on flight trajectory optimization and data-driven flight dynamics modelling. This involved a lot of scientific programming building state-space models and defining optimization problems as well as tasks related to working with a large amount of data such as, cleaning, filtering, transforming to extract training examples and utilizing them in various models. Additionally, last summer I participated in Google Summer of Code 2019 with AerospaceResearch, which is an international space community helping realise space exploration. My project involved the development of a software module to be integrated within a research project tackling electric propulsion system optimization for small satellites. The module is responsible for the visualization of genetic algorithm data in order to extract insights about the evolution process that can be used both to improve the algorithm and as heuristics by human designers. This project involved working with evolution data to automatically create static plots as well as animations that are completely configurable through a user-readable XML input file. My work along with other advancements in the research project was published at the 36th International Electric Propulsion Conference. On a similar note, last fall I participated in Google Season of Docs 2019 with OpenSCAD, which is a scripting software for creating solid 3D CAD models. My project involved the creation of a tutorial focused on new OpenSCAD users. My mentors introduced me to the great presentation “What nobody tells you about documentation” by Daniele Procida at PyCon Australia 2017, which was a major influence for my work. Closely following the guidelines of the presentation for the “tutorial” type of documentation and reviewing existing material and references, I developed a hands-on, follow-along tutorial designed to get new users started with creating their own models as soon as possible, while gradually introducing more advanced features and building their confidence by following a steady progression and a consistent style. So that was about my background and experience, let me now say a few words about my plans for this year. For Google Season of Docs 2020 I would like to work with the NumPy community to create a more advanced, application-based tutorial that will serve as the next step to the previous year’s project “NumPy: the absolute basics for beginners”. Having gone through most of the currently available documentation under https://numpy.org/devdocs/index.html as well the external linked educational material, I believe this project would be a great addition to the existing documents. It would help new users understand how NumPy can be used in practice to solve real problems, get them familiar with more advanced features not referenced in the basic tutorial and get them ready to work on their own projects. This tutorial would include step-by-step explanations providing a lot of context to the users as well as follow-along exercises/challenges. The topics presented on this tutorial can be focused around scientific simulation, optimization and data science. In my opinion data science is a stronger candidate for this purpose, since the same techniques and methodologies are directly applicable to a wider audience across different fields, compared to scientific simulation which is more coupled to domain knowledge and could potentially repel users lacking the relevant background. The exact presented cases of course is something to be discussed and adapted to fit the educative flow and the covered material. In order to avoid this introductory message getting too long and to give you a practical idea of what I mean by step-by-step, follow-along explanations as well as by providing context and explaining the thought process behind doing things a certain way, I would like to link to my work from Google Summer of Code 2019 and Google Season of Docs 2019. Google Summer of Code 2019 -Official project listing on Google’s website: https://summerofcode.withgoogle.com/archive/2019/projects/6650127358361600/ -Final report: https://aerospaceresearch.net/?p=1812 -Blog posts presenting the functionality of the developed module through example use cases (highly recommended if you are into genetic algorithms): ---Blog post 1: https://aerospaceresearch.net/?p=1542 ---Blog post 2: https://aerospaceresearch.net/?p=1571 ---Blog post 3: https://aerospaceresearch.net/?p=1785 Google Season of Docs -Official project listing on Google’s website: https://developers.google.com/season-of-docs/docs/2019/participants/project… -Final report: https://github.com/s-themis/Google-Season-of-Docs-2019-Project-Report -Root page of developed tutorial: https://en.m.wikibooks.org/wiki/OpenSCAD_Tutorial -Alternative linking to the individual tutorial chapters through OpenSCAD’s website: https://www.openscad.org/documentation.html I would also like to add here my 100+ page Master Thesis as an additional example of my technical writing work but unfortunately it is currently set confidential by Airbus. I think this is a good overall introduction to my background, my work and my intentions regarding working with NumPy to get the discussion going about the specific project that I would like to complete during this year’s Google Season of Docs program. I would highly appreciate your input, feedback, thoughts and comments. I am looking forward to hearing from you! Best regards, Themistoklis Spanoudis [View Less]

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Announcing PyData/Sparse 0.10.0
by Hameer Abbasi May 13, 2020

May 13, 2020

On behalf of the community and contributors, I’m pleased to announce PyData/Sparse v0.10.0. PyData/Sparse is a package that provides sparse arrays mimicking NumPy API for the PyData ecosystem. This was a mainly bug-fix focused release with a few features and performance improvements. Most notably, it fixes deprecation warnings that arise when pairing it with Numba v0.49, which will turn into errors with Numba v0.50. The full change-log can be found at https://sparse.pydata.org/en/latest/… [View More]

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Should I introduce a new friendly and efficient way to running and debugging numpy test case?
by ChunLin Fang May 13, 2020

May 13, 2020

Hi, everyone! I'm Qiyu8 <https://github.com/Qiyu8>, Currently, Numpy recommend a command line method to run test case as demonstrated in Testing Guidelines <https://numpy.org/devdocs/reference/testing.html#testing-guidelines> ,Which is heavy and inconvenient, It's also a little painful if test cases can not debug in a visualize way, I happened to find an easier way to running and debugging numpy test case as below: *1.Download VS Code **here <https://code.visualstudio.com/… [View More]

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NEP 38 - Universal SIMD intrinsics
by Daniel Davies May 13, 2020

May 13, 2020

Is clock-throttling of interest here? It would be really annoying if the code that chooses a macro implementation has to guess how much power will be consumed by each core. Or has to dynamically pick a macro implementation based on the current frequencies of all the cores. https://lemire.me/blog/2018/08/13/the-dangers-of-avx-512-throttling-myth-or… https://lemire.me/blog/2018/09/07/avx-512-when-and-how-to-use-these-new-ins… Dan

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NumPy Community Meeting Wednesday
by Sebastian Berg May 12, 2020

May 12, 2020

Hi all, There will be a NumPy Community meeting Wednesday May 13th 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: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both Best wishes Sebastian

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Reg: GSoD 2020
by PRUBHTEJ SINGH May 12, 2020

May 12, 2020

Greetings I would like to contribute to numpy's documentation under GSoD-2020 program. Requesting your guidance for the same. Regards Prubhtej Singh

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GSoD 2020!
by Ben Nathanson May 11, 2020

May 11, 2020

Congratulations on getting chosen once again for Season of Docs! I'm very eager to talk about collaborating.

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Update the Code of Conduct Committee Membership (new members wanted)
by Sebastian Berg May 10, 2020

May 10, 2020

Hi all, it has come up in the last community call that many of our committee membership lists have not been updated in a while. This is not a big issue as such. But, while these committees are not very active on a day-to-day basis, they are an important part of the community and it is better to update them regularly and thus also ensure they remain representative of the community. We would like to start by updating the members of the Code of Conduct (CoC) committee. The CoC committee is in … [View More]

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Feelings about type aliases in NumPy
by Joshua Wilson May 9, 2020

May 9, 2020

Hey everyone, Over in numpy-stubs we've been working on typing "array like": https://github.com/numpy/numpy-stubs/pull/66 It would be nice if the type were public so that downstream projects could use it (e.g. it would be very helpful in SciPy). Originally the plan was to only make it publicly available at typing time and not runtime, which would mean that no changes to NumPy are necessary; see https://github.com/numpy/numpy-stubs/pull/66#issuecomment-618784833 for more information on how … [View More]

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divmod(1.0, 0.0) bug
by Anirudh Subramanian May 9, 2020

May 9, 2020

Hi all, There has been a discussion about divmod (1.0, 0.0) bug here : https://github.com/numpy/numpy/issues/14900 and https://github.com/numpy/numpy/pull/16161 . *SUMMARY* Currently divmod(1.0, 0.0) sets the "Invalid error" and returns (nan, nan). This is not consistent with IEEE 754 <https://en.wikipedia.org/wiki/IEEE_754> standard which says that 1.0/0.0 divisions should return inf and raise dividebyzero error. Although this may not apply to divmod, it should apply to floor_divide … [View More]

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NumPy Development Meeting Tomorrow - Triage Focus
by Sebastian Berg May 5, 2020

May 5, 2020

Hi all, Our bi-weekly triage-focused NumPy development meeting is tomorrow (Wednesday, May 6th) at 11 am Pacific Time (18:00 UTC). 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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Season of Docs technical writer
by Ben Nathanson May 4, 2020

May 4, 2020

I've updated my page (https://bennathanson.com/numpy2020) to include a section on Curation and Adaptation.

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Re: [Numpy-discussion] Closing resolved good-first-issues
by Tina Oberoi May 4, 2020

May 4, 2020

Fri, 1 May 2020 18:05:14 Ralf Gommers <ralf.gommers(a)gmail.com> wrote: > > Hi Tina, thanks for pointing that out. I have added you to the triage team, > so you are able to close issues that you already noticed are fixed. I'll > have a look at labelling some new ones now. These are the issues that have pull requests merged but still open, Please let me know if I am wrong else we can close these issues: - Issue #9476 <https://github.com/numpy/numpy/issues/9476> - … [View More]

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NumPy nightly wheel builds
by Charles R Harris May 3, 2020

May 3, 2020

Hi All, The NumPy "nightly" wheel builds, actually built weekly on Sunday mornings, have moved to https://anaconda.org/scipy-wheels-nightly/numpy/files. They can be installed/downloaded using pip: pip install -i https://pypi.anaconda.org/scipy-wheels-nightly/simple numpy Chuck

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ANN: mplcairo 0.3 release
by Antony Lee May 3, 2020

May 3, 2020

Dear all, I am pleased to announce the release of mplcairo 0.3. mplcairo is a Matplotlib backend based on the well-known cairo library, supporting output to both raster (including interactively) and vector formats. In other words, it provides the functionality of Matplotlib's {,qt5,gtk3,wx,tk,macos}{agg,cairo}, pdf, ps, and svg backends. Per Matplotlib's standard API, the backend can be selected by calling matplotlib.use("module://mplcairo.qt") or setting your MPLBACKEND environment … [View More]

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NumPy 1.18.4 release
by Charles R Harris May 3, 2020

May 3, 2020

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.18.4 has been released. This is the last planned release in the 1.18.x series. It reverts the bool("0") behavior introduced in 1.18.3 and fixes a bug in Generator.integers. There is also a link to a new troubleshooting section in the documentation included in the error message emitted when numpy import fails. The Python versions supported in this release are 3.5-3.8. Downstream developers should use Cython >= 0.29.15 … [View More]

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Deprecate inexact matches for mode, order etc ?
by Anirudh Subramanian May 2, 2020

May 2, 2020

Hi all, I added a proposal to deprecate inexact and case insensitive matches for mode, order, searchside and sortkind. in https://github.com/numpy/numpy/pull/16056 , and this stemmed from a discussion started in https://github.com/numpy/numpy/pull/16007#discussion_r410517462 Currently, numpy allows : np.ravel_multi_index(arr, (7, 6), mode='Clip') np.ravel_multi_index(arr, (7, 6), mode='C') np.ravel_multi_index(arr, (7, 6), mode='cat') We have a similar story for order, searchside and … [View More]

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Closing resolved good-first-issues
by Tina Oberoi May 1, 2020

May 1, 2020

Hi all, I observed that there are many good-first-issues that are resolved but yet open. It would be a great help for new contributors if we could close them and label new good-first-issues (if not labelled already). Thanks and Regards Tina

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