1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86
|
Metadata-Version: 2.1
Name: emcee
Version: 3.1.6
Summary: The Python ensemble sampling toolkit for MCMC
Home-page: https://emcee.readthedocs.io
Author: Daniel Foreman-Mackey
Author-email: foreman.mackey@gmail.com
Maintainer: Daniel Foreman-Mackey
Maintainer-email: foreman.mackey@gmail.com
License: MIT
Project-URL: Source, https://github.com/dfm/emcee
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Description-Content-Type: text/x-rst
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: numpy
Provides-Extra: extras
Requires-Dist: h5py; extra == "extras"
Requires-Dist: scipy; extra == "extras"
Provides-Extra: tests
Requires-Dist: pytest; extra == "tests"
Requires-Dist: pytest-cov; extra == "tests"
Requires-Dist: coverage[toml]; extra == "tests"
emcee
=====
**The Python ensemble sampling toolkit for affine-invariant MCMC**
.. image:: https://img.shields.io/badge/GitHub-dfm%2Femcee-blue.svg?style=flat
:target: https://github.com/dfm/emcee
.. image:: https://github.com/dfm/emcee/workflows/Tests/badge.svg
:target: https://github.com/dfm/emcee/actions?query=workflow%3ATests
.. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat
:target: https://github.com/dfm/emcee/blob/main/LICENSE
.. image:: http://img.shields.io/badge/arXiv-1202.3665-orange.svg?style=flat
:target: https://arxiv.org/abs/1202.3665
.. image:: https://coveralls.io/repos/github/dfm/emcee/badge.svg?branch=main&style=flat&v=2
:target: https://coveralls.io/github/dfm/emcee?branch=main
.. image:: https://readthedocs.org/projects/emcee/badge/?version=latest
:target: http://emcee.readthedocs.io/en/latest/?badge=latest
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) <http://cims.nyu.edu/~weare/papers/d13.pdf>`_.
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 <http://emcee.readthedocs.io/>`_.
Attribution
-----------
Please cite `Foreman-Mackey, Hogg, Lang & Goodman (2012)
<https://arxiv.org/abs/1202.3665>`_ 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.
|