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Kick ass affine-invariant ensemble MCMC sampling

Project description

The Python ensemble sampling toolkit for affine-invariant MCMC

https://secure.travis-ci.org/dfm/emcee.png?branch=master

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

1.1.0 (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.

Project details


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emcee-1.1.0.tar.gz (17.1 kB view hashes)

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