emcee


Nameemcee JSON
Version 3.1.5 PyPI version JSON
download
home_pagehttps://emcee.readthedocs.io
SummaryThe Python ensemble sampling toolkit for MCMC
upload_time2024-04-16 14:26:29
maintainerDaniel Foreman-Mackey
docs_urlNone
authorDaniel Foreman-Mackey
requires_pythonNone
licenseMIT
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            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.

            

Raw data

            {
    "_id": null,
    "home_page": "https://emcee.readthedocs.io",
    "name": "emcee",
    "maintainer": "Daniel Foreman-Mackey",
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": "foreman.mackey@gmail.com",
    "keywords": null,
    "author": "Daniel Foreman-Mackey",
    "author_email": "foreman.mackey@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/d0/f2/fa3e87ae09c3c7483997e6e92537a14b48c8d4d15523d8f51b1b75d23b8d/emcee-3.1.5.tar.gz",
    "platform": null,
    "description": "emcee\n=====\n\n**The Python ensemble sampling toolkit for affine-invariant MCMC**\n\n.. image:: https://img.shields.io/badge/GitHub-dfm%2Femcee-blue.svg?style=flat\n    :target: https://github.com/dfm/emcee\n.. image:: https://github.com/dfm/emcee/workflows/Tests/badge.svg\n    :target: https://github.com/dfm/emcee/actions?query=workflow%3ATests\n.. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat\n    :target: https://github.com/dfm/emcee/blob/main/LICENSE\n.. image:: http://img.shields.io/badge/arXiv-1202.3665-orange.svg?style=flat\n    :target: https://arxiv.org/abs/1202.3665\n.. image:: https://coveralls.io/repos/github/dfm/emcee/badge.svg?branch=main&style=flat&v=2\n    :target: https://coveralls.io/github/dfm/emcee?branch=main\n.. image:: https://readthedocs.org/projects/emcee/badge/?version=latest\n    :target: http://emcee.readthedocs.io/en/latest/?badge=latest\n\n\nemcee is a stable, well tested Python implementation of the affine-invariant\nensemble sampler for Markov chain Monte Carlo (MCMC)\nproposed by\n`Goodman & Weare (2010) <http://cims.nyu.edu/~weare/papers/d13.pdf>`_.\nThe code is open source and has\nalready been used in several published projects in the Astrophysics\nliterature.\n\nDocumentation\n-------------\n\nRead the docs at `emcee.readthedocs.io <http://emcee.readthedocs.io/>`_.\n\nAttribution\n-----------\n\nPlease cite `Foreman-Mackey, Hogg, Lang & Goodman (2012)\n<https://arxiv.org/abs/1202.3665>`_ if you find this code useful in your\nresearch. The BibTeX entry for the paper is::\n\n    @article{emcee,\n       author = {{Foreman-Mackey}, D. and {Hogg}, D.~W. and {Lang}, D. and {Goodman}, J.},\n        title = {emcee: The MCMC Hammer},\n      journal = {PASP},\n         year = 2013,\n       volume = 125,\n        pages = {306-312},\n       eprint = {1202.3665},\n          doi = {10.1086/670067}\n    }\n\nLicense\n-------\n\nCopyright 2010-2021 Dan Foreman-Mackey and contributors.\n\nemcee is free software made available under the MIT License. For details see\nthe LICENSE file.\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "The Python ensemble sampling toolkit for MCMC",
    "version": "3.1.5",
    "project_urls": {
        "Homepage": "https://emcee.readthedocs.io",
        "Source": "https://github.com/dfm/emcee"
    },
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "9fe664805b36c767edc3a5804ca18356f32a4802dffa52cec836dad6e2b281ba",
                "md5": "716ce30bfa2638842dc06499450a3c6d",
                "sha256": "3b7a3c6ff7bf2d04d10705ef648f31e8ac3d8edbab986269af15a90611538b06"
            },
            "downloads": -1,
            "filename": "emcee-3.1.5-py2.py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "716ce30bfa2638842dc06499450a3c6d",
            "packagetype": "bdist_wheel",
            "python_version": "py2.py3",
            "requires_python": null,
            "size": 47273,
            "upload_time": "2024-04-16T14:26:27",
            "upload_time_iso_8601": "2024-04-16T14:26:27.817918Z",
            "url": "https://files.pythonhosted.org/packages/9f/e6/64805b36c767edc3a5804ca18356f32a4802dffa52cec836dad6e2b281ba/emcee-3.1.5-py2.py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "d0f2fa3e87ae09c3c7483997e6e92537a14b48c8d4d15523d8f51b1b75d23b8d",
                "md5": "3a2b2f0358cfecabf42165f4c5c4daf0",
                "sha256": "acc496332f41fa6fbb5ecb73b2aa2b27bd297f73ff4039be30622b601b2dbe6c"
            },
            "downloads": -1,
            "filename": "emcee-3.1.5.tar.gz",
            "has_sig": false,
            "md5_digest": "3a2b2f0358cfecabf42165f4c5c4daf0",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 2870972,
            "upload_time": "2024-04-16T14:26:29",
            "upload_time_iso_8601": "2024-04-16T14:26:29.928360Z",
            "url": "https://files.pythonhosted.org/packages/d0/f2/fa3e87ae09c3c7483997e6e92537a14b48c8d4d15523d8f51b1b75d23b8d/emcee-3.1.5.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-04-16 14:26:29",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "dfm",
    "github_project": "emcee",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "tox": true,
    "lcname": "emcee"
}
        
Elapsed time: 2.89249s