Mailman 3 April 2015 - NumPy-Discussion

GSoC students: please read
by Ralf Gommers April 4, 2015

April 4, 2015

Hi all, It's great to see that this year there are a lot of students interested in doing a GSoC project with Numpy or Scipy. So far five proposals have been submitted, and it looks like several more are being prepared now. I'd like to give you a bit of advice as well as an idea of what's going to happen in the few weeks. The deadline for submitting applications is 27 March. Don't wait until the last day to submit your proposal! It has happened before that Melange was overloaded and unavailable - the Google program admins will not accept that as an excuse and allow you to submit later. So as soon as your proposal is in good shape, put it in. You can still continue revising it. >From 28 March until 13 April we will continue to interact with you, as we request slots from the PSF and rank the proposals. We don't know how many slots we will get this year, but to give you an impression: for the last two years we got 2 slots. Hopefully we can get more this year, but that's far from certain. Our ranking will be based on a combination of factors: the interaction you've had with potential mentors and the community until now (and continue to have), the quality of your submitted PRs, quality and projected impact of your proposal, your enthusiasm, match with potential mentors, etc. We will also organize a video call (Skype / Google Hangout / ...) with each of you during the first half of April to be able to exchange ideas with a higher communication bandwidth medium than email. Finally a note on mentoring: we will be able to mentor all proposals submitted or suggested until now. Due to the large interest and technical nature of a few topics it has in some cases taken a bit long to provide feedback on draft proposals, however there are no showstoppers in this regard. Please continue improving your proposals and working with your potential mentors. Cheers, Ralf

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Re: [Numpy-discussion] Fix masked arrays to properly edit views
by John Kirkham April 4, 2015

April 4, 2015

Hey Eric, That's a good point. I remember seeing this behavior before and thought it was a bit odd. Best, John > On Mar 16, 2015, at 2:20 AM, numpy-discussion-request(a)scipy.org wrote: > > Send NumPy-Discussion mailing list submissions to > numpy-discussion(a)scipy.org > > To subscribe or unsubscribe via the World Wide Web, visit > http://mail.scipy.org/mailman/listinfo/numpy-discussion > or, via email, send a message with subject or body 'help' to > numpy-discussion-request(a)scipy.org > > You can reach the person managing the list at > numpy-discussion-owner(a)scipy.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of NumPy-Discussion digest..." > > > Today's Topics: > > 1. Re: Fix masked arrays to properly edit views (Eric Firing) > 2. Rewrite np.histogram in c? (Robert McGibbon) > 3. numpy.stack -- which function, if any, deserves the name? > (Stephan Hoyer) > 4. Re: Rewrite np.histogram in c? (Jaime Fern?ndez del R?o) > 5. Re: Rewrite np.histogram in c? (Robert McGibbon) > 6. Re: Rewrite np.histogram in c? (Robert McGibbon) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 14 Mar 2015 14:01:04 -1000 > From: Eric Firing <efiring(a)hawaii.edu> > Subject: Re: [Numpy-discussion] Fix masked arrays to properly edit > views > To: numpy-discussion(a)scipy.org > Message-ID: <5504CBC0.1080502(a)hawaii.edu> > Content-Type: text/plain; charset=windows-1252; format=flowed > >> On 2015/03/14 1:02 PM, John Kirkham wrote: >> The sample case of the issue ( >> https://github.com/numpy/numpy/issues/5558 ) is shown below. A proposal >> to address this behavior can be found here ( >> https://github.com/numpy/numpy/pull/5580 ). Please give me your feedback. >> >> >> I tried to change the mask of `a` through a subindexed view, but was >> unable. Using this setup I can reproduce this in the 1.9.1 version of NumPy. >> >> import numpy as np >> >> a = np.arange(6).reshape(2,3) >> a = np.ma.masked_array(a, mask=np.ma.getmaskarray(a), shrink=False) >> >> b = a[1:2,1:2] >> >> c = np.zeros(b.shape, b.dtype) >> c = np.ma.masked_array(c, mask=np.ma.getmaskarray(c), shrink=False) >> c[:] = np.ma.masked >> >> This yields what one would expect for `a`, `b`, and `c` (seen below). >> >> masked_array(data = >> [[0 1 2] >> [3 4 5]], >> mask = >> [[False False False] >> [False False False]], >> fill_value = 999999) >> >> masked_array(data = >> [[4]], >> mask = >> [[False]], >> fill_value = 999999) >> >> masked_array(data = >> [[--]], >> mask = >> [[ True]], >> fill_value = 999999) >> >> Now, it would seem reasonable that to copy data into `b` from `c` one >> can use `__setitem__` (seen below). >> >> b[:] = c >> >> This results in new data and mask for `b`. >> >> masked_array(data = >> [[--]], >> mask = >> [[ True]], >> fill_value = 999999) >> >> This should, in turn, change `a`. However, the mask of `a` remains >> unchanged (seen below). >> >> masked_array(data = >> [[0 1 2] >> [3 0 5]], >> mask = >> [[False False False] >> [False False False]], >> fill_value = 999999) > > I agree that this behavior is wrong. A related oddity is this: > > In [24]: a = np.arange(6).reshape(2,3) > In [25]: a = np.ma.array(a, mask=np.ma.getmaskarray(a), shrink=False) > In [27]: a.sharedmask > True > In [28]: a.unshare_mask() > In [30]: b = a[1:2, 1:2] > In [31]: b[:] = np.ma.masked > In [32]: b.sharedmask > False > In [33]: a > masked_array(data = > [[0 1 2] > [3 -- 5]], > mask = > [[False False False] > [False True False]], > fill_value = 999999) > > It looks like the sharedmask property simply is not being set and > interpreted correctly--a freshly initialized array has sharedmask True; > and after setting it to False, changing the mask of a new view *does* > change the mask in the original. > > Eric > >> >> Best, >> John >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion(a)scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > ------------------------------ > > Message: 2 > Date: Sun, 15 Mar 2015 21:32:49 -0700 > From: Robert McGibbon <rmcgibbo(a)gmail.com> > Subject: [Numpy-discussion] Rewrite np.histogram in c? > To: Discussion of Numerical Python <numpy-discussion(a)scipy.org> > Message-ID: > <CAN4+E8Ff_Ck-9GBRCbSTq6qPiuGxgKeiX3+kKrXn4NM-Lnn6rg(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Hi, > > Numpy.histogram is implemented in python, and is a little sluggish. This > has been discussed previously on the mailing list, [1, 2]. It came up in a > project that I maintain, where a new feature is bottlenecked by > numpy.histogram, and one developer suggested a faster implementation in > cython [3]. > > Would it make sense to reimplement this function in c? or cython? Is moving > functions like this from python to c to improve performance within the > scope of the development roadmap for numpy? I started implementing this a > little bit in c, [4] but I figured I should check in here first. > > -Robert > > [1] > http://scipy-user.10969.n7.nabble.com/numpy-histogram-is-slow-td17208.html > [2] http://numpy-discussion.10968.n7.nabble.com/Fast-histogram-td9359.html > [3] https://github.com/mdtraj/mdtraj/pull/734 > [4] https://github.com/rmcgibbo/numpy/tree/histogram >

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SciPy 2015 Conference Updates - Call for talks extended to 4/10, registration open, keynotes announced, John Hunter Plotting Contest
by Courtenay Godshall (Enthought) April 3, 2015

April 3, 2015

---------------------------------------------------------------------------- ----------------------------------------------------------- **LAST CALL FOR SCIPY 2015 TALK AND POSTER SUBMISSIONS - EXTENSION TO 4/10* ---------------------------------------------------------------------------- ----------------------------------------------------------- SciPy 2015 will include 3 major topic tracks and 7 mini-symposia tracks. Submit a proposal on the SciPy 2015 website: <http://scipy2015.scipy.org> http://scipy2015.scipy.org. If you have any questions or comments, feel free to contact us at: <mailto:scipy-organizers@scipy.org> scipy-organizers(a)scipy.org <http://scipy2015.scipy.org> . You can also follow @scipyconf on Twitter or sign up for the mailing list on the website for the latest updates! Major topic tracks include: - Scientific Computing in Python (General track) - Python in Data Science - Quantitative Finance and Computational Social Sciences Mini-symposia will include the applications of Python in: - Astronomy and astrophysics - Computational life and medical sciences - Engineering - Geographic information systems (GIS) - Geophysics - Oceanography and meteorology - Visualization, vision and imaging -------------------------------------------------------------------------- **SCIPY 2015 REGISTRATION IS OPEN** Please register ASAP to help us get a good headcount and open the conference to as many people as we can. PLUS, everyone who registers before May 15 will not only get early bird discounts, but will also be entered in a drawing for a free registration (via refund or extra)! Register on the website at http://scipy2015.scipy.org -------------------------------------------------------------------------- **SCIPY 2015 KEYNOTE SPEAKERS ANNOUNCED** Keynote speakers were just announced and include Wes McKinney, author of Pandas; Chris Wiggins, Chief Data Scientist for The New York Times; and Jake VanderPlas, director of research at the University of Washington's eScience Institute and core contributor to a number of scientific Python libraries including sci-kit learn and AstroML. -------------------------------------------------------------------------- **ENTER THE SCIPY JOHN HUNTER EXCELLENCE IN PLOTTING CONTEST - DUE 4/13** In memory of John Hunter, creator of matplotlib, we are pleased to announce the Third Annual SciPy John Hunter Excellence in Plotting Competition. This open competition aims to highlight the importance of quality plotting to scientific progress and showcase the capabilities of the current generation of plotting 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 is graciously sponsoring cash prizes up to $1,000 for the winners. We look forward to exciting submissions that push the boundaries of plotting! See details here: http://scipy2015.scipy.org/ehome/115969/276538/ Entries must be submitted by April 13, 2015 via e-mail to plotting-contest(a)scipy.org -------------------------------------------------------------------------- **CALENDAR AND IMPORTANT DATES** --Sprint, Birds of a Feather, Financial Aid and Talk submissions are open NOW --Apr 10, 2015: Talk and Poster submission deadline --Apr 13, 2015: Plotting contest submissions due --Apr 15, 2015: Financial aid application deadline --Apr 17, 2015: Tutorial schedule announced --May 1, 2015: General conference speakers & schedule announced --May 15, 2015 (or 150 registrants): Early-bird registration ends --Jun 1, 2015: BoF submission deadline --Jul 6-7, 2015: SciPy 2015 Tutorials --Jul 8-10, 2015: SciPy 2015 General Conference --Jul 11-12, 2015: SciPy 2015 Sprints

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IDE's for numpy development?
by Charles R Harris April 2, 2015

April 2, 2015

Hi All, In a recent exchange Mark Wiebe suggested that the lack of support for numpy development in Visual Studio might limit the number of developers attracted to the project. I'm a vim/console developer myself and make no claim of familiarity with modern development tools, but I wonder if such tools might now be available for Numpy. A quick google search turns up a beta plugin for Visual Studio, <https://pytools.codeplex.com/>, and there is an xcode IDE for the mac that apparently offers some Python support. The two things that I think are required are: 1) support for mixed C, python developement and 2) support for building and testing numpy. I'd be interested in information from anyone with experience in using such an IDE and ideas of how Numpy might make using some of the common IDEs easier. Thoughts? Chuck

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How to Force Storage Order
by Klemm, Michael April 1, 2015

April 1, 2015

Dear all, I have found a bug in one of my codes and the way it passes a Numpy matrix to MKL's dgemm routine. Up to now I was assuming that the matrixes are using C order. I guess I have to correct this assumption :-). I have found that the numpy.linalg.svd algorithm creates the resulting U, sigma, and V matrixes with Fortran storage. Is there any way to force these kind of algorithms to not change the storage order? That would make passing the matrixes to the native dgemm operation much easier. Cheers, -michael Dr.-Ing. Michael Klemm Senior Application Engineer Software and Services Group Developer Relations Division Phone +49 89 9914 2340 Cell +49 174 2417583 Intel GmbH Dornacher Strasse 1 85622 Feldkirchen/Muenchen, Deutschland Sitz der Gesellschaft: Feldkirchen bei Muenchen Geschaeftsfuehrer: Christian Lamprechter, Hannes Schwaderer, Douglas Lusk Registergericht: Muenchen HRB 47456 Ust.-IdNr./VAT Registration No.: DE129385895 Citibank Frankfurt a.M. (BLZ 502 109 00) 600119052

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Adding 'where' to ufunc methods?
by Jaime Fernández del Río April 1, 2015

April 1, 2015

This question on StackOverflow: http://stackoverflow.com/questions/29394377/minimum-of-numpy-array-ignoring… Got me thinking that I had finally found a use for the 'where' kwarg of ufuncs. Unfortunately it is only provided for the ufunc itself, but not for any of its methods. Is there any fundamental reason these were not implemented back in the day? Any frontal opposition to having them now? Jaime -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.

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