Mailman 3 February 2016 - SciPy-Dev

dense output option in integrate.ode
by Evgeni Burovski Feb. 20, 2017

Feb. 20, 2017

Hi David, Hi Jim, > I am new to SciPy-dev. Will the dense output option in scipy.integrate.ode > become available in 0.17.0? This is a feature already available in the > original FORTAN, but wasn't implemented in the wrapper. If the feature is sent as a pull request against the scipy master branch, the PR is reviewed by the maintainers of the integrate package and merged into master before the release split, then yes, it would be available in 0.17.0. So far I do not see any progress towards it. > I wrote these dense output extensions that you listed: > > https://github.com/jddmartin/scipy/tree/dense_output_from_dopri5_and_dop853 > https://github.com/jddmartin/dense_output_example_usage > > but I didn't issue any pull request to scipy. I sent this message to the > scipy developers list: > http://article.gmane.org/gmane.comp.python.scientific.devel/19635/ > explaining the changes. I was hoping for some feedback before issuing a > pull request. Ah, I see that the email likely fell through the cracks back in April. Sorry about that. You might want to ping that email thread once more or send a pull request on github (or both). <snip> Cheers, Evgeni

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PR for Scipy developers guide
by Ralf Gommers Feb. 26, 2016

Feb. 26, 2016

Hi all, https://github.com/scipy/scipy/pull/5424 adds a developers guide to the documentation. The PR was open for a while, but I've added some sections and hooked it up to the rest of the docs, so it's ready for review/merge. There are no proposals for changes in there, it's just documenting how we do things now. Still, it would be good to get a few pairs of eyes on it. Cheers, Ralf

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ANN: SciPy (Scientific Python) 2016 Conference Call for Talk / Tutorial Proposals Open Until 3/25
by Courtenay Godshall (Enthought) Feb. 26, 2016

Feb. 26, 2016

**SciPy 2016 Conference (Scientific Computing with Python) Announcement** *Call for Proposals: Submit Your Tutorial and Talk Ideas by March 25, 2015 at http://scipy2016.scipy.org. <http://www.scipy2016.scipy.org> SciPy 2016, the 15th annual Scientific Computing with Python conference, will be held July 11-17, 2016 in Austin, Texas. SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conference brings together over 650 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The full program will consist of <http://scipy2016.scipy.org/ehome/146062/332967/?&&> 2 days of tutorials (July 11-12), <http://scipy2016.scipy.org/ehome/146062/332968/?&&> 3 days of talks (July 13-15), and 2 days of <http://scipy2016.scipy.org/ehome/146062/332969/?&&> developer sprints (July 16-17). More info is available on the conference website at <http://www.scipy2016.scipy.org> http://scipy2016.scipy.org (where you can sign up for the mailing list); or follow <https://twitter.com/scipyconf> @scipyconf on Twitter. We hope you'll join us - early bird registration is open until May 22, 2016 at <http://scipy2016.scipy.org/ehome/146062/332936/?&&> http://scipy2016.scipy.org/ehome/146062/332936/?&& We encourage you to submit tutorial or talk proposals in the categories below; please also share with others who you'd like to see participate! Submit via the conference website: <http://www.scipy2016.scipy.org> http://scipy2016.scipy.org. ---------------------------------------------------------------------------- ------------------------- *SUBMIT A SCIPY 2016 TUTORIAL PROPOSAL - DUE MARCH 21, 2016* ---------------------------------------------------------------------------- ------------------------- Details and submission here: <http://scipy2016.scipy.org/ehome/146062/332967/?&&> http://scipy2016.scipy.org/ehome/146062/332967/?&& These sessions provide extremely affordable access to expert training, and consistently receive fantastic feedback from participants. We're looking for submissions on topics from introductory to advanced - we'll have attendees across the gamut looking to learn. Whether you are a major contributor to a scientific Python library or an expert-level user, this is a great opportunityto share your knowledge and stipends are available. ---------------------------------------------------------------------------- --------------------------------- **SUBMIT A SCIPY 2016 TALK / POSTER PROPOSAL - DUE MARCH 25, 2016* ---------------------------------------------------------------------------- --------------------------------- Details and submission here: <http://scipy2016.scipy.org/ehome/146062/332968/?&&> http://scipy2016.scipy.org/ehome/146062/332968/?&& SciPy 2016 will include 3 major topic tracks and 8 mini-symposia tracks. Major topic tracks include: - Scientific Computing in Python - Python in Data Science (Big data and not so big data) - High Performance Computing Mini-symposia will include the applications of Python in: - Earth and Space Science - Engineering - Medicine and Biology - Social Sciences - Special Purpose Databases - Case Studies in Industry - Education - Reproducibility If you have any questions or comments, feel free to contact us at: scipy-organizers(a)scipy.org ----------------------------------------------------------- **SCIPY 2016 REGISTRATION IS OPEN** ----------------------------------------------------------- Please register early. SciPy early bird registration until May 22, 2016! Register at <http://scipy2016.scipy.org> http://scipy2016.scipy.org. Plus, enter our t-shirt design contest to win a free registration. (Send a vector art file to scipy(a)enthought.com by March 31 to enter).

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removing pure python KDTree implementation
by Ralf Gommers Feb. 25, 2016

Feb. 25, 2016

Hi all, For a long time we've had both a Python (KDTree) and a Cython/C++ (cKDTree) version of a k-d tree structure in scipy.spatial. The cKDTree version reached feature-parity with KDTree in 0.12.0, and new features are being added regularly now. So keeping the orders of magnitude slower pure Python version seems to be a bit pointless - only adds to a maintenance burden and to giving users an unnecessary choice to make. So proposal: remove the pure Python code and make KDTree an alias for cKDTree. This can be done straight away. For the future it may also be desirable to get rid of the duplicate name. The issue then is which one to keep. KDTree is nicer, but it would require users who have picked the fast version now to change their code. So maybe just deprecate one in documentation, but keep both names working? Ralf

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BayesPy.Org
by Robert Lucente Feb. 24, 2016

Feb. 24, 2016

People are probably aware of BayesPy.Org but just in case.

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ANN: SfePy 2016.1
by Robert Cimrman Feb. 24, 2016

Feb. 24, 2016

I am pleased to announce release 2016.1 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method or by the isogeometric analysis (preliminary support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: http://groups.google.com/group/sfepy-devel Git (source) repository, issue tracker, wiki: http://github.com/sfepy Highlights of this release -------------------------- - major simplification of finite element field code - automatic checking of shapes of term arguments - improved mesh parametrization code and documentation - support for fieldsplit preconditioners of PETSc For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Best regards, Robert Cimrman on behalf of the SfePy development team --- Contributors to this release in alphabetical order: Robert Cimrman Vladimir Lukes

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Numpy 1.11.0rc1 released.
by Charles R Harris Feb. 23, 2016

Feb. 23, 2016

Hi All, I'm delighted to announce the release of Numpy 1.11.0rc1. Hopefully the issues discovered in 1.11.0b3 have been dealt with and this release can go on to become the official release. Source files and documentation can be found on Sourceforge <https://sourceforge.net/projects/numpy/files/NumPy/1.11.0rc1/>, while source files and OS X wheels for Python 2.7, 3.3, 3.4, and 3.5 can be installed from Pypi. Please test thoroughly. Chuck

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welcome Andrew Nelson and Eric Quintero to core team
by Ralf Gommers Feb. 22, 2016

Feb. 22, 2016

Hi all, On behalf of the Scipy developers I'd like to welcome Andrew Nelson and Eric Quintero as members of the core dev team. Andrew has been contributing for ~2 years to scipy.optimize. He's the author of the differential_evolution global optimizer and adapted the ampgo testsuite functions to the benchmark suite (merged just last week) - https://github.com/scipy/scipy/pulls/andyfaff. Eric has been contributing for ~1 year to scipy.signal. He's the author of a number of the spectral analysis functions - https://github.com/scipy/scipy/pulls/e-q. I'm looking forward to their continued contributions! Cheers, Ralf

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Where do I start?
by Shashank Gandham Feb. 22, 2016

Feb. 22, 2016

I am interested in contributing to numpy, I have never contributed to an open source project. How do I start?

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welcome Eric Larson and Ian Henriksen to core team
by Ralf Gommers Feb. 22, 2016

Feb. 22, 2016

Hi all, On behalf of the Scipy developers I'd like to welcome Eric Larson and Ian Henriksen as members of the core dev team. Eric has been contributing for ~1.5 years, mostly to scipy.signal. He recently added upfirdn and polyphase resampling, and was one of the authors of the marathon PR on second-order-sections filtering (gh-3717). Ian has also been contributing for ~1.5 years, mostly to scipy.linalg. He is the author of the Cython API for BLAS/LAPACK. I'm looking forward to their continued contributions! Cheers, Ralf

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