It has been a busy year, for various reasons. However, one loose end that urgently needs tidying up are an assortment of bits and pieces relating to the use of python as a computing language. Somewhere during the year the iPython notebook seemed to catch on. So, we have reworked the famous Coal Disaster changepoint model as a Bayesian model fitted with a Gibbs sampler using python. There are all sorts of nice features about the notebook:
- Code chunks can be run as a block (great for debugging, and checking out sensitivity to starting values
- The R magic tool lets you send objects to R for work there (I am still taking a long time to learn python – at the moment rather a lot of plotting functions are farmed out that way
- There is an online notebook viewing service available via the nbviewer website. The current version of my notebook can be viewed here: Gibbs Sampler Changepoint
One small issue I’m still struggling with in terms of the nbviewer is the ability to output directly to html – I can’t find a template file html-blogger for example. But still, this looks like a very promising tool indeed.