A simple python 2 implementation of the Bayesian approach to fitting a straight
line to two-dimensional data with covariant errors on the two coordinates and some outliers
(see e.g. Hogg, Bovy & Lang (2010) for discussion). Depends
on numpy, scipy, matplotlib and emcee.
Install by running
pip install https://github.com/anguswilliams91/LinearBayes/archive/master.zip
If you don't have emcee, it will be installed automatically. The function that
does all of the work is called fit_data and has an explanatory docstring.
Example snippet, which runs a test on some mock data and produces two plots (shown below):
import linear_bayes as lb
lb.mock_test(nproc=8) #run the test case and parallelise over 8 threads
