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out-of-core processing and plotting of MultiNest output

Project description

=======
barrett
=======

barrett is a software package meant to process and visualise the output of the nested sampling
algorithm MultiNest. There are several packages already on the market for this, but barrett's
main differential feature is out-of-core processing so the code can handle very large datasets.

Specific technologies: HDF5, and Python (h5py, scipy, numpy, matplotlib).

Usage
-----

barrett is split into four submodules:

+ barrett.data implements methods for modifying data (e.g. log, change units) or calculate
depended variables (e.g. mean squark mass)

+ barrett.posterior is for calculating and plot the one or two dimensional marginal
posterior distribution.

+ barrett.profilelikelihood is for calculating and plot the one or two dimensional profile
likelihood.

+ barrett.util contain various utility functions most notable convert_chain() which converts
the plain text MultiNest output to the HDF5 format used by barrett.

As for parallelisation; writing to the same hdf5 file is strongly discouraged. Reading the file
is however perfectly fine. So posterior/profilelikelihood module is perfectly parallelisable.
The code itself is not parallelised, instead I recommend using Python's multiprocessing module to
producing several plots in parallell. In most system tested the plotting is CPU bound, your
mileage may vary.

Installation
------------

Barrett is available on PyPI and can be installed using pip

pip install barrett

Cite
----
If you use barrett in your research please cite arXiv:1608.00990:

@article{2016arXiv160800990L,
author = {Liem, Sebastian},
title = "{Barrett: out-of-core processing of MultiNest output}",
archivePrefix = "arXiv",
eprint = {1608.00990},
primaryClass = "stat.CO",
year = 2016
}

Example
-------

Please check the example directory for plot.py for an, you guessed it, example.



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