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Metadata-Version: 1.1
Name: emcee
Version: 2.2.1
Summary: Kick ass affine-invariant ensemble MCMC sampling
Home-page: http://dan.iel.fm/emcee/
Author: Daniel Foreman-Mackey
Author-email: danfm@nyu.edu
License: MIT
Description: emcee
        =====
        
        **The Python ensemble sampling toolkit for affine-invariant MCMC**
        
        .. image:: http://img.shields.io/travis/dfm/emcee/master.svg?style=flat
                :target: http://travis-ci.org/dfm/emcee
        .. image:: http://img.shields.io/pypi/dm/emcee.svg?style=flat
                :target: https://pypi.python.org/pypi/emcee/
        .. image:: http://img.shields.io/pypi/v/emcee.svg?style=flat
                :target: https://pypi.python.org/pypi/emcee/
        .. image:: http://img.shields.io/badge/license-MIT-blue.svg?style=flat
                :target: https://github.com/dfm/emcee/blob/master/LICENSE
        .. image:: http://img.shields.io/badge/arXiv-1202.3665-orange.svg?style=flat
                :target: http://arxiv.org/abs/1202.3665
        .. image:: https://codecov.io/gh/dfm/emcee/branch/master/graph/badge.svg
                :target: https://codecov.io/gh/dfm/emcee
        
        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 `dan.iel.fm/emcee <http://dan.iel.fm/emcee/>`_.
        
        Attribution
        -----------
        
        Please cite `Foreman-Mackey, Hogg, Lang & Goodman (2012)
        <http://arxiv.org/abs/1202.3665>`_ if you find this code useful in your
        research and add your paper to `the testimonials list
        <https://github.com/dfm/emcee/blob/master/docs/testimonials.rst>`_.
        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 2010-2016 Dan Foreman-Mackey and contributors.
        
        emcee is free software made available under the MIT License. For details see
        the LICENSE file.
        
        
        Changelog
        ---------
        
        .. :changelog:
        
        2.2.0 (2016-07-12)
        ++++++++++++++++++
        
        - Improved autocorrelation time computation.
        - Numpy compatibility issues.
        - Fixed deprecated integer division behavior in PTSampler.
        
        
        2.1.0 (2014-05-22)
        ++++++++++++++++++
        
        - Removing dependence on ``acor`` extension.
        - Added arguments to ``PTSampler`` function.
        - Added automatic load-balancing for MPI runs.
        - Added custom load-balancing for MPI and multiprocessing.
        - New default multiprocessing pool that supports ``^C``.
        
        
        2.0.0 (2013-11-17)
        ++++++++++++++++++
        
        - **Re-licensed under the MIT license!**
        - Clearer less verbose documentation.
        - Added checks for parameters becoming infinite or NaN.
        - Added checks for log-probability becoming NaN.
        - Improved parallelization and various other tweaks in ``PTSampler``.
        
        
        1.2.0 (2013-01-30)
        ++++++++++++++++++
        
        - Added a parallel tempering sampler ``PTSampler``.
        - Added instructions and utilities for using ``emcee`` with ``MPI``.
        - Added ``flatlnprobability`` property to the ``EnsembleSampler`` object
          to be consistent with the ``flatchain`` property.
        - Updated document for publication in PASP.
        - Various bug fixes.
        
        
        1.1.3 (2012-11-22)
        ++++++++++++++++++
        
        - Made the packaging system more robust even when numpy is not installed.
        
        
        1.1.2 (2012-08-06)
        ++++++++++++++++++
        
        - Another bug fix related to metadata blobs: the shape of the final ``blobs``
          object was incorrect and all of the entries would generally be identical
          because we needed to copy the list that was appended at each step. Thanks
          goes to Jacqueline Chen (MIT) for catching this problem.
        
        
        1.1.1 (2012-07-30)
        ++++++++++++++++++
        
        - Fixed bug related to metadata blobs. The sample function was yielding
          the ``blobs`` object even when it wasn't expected.
        
        
        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.
        
Platform: UNKNOWN
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