Skip to main content

Scipy advanced tutorials results

We recently conducted a poll on Doodle, soliciting feedback on the preferred topics for the advanced track, which is meant to contain 2 days with 8 2-hour sessions focusing on one specific topic at a time. The table below shows the complete results, which I've only sorted for convenient viewing and anonymized (the raw Doodle output contains the names given by each person voting). If anyone would like the raw spreadsheet, just drop me a line.

The score was computed as #yes-#no (i.e., yes=+1, neutral=0, no=-1), from a total of 30 responses, and the results are in the table below, ranked from highest to lowest score. In my personal opinion, all the topics offered would have made for very good and interesting tutorials, but the point of asking for feedback is obviously to follow it to some degree, which we will now do.

I think it's worth noting --though not particularly surprising-- that the ranking roughly follows the generality of the tools: matplotlib and numpy are at the top, with finite elements and graph theory at the bottom. While I personally use NetworkX and love it, it's a specialized tool that for many probably offers no compelling reason to learn it, while pretty much every single numerical python user needs numpy and matplotlib. We are now in the process of contacting possible speakers for the top topics, and will communicate on the mailing list a final list of topics once we have confirmed speakers for all.  
  

Yes Neutral No Score Rank
Advanced topics in matplotlib use 18 10 2 16 1
Advanced numpy 18 10 2 16 2
Designing scientific interfaces with Traits 15 11 4 11 3
Mayavi/TVTK 13 11 6 7 4
Cython 14 8 8 6 5
Symbolic computing with sympy 15 6 9 6 6
Statistics with Scipy 9 15 6 3 7
Using GPUs with PyCUDA 13 7 10 3 8
Testing strategies for scientific codes 11 11 8 3 9
Parallel computing in Python and mpi4py 12 8 10 2 10
Sparse Linear Algebra with Scipy 9 12 9 0 11
Structured and record arrays in numpy 8 14 8 0 12
Design patterns for efficient iterator-based scientific codes 9 7 14 -5 13
Sage 8 6 16 -8 14
The TimeSeries scikit 4 13 13 -9 15
Hermes: high order Finite Element Methods 6 9 15 -9 16
Graph theory with NetworkX 5 9 16 -11 17
Labels:

Comments

Post a Comment

Popular posts from this blog

Blogging with the IPython notebook

Update (May 2014): Please note that these instructions are outdated. while it is still possible (and in fact easier) to blog with the Notebook, the exact process has changed now that IPython has an official conversion framework. However, Blogger isn't the ideal platform for that (though it can be made to work). If you are interested in using the Notebook as a tool for technical blogging, I recommend looking at Jake van der Plas' Pelican support or Damián Avila's support in Nikola . Update: made full github repo for blog-as-notebooks, and updated instructions on how to more easily configure everything and use the newest nbconvert for a more streamlined workflow. Since the notebook was introduced with IPython 0.12 , it has proved to be very popular, and we are seeing great adoption of the tool and the underlying file format in research and education. One persistent question we've had since the beginning (even prior to its official release) was whether it would...
13 comments
Read more

Help save open space in the Bay Area by protecting Knowland Park from development

Vote NO on new Tax Measure A1 Update:  there is now evidence that Zoo officials have actually violated election laws  in their zeal to promote measure A1. I normally only blog about technical topics, but the destruction of a beautiful piece of open space in the Bay Area is imminent, and I want to at least do a little bit to help prevent this disaster. In short: there's a tax measure on the November ballot, Measure A1 , that would impose a parcel tax on all residences and businesses in Alameda County to fund the Oakland Zoo for the next 25 years .  The way the short text on the ballot is worded makes it appear as something geared towards animal care for a cash-strapped Zoo.  The sad reality is that the full text of the measure allows the Zoo to use these funds for a very controversial expansion plan that includes a 34,000 sq. ft. visitor center, gift shop and restaurant serviced by a ski gondola atop one of the last pristine remaining ridges in Knowland Park, ...
5 comments
Read more

An ambitious experiment in Data Science takes off: a biased, Open Source view from Berkeley

Today, during a White House OSTP event combining government, academia and industry, the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation announced a $37.8M funding commitment to build new data science environments. This caps a year's worth of hard work for us at Berkeley, and even more for the Moore and Sloan teams, led by Vicki Chandler , Chris Mentzel and Josh Greenberg : they ran a very thorough selection process to choose three universities to participate in this effort. The Berkeley team was led by Saul Perlmutter , and we are now thrilled to join forces with teams at the University of Washington and NYU, respectively led by Ed Lazowska and Yann LeCun . We have worked very hard on this in private, so it's great to finally be able to publicly discuss what this ambitious effort is all about. Most of the UC Berkeley BIDS team, from left to right: Josh Bloom, Cathryn Carson, Jas Sekhon, Saul Perlmutter, Erik Mitchell, Kimmen Sjölander, Jim Sethia...
5 comments
Read more