Kick ass affine-invariant ensemble MCMC sampling
Project description
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.
Documentation
Read the docs at danfm.ca/emcee.
Attribution
Please cite Foreman-Mackey, Hogg, Lang & Goodman (2012) if you find this code useful in your research.
License
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/](http://www.gnu.org/licenses/).
Changelog
1.1.1 (2012-07-30)
Fixed bug related to metadata blobs. The sample function was yielding the blobs object even when it wasn’t expected.
1.1.0 (2012-07-28)
Allow the lnprobfn to return arbitrary “blobs” of data as well as the log-probability.
Python 3 compatible (thanks Alex Conley)!
Various speed ups and clean ups in the core code base.
New documentation with better examples and more discussion.
1.0.1 (2012-03-31)
Fixed transpose bug in the usage of acor in EnsembleSampler.
1.0.0 (2012-02-15)
Initial release.
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