2011-06-23

scicoder

I spent most of the day at scicoder, Demetri Muna's workshop for astronomers who code. I spoke about the practice of building academic software systems—pair coding, functional testing, and using packages vs writing your own—and then went to lunch with a small group. On the writing your own point, I said that it is a good idea to both write your own and use pre-built packages, because you learn so much by writing your own, and you get so much performance out of (well built) industrial-strength code (though you can use your own if performance isn't a problem). Partly my remarks are motivated by the point that academic programming is about learning, not just shipping. In the afternoon, Muna taught us about using R for browsing data and making plots. Tsalmantza and I wrote all of our heteroscedastic matrix factorization stuff in R, so I was already a believer, though Python is my one true love.

2 comments:

  1. This entire post is just an excuse to use the word "heteroscedastic"

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  2. I met a biostatistician on a plane the other day, and when I told him I program in C++, Octave and Python he said I should try R. A lot of statistical folk seem to love it. I suspect three languages may be enough though, and my time would be better spent getting really good at those.

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