Mailman 3 March 2019 - NumPy-Discussion

Introducing myself
by Brinda March 23, 2019

March 23, 2019

Hello, I am called Malika. My outreachy initial application has been recently approved. I am new to this community and I'm really eager to work on this project. Please I wish someone explains to me how to get started.

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prpp report—please help review!
by Stefan van der Walt March 21, 2019

March 21, 2019

Hi everyone, During the community call today, we drew up a list of open PR counts per developer. We are working towards bringing down their number (around 240 today), and would appreciate it if you could help us review and/or make decisions. NumPy also has 1760 open issues <https://github.com/numpy/numpy/issues>; many of these are probably invalid—but just clicking through them all takes a lot of time. So if you want to grab 5 random ones and check their status, that would be very helpful. Best regards, Stéfan PR count `1. eric-wieser: 32 2. jaimefrio: 10 3. juliantaylor: 6 4. madphysicist: 6 5. mattip: 5 6. bashtage: 4 7. tylerjereddy: 4 8. zerothi: 4 9. pitrou: 3 10. hameerabbasi: 3 ` Eric’s PRs: * #12519: ENH/DEP: Use a ufunc under the hood for ndarray.clip <https://api.github.com/repos/numpy/numpy/pulls/12519> * #12473: ENH: Make the contents of dtype.fields namedtuple-like <https://api.github.com/repos/numpy/numpy/pulls/12473> * #12205: MAINT: avoid relying on `np.generic.__name__` in `np.dtype.name` <https://api.github.com/repos/numpy/numpy/pulls/12205> * #12178: BUG: Prevent segfaults if python runs out of memory concatenating strings in ufunc error messages <https://api.github.com/repos/numpy/numpy/pulls/12178> * #11955: MAINT: Move _do_append and _do_prepend out of the functions to generate padding values <https://api.github.com/repos/numpy/numpy/pulls/11955> * #11829: MAINT: Use textwrap.dedent in f2py tests <https://api.github.com/repos/numpy/numpy/pulls/11829> * #11397: DEP: Deprecate the normed argument to histogramdd to match histogram <https://api.github.com/repos/numpy/numpy/pulls/11397> * #10765: BUG: Disable hex(np.floating) and oct(np.floating) on python 2 <https://api.github.com/repos/numpy/numpy/pulls/10765> * #10741: ENH: Implement `np.floating.as_integer_ratio` <https://api.github.com/repos/numpy/numpy/pulls/10741> * #10723: BUG: longdouble(int) does not work <https://api.github.com/repos/numpy/numpy/pulls/10723> * #10417: ENH: Allow dtype objects to be indexed with multiple fields at once <https://api.github.com/repos/numpy/numpy/pulls/10417> * #10308: API: Make MaskedArray.mask return a view, rather than the underlying mask <https://api.github.com/repos/numpy/numpy/pulls/10308> * #10151: BUG: Numpy scalar types sometimes have the same name <https://api.github.com/repos/numpy/numpy/pulls/10151> * #10132: BUG: np.matrix does not return an array when given a full index ending in … <https://api.github.com/repos/numpy/numpy/pulls/10132> * #10025: ENH: Add the ndmin argument from np.array to np.as[any]array <https://api.github.com/repos/numpy/numpy/pulls/10025> * #9963: ENH: Add the C99 remainder function, as `np.remainder_ieee` <https://api.github.com/repos/numpy/numpy/pulls/9963> * #9951: ENH: Make dtype iterable <https://api.github.com/repos/numpy/numpy/pulls/9951> * #9705: BUG: Fix some (not all) compiler warnings <https://api.github.com/repos/numpy/numpy/pulls/9705> * #9690: BUG: Fix broken out argument in np.ma ufunc_likes <https://api.github.com/repos/numpy/numpy/pulls/9690> * #9459: MAINT: Remove unhelpful docstrings, improve helpful ones <https://api.github.com/repos/numpy/numpy/pulls/9459> * #9428: ENH: add a neigborwise function <https://api.github.com/repos/numpy/numpy/pulls/9428> * #9353: BUG: Fix np.ma.take on un-indexable scalars <https://api.github.com/repos/numpy/numpy/pulls/9353> * #8970: ENH/API: Change flexible types to indicate resizability with elsize == -1 <https://api.github.com/repos/numpy/numpy/pulls/8970> * #8910: ENH: avoid allocations in getmaskarray <https://api.github.com/repos/numpy/numpy/pulls/8910> * #8868: MAINT: Split ufunc into two subtypes, and remove methods where innapropriate <https://api.github.com/repos/numpy/numpy/pulls/8868> * #8853: BUG: Prevent power(uint64, int64) casting to float <https://api.github.com/repos/numpy/numpy/pulls/8853> * #8662: ENH: preserve subclasses in ufunc.outer <https://api.github.com/repos/numpy/numpy/pulls/8662> * #8641: BUG: Preserve types of empty arrays in ix_ when known <https://api.github.com/repos/numpy/numpy/pulls/8641> * #8640: ENH: generalize `ix_` to work for arbitrary dimensionality of input <https://api.github.com/repos/numpy/numpy/pulls/8640> * #8615: ENH: Add support for coercing structured arrays into dicts <https://api.github.com/repos/numpy/numpy/pulls/8615> * #8514: ENH: Make it possible to call .view on object arrays <https://api.github.com/repos/numpy/numpy/pulls/8514> * #8511: MAINT: make np.ma.apply_along_axis consistent with np.apply_along_axis <https://api.github.com/repos/numpy/numpy/pulls/8511> Jaime’s PRs: * #9424: ENH: Adds an out argument to bincount. <https://api.github.com/repos/numpy/numpy/pulls/9424> * #7473: BUG: shift operator cycles, fixes #2449 <https://api.github.com/repos/numpy/numpy/pulls/7473> * #7464: ENH: Make bincount output same type as weights, fixes #6854 <https://api.github.com/repos/numpy/numpy/pulls/7464> * #7450: BUG, MAINT: concatenate of empty sequences, fixes #1586 <https://api.github.com/repos/numpy/numpy/pulls/7450> * #7441: MANT: refactor PyArrayMultiIterObject constructors <https://api.github.com/repos/numpy/numpy/pulls/7441> * #6219: MAINT: refactor unravel_index for code repetition <https://api.github.com/repos/numpy/numpy/pulls/6219> * #5890: BUG: Don’t use longlong for PyLong if it isn’t larger than long <https://api.github.com/repos/numpy/numpy/pulls/5890> * #5740: MAINT: Refactor .flags attribute of ndarray <https://api.github.com/repos/numpy/numpy/pulls/5740> * #4366: BUG: Allow any integer type in bincount (fixes #823) <https://api.github.com/repos/numpy/numpy/pulls/4366> * #4246: BUG: `take` casting logic with an `out=` argument <https://api.github.com/repos/numpy/numpy/pulls/4246>

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Outreachy Program Aspirant
by rishab lamba March 20, 2019

March 20, 2019

Hi, I am Rishab Lamba undergoing my B.Tech from BVCOE, India. As an applicant from Outreachy, I was going through this project https://www.outreachy.org/may-2019-august-2019-outreachy-internships/commun… and would like to work on it. I was not aware of such a program and hence cutting it really close to the deadline but I still hope if I can make contributions as much as possible to the numpy repository. For this, any guidance for submitting the PRs will be appreciated

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BIDS / NumPy Community Meeting tomorrow (March 20th)
by Tyler Reddy March 20, 2019

March 20, 2019

Hi, Just a reminder of the community meeting tomorrow at 12 pm Pacific time. There's a section for community suggested topics in the work-in-progress document that can be edited here: https://hackmd.io/c_SRuI0GTNKBZHzsRX9wSw?view

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BoF submission to SciPy 2019 open
by Matthias Bussonnier March 19, 2019

March 19, 2019

Hello NumPy developers, The SciPy conference would like to encourage you to submit proposals for Birds of a Feather (BoF) sessions at this year's SciPy! BoFs usually include short presentations by a panel and a moderator with the bulk of the time spent opening up the discussion to everyone in attendance, but the format is flexible. BoF topics can be of general interest, such as state-of-the-project BoFs, or based on the themes of the conference and the mini-symposia topics, or can be a great opportunity to collect informations from members of the SciPy community. We would like to encourage you to think about topics of interest and submit your proposals. Submissions are open and will close on Friday, May 31st, 2019. You can submit you proposal here: https://www.scipy2019.scipy.org/bof-sessions. Last Year if my memory serves correctly we had Matti and Stefan for a "So What's up with NumPy". Past SciPy conferences have had a large variety of BoF sessions, including topics on Reproducibility, Jupyter Notebooks, Distributed Computing, Geospatial Packages in Python, Teaching Scientific Computing with Python, Python and Finance, NumFOCUS, Python in Astronomy, Collaborating and Contributing in Open Science, Education, and a Matplotlib Enhancement Proposal Discussion. Generally, if there is a topic where you think a number of people at SciPy will be interested, you should propose it! Please share this with anyone else in the community who you think would be a good candidate for organizing a BoF. The BoF committee will try to select the BoFs based on a number of criteria, and/or attempt to merge BoFs submissions with a large overlap. Thanks in advance for your submission(s), and looking forward to see you at SciPy 2019, Austin Texas, July 8-14, 2019. Feel free to contact us if you have any questions, concerns or suggestions. -- Lindsey Heagy and Matthias Bussonnier for the SciPy organizers. scipybofs(a)gmail.com

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2019 John Hunter Excellence in Plotting Contest
by Madicken Munk March 18, 2019

March 18, 2019

In memory of John Hunter, we are pleased to be reviving the SciPy John Hunter Excellence in Plotting Competition for 2019. 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 the conference. John Hunter’s family and NumFocus 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, 8th to the form at https://goo.gl/forms/cFTB3FUBrMPfQ7Vz1 - Winners will be announced at Scipy 2019 in Austin, TX. - 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, 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. This 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 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). SciPy John Hunter Excellence in Plotting Competition Co-Chairs Hannah Aizenman Thomas Caswell Madicken Munk Nelle Varoquaux

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Outreachy applicant: Improve C API Documentation for Numpy
by Nisha Aggarwal March 17, 2019

March 17, 2019

Hello, I am an Outreachy applicant interested in the project: Improve C API Documentation for Numpy, but I am unsure of how to proceed. Can someone guide me here? Thanks

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Testing your contributions
by Sandy March 16, 2019

March 16, 2019

Hey there, I am new to numpy. I just wanted to know, suppose I make a code contribution to the repo https://github.com/numpy/numpy how do I test its working?

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NumPy sprint at BIDS: May 10/11
by Stefan van der Walt March 15, 2019

March 15, 2019

Hi everyone, On May 10/11, we will host another NumPy sprint at the Berkeley Institute for Data Science. The focus of this meeting will be the design of a new data type system, and to consolidate: - https://github.com/numpy/numpy/pull/12630 [Matti's NEP PR WIP] - https://hackmd.io/ok21UoAQQmOtSVk6keaJhw?view [Matti's dtype notes] - https://hackmd.io/s/ryTFaOPHE# [Eric's dtype notes] Please let me know if you are interested in attending. Best regards, Stéfan

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#4808 -- let np.pad default to constant
by Stefan van der Walt March 14, 2019

March 14, 2019

In PR 4808, I propose changing the default padding mode (for `np.pad`) to constant (0). It was suggested that I mention the change here, in case someone has a use case or argument for not making it. https://github.com/numpy/numpy/pull/4808 Thanks! Stéfan

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