SciPy 2013 From A Distance

SciPy 2013 was the twelfth annual Scientific Computing with Python conference, held this year in Austin, TX, from June 24 to June 29. I was unable to attend, so I am giving this report from a distance based on the meeting web page, conversations with attendees and the Twitter feed (hashtag #scipy2013). I was not able to unearth many blog postings –  am sure there must have been plenty, and if readers know of any, please send me links to them.

The Conference has special mini-sessions on the application of Python to specific disciplines: Meteorology, climatology, and atmospheric and oceanic science, Medical imaging, Bio-informatics, GIS – Geospatial Data Analysis, and Astronomy and astrophysics. The astronomy talks were as follows:

The conference also included specialized tracks on Machine Learning and Reproducible Science,  and three keynote presentations:

The program contained an extensive program of tutorials, with presentations on such topics as Statistical Data Analysis in Python, Data Processing with Python, Diving into NumPy code, and Version Control and Unit Testing for Scientific Software (I was delighted to see a tutorial on best practices).  Links to videos of these sessions, along with tutorial descriptions an links to documentation, are available from the tutorials page. Here is part 1 of 3 of the Data Processing with Python session, which I particularly liked:

I was hoping that the conference web page would include links to talks, but fortunately many links have been posted on Twitter (check out hashtag #scipy2013  to see the latest).  I learned that all videos have now been posted on-line at . Here is one talk I particularly enjoyed:  Astropy, growing a community-based software system for astronomy, by Erik Tollerud, Michael Droettboom and Thomas Robitaille

I also enjoyed Chris Beaumont’s talk on Multidimensional Data Exploration with Glue:

This entry was posted in Astronomy, computer videos, computing videos, cyberinfrastructure, Data mining, High performance computing, informatics, information sharing, Machine learning, Open Access, programming, Python, social media, social networking, software engineering, software maintenance, software sustainability, statistical analysis, Uncategorized, visualization and tagged , , , , , , , , , , , , , , , , . Bookmark the permalink.

6 Responses to SciPy 2013 From A Distance

  1. Matt Turk says:

    I attended the conference and found it to be full of very excellent talks, great attendees and exciting discussions. In the astronomy vein, Sam Skillman gave a very nice talk about yt ( ) as well, and using it to volume render very large astrophysical datasets. His talk can be found here:

  2. Thanks for your post! Glad you were able to follow along through the internet and twitter. Now I have a good post to point to when people tell me that Twittier is useless =P

    The talks will be linked up on the webpage, we just updated the YouTube videos first to keep people interested. I think most people are still recovering from the week, so blog posts are slowly rolling out.

  3. Pingback: Why you should write buggy software with as few features as possible (no, really!) | Astronomy Computing Today

  4. Tony Silva says:

    Reblogged this on Astronovae.

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