emcee v3

emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC - Published in JOSS (2019)

https://github.com/dfm/emcee

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
    17 of 75 committers (22.7%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

mcmc mcmc-sampler probabilistic-data-analysis python

Keywords from Contributors

astronomy astrophysics exoplanet bayesian-inference parallel-computing multiprocessing mpi physics sunpy sun

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 4 months ago · JSON representation

Repository

The Python ensemble sampling toolkit for affine-invariant MCMC

Basic Info
Statistics
  • Stars: 1,533
  • Watchers: 84
  • Forks: 437
  • Open Issues: 63
  • Releases: 18
Topics
mcmc mcmc-sampler probabilistic-data-analysis python
Created about 14 years ago · Last pushed 4 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Authors

README.rst

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) `_.
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.

Owner

  • Name: Dan Foreman-Mackey
  • Login: dfm
  • Kind: user
  • Location: NYC

JOSS Publication

emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC
Published
November 17, 2019
Volume 4, Issue 43, Page 1864
Authors
Daniel Foreman-Mackey ORCID
Center for Computational Astrophysics, Flatiron Institute
Will M. Farr ORCID
Center for Computational Astrophysics, Flatiron Institute, Department of Physics and Astronomy, Stony Brook University, United States
Manodeep Sinha ORCID
Centre for Astrophysics & Supercomputing, Swinburne University of Technology, Australia, ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
Anne M. Archibald ORCID
University of Newcastle
David W. Hogg ORCID
Center for Computational Astrophysics, Flatiron Institute, Center for Cosmology and Particle Physics, Department of Physics, New York University
Jeremy S. Sanders ORCID
Max Planck Institute for Extraterrestrial Physics
Joe Zuntz ORCID
Institute for Astronomy, University of Edinburgh, Edinburgh, EH9 3HJ, UK
Peter K. g. Williams ORCID
Center for Astrophysics | Harvard & Smithsonian, American Astronomical Society
Andrew R. j. Nelson ORCID
Australian Nuclear Science and Technology Organisation, NSW, Australia
Miguel de Val-Borro ORCID
Planetary Science Institute, 1700 East Fort Lowell Rd., Suite 106, Tucson, AZ 85719, USA
Tobias Erhardt ORCID
Climate and Environmental Physics and Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
Ilya Pashchenko ORCID
P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow, Russia
Oriol Abril Pla ORCID
Universitat Pompeu Fabra, Barcelona
Editor
Juanjo Bazán ORCID
Tags
astronomy

GitHub Events

Total
  • Issues event: 2
  • Watch event: 66
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  • Issue comment event: 3
  • Push event: 8
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  • Create event: 5
Last Year
  • Issues event: 2
  • Watch event: 66
  • Delete event: 2
  • Issue comment event: 3
  • Push event: 8
  • Pull request event: 18
  • Fork event: 10
  • Create event: 5

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 829
  • Total Committers: 75
  • Avg Commits per committer: 11.053
  • Development Distribution Score (DDS): 0.335
Past Year
  • Commits: 10
  • Committers: 3
  • Avg Commits per committer: 3.333
  • Development Distribution Score (DDS): 0.4
Top Committers
Name Email Commits
Dan F-M d****m@n****u 551
pre-commit-ci[bot] 6****] 36
Will Meierjurgen Farr w****r@g****m 32
Anne Archibald p****d@g****m 25
dependabot[bot] 4****] 24
Erik Tollerud e****d@g****m 18
David W. Hogg d****g@g****m 12
Andrew Nelson a****f@g****m 10
Nicholas S. Kern n****n@b****u 7
Jeremy Sanders j****y@j****t 6
Dustin Lang d****n@a****u 6
Peter Williams p****r@n****x 5
Dustin Lang d****n@g****m 5
Manodeep Sinha m****p@g****m 4
bencebeky z****e@g****m 4
Miguel de Val-Borro m****l@g****m 3
Adrian Price-Whelan a****w@g****m 3
Joe Zuntz j****z@g****m 3
Eric Dill e****l@b****v 3
Miguel de Val-Borro m****l@a****t 3
Alex Conley a****y@c****u 3
Will Vousden w****l@v****k 3
Oriol (Prodesk) o****a@g****m 2
Ilya i****o@g****m 2
Carlos Martin c****n@a****u 2
Christopher Bradshaw c****b@g****m 2
Laura Watkins l****s@g****m 2
Andy Casey a****y@m****u 2
Simon Walker s****1@g****m 2
Tobias Erhardt t****t@g****m 2
and 45 more...

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 75
  • Total pull requests: 121
  • Average time to close issues: 3 months
  • Average time to close pull requests: 10 days
  • Total issue authors: 67
  • Total pull request authors: 28
  • Average comments per issue: 3.44
  • Average comments per pull request: 0.94
  • Merged pull requests: 95
  • Bot issues: 0
  • Bot pull requests: 78
Past Year
  • Issues: 3
  • Pull requests: 22
  • Average time to close issues: 15 days
  • Average time to close pull requests: 10 days
  • Issue authors: 3
  • Pull request authors: 6
  • Average comments per issue: 0.67
  • Average comments per pull request: 0.0
  • Merged pull requests: 16
  • Bot issues: 0
  • Bot pull requests: 16
Top Authors
Issue Authors
  • dfm (3)
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Pull Request Authors
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  • MuellerSeb (2)
  • DavidMStraub (1)
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  • mercury0100 (1)
Top Labels
Issue Labels
Documentation (2) Feature Request (1)
Pull Request Labels
dependencies (36) github_actions (4)

Packages

  • Total packages: 13
  • Total downloads:
    • pypi 148,138 last-month
  • Total docker downloads: 4,590
  • Total dependent packages: 188
    (may contain duplicates)
  • Total dependent repositories: 564
    (may contain duplicates)
  • Total versions: 68
  • Total maintainers: 2
pypi.org: emcee

The Python ensemble sampling toolkit for MCMC

  • Versions: 27
  • Dependent Packages: 161
  • Dependent Repositories: 538
  • Downloads: 148,138 Last month
  • Docker Downloads: 4,590
Rankings
Dependent packages count: 0.1%
Dependent repos count: 0.6%
Downloads: 1.0%
Average: 1.3%
Docker downloads count: 1.5%
Stargazers count: 1.8%
Forks count: 2.6%
Maintainers (1)
Last synced: 4 months ago
proxy.golang.org: github.com/dfm/emcee
  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Forks count: 1.4%
Stargazers count: 1.8%
Average: 5.9%
Dependent packages count: 9.6%
Dependent repos count: 10.8%
Last synced: 4 months ago
alpine-edge: py3-emcee-pyc

Precompiled Python bytecode for py3-emcee

  • Versions: 4
  • Dependent Packages: 0
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Rankings
Dependent repos count: 0.0%
Forks count: 4.9%
Average: 6.6%
Stargazers count: 8.5%
Dependent packages count: 13.2%
Maintainers (1)
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alpine-edge: py3-emcee

Python ensemble sampling toolkit for affine-invariant MCMC

  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 0.0%
Forks count: 4.9%
Average: 6.6%
Stargazers count: 8.5%
Dependent packages count: 13.2%
Maintainers (1)
Last synced: 4 months ago
conda-forge.org: emcee
  • Versions: 9
  • Dependent Packages: 27
  • Dependent Repositories: 26
Rankings
Dependent packages count: 2.5%
Dependent repos count: 7.2%
Average: 7.2%
Forks count: 8.1%
Stargazers count: 11.1%
Last synced: 4 months ago
alpine-v3.22: py3-emcee-pyc

Precompiled Python bytecode for py3-emcee

  • Versions: 1
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alpine-v3.20: py3-emcee-pyc

Precompiled Python bytecode for py3-emcee

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alpine-v3.22: py3-emcee

Python ensemble sampling toolkit for affine-invariant MCMC

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alpine-v3.20: py3-emcee

Python ensemble sampling toolkit for affine-invariant MCMC

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alpine-v3.21: py3-emcee

Python ensemble sampling toolkit for affine-invariant MCMC

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alpine-v3.21: py3-emcee-pyc

Precompiled Python bytecode for py3-emcee

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alpine-v3.19: py3-emcee

Python ensemble sampling toolkit for affine-invariant MCMC

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alpine-v3.19: py3-emcee-pyc

Precompiled Python bytecode for py3-emcee

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Dependencies

docs/requirements.txt pypi
  • celerite *
  • corner *
  • h5py *
  • matplotlib *
  • myst-nb *
  • scipy *
  • sphinx-book-theme *
.github/workflows/tests.yml actions
  • actions/checkout v2 composite
  • actions/download-artifact v2 composite
  • actions/setup-python v2 composite
  • actions/upload-artifact v2 composite
  • pypa/gh-action-pypi-publish v1.4.2 composite
binder/environment.yml pypi
  • autograd *
  • celerite *