Highlights from EuroSciPy

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In July, Agile reported from SciPy in Austin, Texas, one of several annual conferences for people writing scientific software in the Python programming language. I liked it so much I was hungry for more, so at the end of my recent trip to Europe I traveled to the city of Cambridge, UK, to participate in EuroSciPy.

The conference was quite a bit smaller than its US parent, but still offered 2 days of tutorials, 2 days of tech talks, and a day of sprints. It all took place in the impressive William Gates Building, just west of the beautiful late Medieval city centre, and just east of Schlumberger's cool-looking research centre. What follows are my highlights...

Okay you win, Julia

Steven Johnson, an applied mathematician at MIT, gave the keynote on the first morning. His focus was Julia, the current darling of the scientific computing community, and part of a new ecosystem of languages that seek to cooperate, not compete. I'd been sort of ignoring Julia, in the hope that it might go away and let me focus on Python, the world's most useful language, and JavaScript, the world's most useful pidgin... but I don't think scientists can ignore Julia much longer.

I started writing about what makes Julia so interesting, but it turned into another post — up next. Spoiler: it's speed. [Edit: Here is that post! Julia in a nutshell.]

Learning from astrophysics

The Astropy project is a truly inspiring community — in just 2 years it has synthesized a dozen or so disparate astronomy libraries into an increasingly coherent and robust toolbox for astronomers and atrophysicists. What does this mean?

  • The software is well-tested and reliable.
  • Datatypes and coordinate systems are rich and consistent.
  • Documentation is useful and evenly distributed.
  • There is a tangible project to rally developers and coordinate funding.

Geophysicists might even be interested in some of the components of Astropy and the related SunPy project, for example:

  • astropy.units, just part of the ever-growing astropy library, as a unit conversion and quantity handler to compare with pint.
  • sunpy datatypes map and spectra for types of data that need special methods.
  • asv is a code-agnostic benchmarking library, a bit like freebench.

Speed dating for scientists

Much of my work is about connecting geoscientists in meaningful collaboration. There are several ways to achieve this, other than through project work: unsessions, wikis, hackathons, and so on. Now there's another way: speed dating.

Okay, it doesn't quite get to the collaboration stage, but Vaggi and his co-authors shared an ingenious way to connect people and give their professional relationship the best chance of success (an amazing insight, a new algorithm, or some software). They asked everyone at a small 40-person conference to complete a questionnaire that asked, among other things, what they knew about, who they knew, and, crucially, what they wanted to know about. Then they applied graph theory to find the most desired new connections (the matrix shows the degree of similarity of interests, red is high), and gave the scientists five 10-minute 'dates' with scientists whose interests overlapped with theirs, and five more with scientists who knew about fields that were new to them. Brilliant! We have to try this at SEG.

Vaggi, F, T Schiavinotto, A Csikasz-Nagy, and R Carazo-Salas (2014). Mixing scientists at conferences using speed dating. Poster presentation at EuroSciPy, Cambridge, UK, August 2014. Code on GitHub.

Vaggi, F, T Schiavinotto, J Lawson, A Chessel, J Dodgson, M Geymonat, M Sato, R Carazo Salas, A Csikasz Nagy (2014). A network approach to mixing delegates at meetings. eLife, 3. DOI: 10.7554/eLife.02273

Other highlights

  • sumatra to generate and keep track of simulations.
  • vispy, an OpenGL-based visualization library, now has higher-level, more Pythonic components.
  • Ian Osvald's IPython add-on for RAM usage.
  • imageio for lightweight I/O of image files.
  • nbagg backend for matplotlib version 1.4, bringin native (non-JS) interactivity.
  • An on-the-fly kernel chooser in upcoming IPython 3 (currently in dev).

All in all, the technical program was a great couple of days, filled with the usual note-taking and hand-shaking. I had some good conversations around my poster on modelr. I got a quick tour of the University of Cambridge geophysics department (thanks to @lizzieday), which made me a little nostalgic for British academic institutions. A fun week!