Mailman 3 March 2013 - NumPy-Discussion

SciPy John Hunter Excellence in Plotting Contest
by Michael Droettboom 08 Mar '13

08 Mar '13

Apologies for any accidental cross-posting. Email not displaying correctly? View it in your browser. <http://us1.campaign-archive1.com/?u=e91b4574d5d1709a9dc4f7ab7&id=999d7ba343…> Scientific Computing with Python-Austin, Texas-June 24-29, 2013 SciPy John Hunter Excellence in Plotting Contest In memory of John Hunter, we are pleased to announce the first 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. NumFOCUS is graciously sponsoring cash prizes for the winners in the following amounts: * 1st prize: $500 * 2nd prize: $200 * 3rd prize: $100 Instructions * Entries must be submitted by April 3 via e-mail <mailto:plotting-contest@scipy.org>. * Plots may be produced with any combination of Python-based tools (it is not required that they use matplotlib, for example). * Source code for the plot must be provided, along with a rendering of the plot in a vector format (PDF, PS, etc.). If the 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. * Entries will be judged on their clarity, innovation and aesthetics, but most importantly for their effectiveness in illuminating real scientific work. Entrants are encouraged to submit plots that were used during the course of research, rather than merely being hypothetical. * SciPy reserves the right to display the entry at the conference, use in any materials or on its website, providing attribution to the original author(s). Important dates: * April 3rd: Plotting submissions due * Monday-Tuesday, June 24 - 25: SciPy 2013 Tutorials, Austin TX * Wednesday-Thursday, June 26 - 27: SciPy 2013 Conference, Austin TX * Winners will be announced during the conference days * Friday-Saturday, June 27 - 28: SciPy 2013 Sprints, Austin TX & remote We look forward to exciting submissions that push the boundaries of plotting, in this, our first attempt at this kind of competition. The SciPy Plotting Contest Organizer -Michael Droettboom, Space Telescope Science Institute You are receiving this email because you subscribed to the mailing list or registered for the SciPy 2010 or SciPy 2011 conference in Austin, TX. Unsubscribe <http://scipy.us1.list-manage.com/unsubscribe?u=e91b4574d5d1709a9dc4f7ab7&id…> mdboom(a)gmail.com <mailto:mdboom@gmail.com> from this list | Forward to a friend <http://us1.forward-to-friend1.com/forward?u=e91b4574d5d1709a9dc4f7ab7&id=99…> | Update your profile <http://scipy.us1.list-manage.com/profile?u=e91b4574d5d1709a9dc4f7ab7&id=069…> *Our mailing address is:* Enthought, Inc. 515 Congress Ave. Austin, TX 78701 Add us to your address book <http://scipy.us1.list-manage.com/vcard?u=e91b4574d5d1709a9dc4f7ab7&id=069dc…> /Copyright (C) 2013 Enthought, Inc. All rights reserved./ -- Michael Droettboom http://www.droettboom.com/

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Definition of dot function
by Mayank Daga 07 Mar '13

07 Mar '13

Hi, Can someone point me to the definition of dot() in the numpy source? The only instance of 'def dot()' I found was in numpy/ma/extras.py but that does not seem to be the correct one. ~mayank -- Mayank Daga "Nothing Succeeds Like Success"

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feature tracking in numpy/scipy
by Scott Collis 07 Mar '13

07 Mar '13

Good afternoon list, I am looking at feature tracking in a 2D numpy array, along the lines of Dixon and Wiener 1993 (for tracking precipitating storms) Identifying features based on threshold is quite trivial using ndimage.label b_fld=np.zeros(mygrid.fields['rain_rate_A']['data'].shape) rr=10 b_fld[mygrid.fields['rain_rate_A']['data'] > rr]=1.0 labels, numobjects = ndimage.label(b_fld[0,0,:,:]) (note mygrid.fields['rain_rate_A']['data'] is dimensions time,height, y, x) using the matplotlib contouring and fetching the vertices I can get a nice list of polygons of rain rate above a certain threshold… Now from here I can just go and implement the Dixon and Wiener methodology but I thought I would check here first to see if anyone know of a object/feature tracking algorithm in numpy/scipy or using numpy arrays (it just seems like something people would want to do!).. i.e. something that looks back and forward in time and identifies polygon movement and identifies objects with temporal persistence.. Cheers! Scott Dixon, M., and G. Wiener, 1993: TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting—A Radar-based Methodology. Journal of Atmospheric and Oceanic Technology, 10, 785–797, doi:10.1175/1520-0426(1993)010<0785:TTITAA>2.0.CO;2. http://journals.ametsoc.org/doi/abs/10.1175/1520-0426%281993%29010%3C0785%3…

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polyfit with fixed points
by Jaime Fernández del Río 07 Mar '13

07 Mar '13

A couple of days back, answering a question in StackExchange ( http://stackoverflow.com/a/15196628/110026), I found myself using Lagrange multipliers to fit a polynomial with least squares to data, making sure it went through some fixed points. This time it was relatively easy, because some 5 years ago I came across the same problem in real life, and spent the better part of a week banging my head against it. Even knowing what you are doing, it is far from simple, and in my own experience very useful: I think the only time ever I have fitted a polynomial to data with a definite purpose, it required that some points were fixed. Seeing that polyfit is entirely coded in python, it would be relatively straightforward to add support for fixed points. It is also something I feel capable, and willing, of doing. * Is such an additional feature something worthy of investigating, or will it never find its way into numpy.polyfit? * Any ideas on the best syntax for the extra parameters? Thanks, Jaime -- (\__/) ( O.o) ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale en sus planes de dominación mundial.

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scipy.optimize.fminbound bound violation
by Alan G Isaac 07 Mar '13

07 Mar '13

Under what conditions should I expect fminbound to call the supplied function with argument values substantially outside the user-provided bounds? Thanks, Alan Isaac

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Numpy deprecation schedule
by Nathaniel Smith 06 Mar '13

06 Mar '13

A number of items on the 1.8 todo list are reminders to remove things that we deprecated in 1.7, and said we would remove in 1.8, e.g.: https://github.com/numpy/numpy/issues/596 https://github.com/numpy/numpy/issues/294 But, since 1.8 is so soon after 1.7, we probably shouldn't actually do that. I suggest we switch to a time-based deprecation schedule, where instead of saying "this will be removed in N releases" we say "this will be removed in the first release on or after (now+N months)". I also suggest that we set N=12, because it's a round number, it roughly matches numpy's historical release cycle, and because AFAICT that's the number that python itself uses for core and stdlib deprecations. Thoughts? -n

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scipy.weave + nose testing no longer works with numpy 1.7.0
by Marcel Stimberg 06 Mar '13

06 Mar '13

Hi, I noticed that our unit tests running under nose and using scipy.weave started to fail with numpy 1.7.0 because of a change in numpy.distutils.exec_command (called by scipy.weave) which now assumes that sys.stdout always provides a fileno function (which fails because nose redirect stdout to a cStringIO). I guess the combination of scipy.weave and nose is not that unusual for scientific software, maybe 1.7.1 could make the exec_command a bit more robust in that regard? I filed the issue as #2999 in github (including a simple example triggering the error): https://github.com/numpy/numpy/issues/2999 Thanks Marcel

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GSOC 2013
by Todd 06 Mar '13

06 Mar '13

Is numpy planning to participate in GSOC this year, either on their own or as a part of another group? If so, should we start trying to get some project suggestions together?

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a question about freeze on numpy 1.7.0
by Gelin Yan 06 Mar '13

06 Mar '13

Hi All When I used numpy 1.7.0 with cx_freeze 4.3.1 on windows, I quickly found out even a simple "import numpy" may lead to program failed with following exception: "AttributeError: 'module' object has no attribute 'sys' After a poking around some codes I noticed /numpy/core/__init__.py has a line 'del sys' at the bottom. After I commented this line, and repacked the whole program, It ran fine. I also noticed this 'del sys' didn't exist on numpy 1.6.2 I am curious why this 'del sys' should be here and whether it is safe to omit it. Thanks. Regards gelin yan

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Help trying to fix issue 368 on Github (math functions fail confusingly on long integers (and object arrays generally))
by Dan Blanchard 06 Mar '13

06 Mar '13

Hi, I've been trying to take a crack at fixing https://github.com/numpy/numpy/issues/368, and I think I've identified all of the affected functions and even a potential fix, but I'm new to the Python C API and the numpy source, so if anyone has time to look at the discussion on Github and chime in with suggestions, I'd be glad to help finish getting this patched up. It is currently very frustrating that many of the math functions do not work with longs. Thanks, Dan

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