(c) 2016 Brendon J. Brewer and Jared Tobin
There are a few examples included that you can run using Stack as follows:
$ stack test NestedSampling-hs:test:spikeslab $ stack test NestedSampling-hs:test:rosenbrock
.. and so on. Check the .cabal file for a list of examples, the code for which
can always be found in the
Running any of these examples will log sampling progress to stdout and also dump output information to a couple of CSV files:
nested_sampling_info.csvincludes log x, log prior weight, log likelihood, current log evidence estimate, and current information estimate by sampler iteration.
nested_sampling_parameters.csvincludes parameter information (where one line = one sample).
You can then run a Python postprocessing script to generate some plots, and a text file of posterior weights:
$ python showresults.py
This script requires NumPy, Matplotlib, and Pandas.