This release is a pre-release and may not be stable for production use.
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 emcee.readthedocs.io.
Attribution
Please cite Foreman-Mackey, Hogg, Lang & Goodman (2012) if you find this code useful in your research. The BibTeX entry for the paper is:
@article{emcee,
author = {{Foreman-Mackey}, D. and {Hogg}, D.~W. and {Lang}, D. and {Goodman}, J.},
title = {emcee: The MCMC Hammer},
journal = {PASP},
year = 2013,
volume = 125,
pages = {306-312},
eprint = {1202.3665},
doi = {10.1086/670067}
}
License
Copyright 2010-2021 Dan Foreman-Mackey and contributors.
emcee is free software made available under the MIT License. For details see the LICENSE file.
1 maintainer
Release files for emcee 3.1.5rc1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| emcee-3.1.5rc1.tar.gz | 2.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| emcee-3.1.5rc1-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 2.9 MB
Release files / emcee-3.1.5rc1.tar.gz
| Download URL | emcee-3.1.5rc1.tar.gz |
|---|---|
| Size | 2.9 MB |
| Tags | Source |
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Release files / emcee-3.1.5rc1-py2.py3-none-any.whl
| Download URL | emcee-3.1.5rc1-py2.py3-none-any.whl |
|---|---|
| Size | 47.3 kB |
| Tags | Python 2 Python 3 |
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