The Python ensemble sampling toolkit for affine-invariant MCMC
emcee is a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the Astrophysics literature.
emcee was developed by Daniel Foreman-Mackey at NYU with contributions from Dustin Lang.
Read the docs at danfm.ca/emcee. You can also look at these docs after you've cloned the repository by running
python -m SimpleHTTPServer 5000
in the docs directory and navigating to
localhost:5000.
Please cite Foreman-Mackey, Hogg, Lang & Goodman (2012) if you find this code useful in your research.
emcee is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License version 2 as published by the Free Software Foundation.
emcee is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with emcee. If not, see http://www.gnu.org/licenses/.