Metadata-Version: 1.1
Name: emcee
Version: 1.2.0
Summary: Kick ass affine-invariant ensemble MCMC sampling
Home-page: http://danfm.ca/emcee/
Author: Daniel Foreman-Mackey
Author-email: danfm@nyu.edu
License: GPLv2
Description: emcee
        =====
        
        **The Python ensemble sampling toolkit for affine-invariant MCMC**
        
        .. image:: https://secure.travis-ci.org/dfm/emcee.png?branch=master
                :target: http://travis-ci.org/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>`_—or `email
        us <mailto:danfm@nyu.edu>`_ to get added—if you made use of ``emcee``.
        
        
        License
        -------
        
        emcee is free software: you can redistribute it and/or modify
        it under the terms of the GNU General Public License version 2 as
        published by the Free Software Foundation.
        
        emcee is distributed in the hope that it will be useful,
        but WITHOUT ANY WARRANTY; without even the implied warranty of
        MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
        GNU General Public License for more details.
        
        You should have received a copy of the GNU General Public License
        along with emcee.  If not, see
        `http://www.gnu.org/licenses/ <http://www.gnu.org/licenses/>`_.
        
        
        Changelog
        ---------
        
        .. :changelog:
        
        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 :: GNU General Public License (GPL)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
