Metadata-Version: 1.1
Name: abcpmc
Version: 0.1.1
Summary: approximate bayesian computing with population monte carlo
Home-page: http://www.cosmology.ethz.ch/research/software-lab/abcpmc.html
Author: Joel Akeret
Author-email: jakeret@phys.ethz.ch
License: GPLv3
Description: =============================
        abcpmc
        =============================
        
        .. image:: https://badge.fury.io/py/abcpmc.png
            :target: http://badge.fury.io/py/abcpmc
        
        .. image:: https://travis-ci.org/jakeret/abcpmc.png?branch=master
                :target: https://travis-ci.org/jakeret/abcpmc
                
        .. image:: https://coveralls.io/repos/jakeret/abcpmc/badge.png?branch=master
                :target: https://coveralls.io/r/jakeret/abcpmc?branch=master
        
        .. image:: http://img.shields.io/badge/arXiv-1504.07245-orange.svg?style=flat
                :target: http://arxiv.org/abs/1504.07245
        
        
        
        A Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques.
        
        .. image:: https://raw.githubusercontent.com/jakeret/abcpmc/master/docs/abcpmc.png
           :alt: approximated 2d posterior (created with triangle.py).
           :align: center
        
        The **abcpmc** package has been developed at ETH Zurich in the `Software Lab of the Cosmology Research Group <http://www.cosmology.ethz.ch/research/software-lab.html>`_ of the `ETH Institute of Astronomy <http://www.astro.ethz.ch>`_. 
        
        The development is coordinated on `GitHub <http://github.com/jakeret/abcpmc>`_ and contributions are welcome. The documentation of **abcpmc** is available at `readthedocs.org <http://abcpmc.readthedocs.org/>`_ and the package is distributed over `PyPI <https://pypi.python.org/pypi/abcpmc>`_.
        
        Features
        --------
        
        * Entirely implemented in Python and easy to extend
        
        * Follows Beaumont et al. 2009 PMC algorithm
        
        * Parallelized with muliprocessing or message passing interface (MPI)
        
        * Extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels (Fillipi et al. 2012)
        
        * Detailed examples in IPython notebooks 
        
        	* A `2D gauss <http://nbviewer.ipython.org/github/jakeret/abcpmc/blob/master/notebooks/2d_gauss.ipynb>`_ case study 
        	
        	* A `toy model <http://nbviewer.ipython.org/github/jakeret/abcpmc/blob/master/notebooks/toy_model.ipynb>`_ including a comparison to theoretical predictions
        	
        	
        
        
        
        Documentation
        -------------
        
        The full documentation can be generated with Sphinx
        
        
        
        History
        -------
        0.1.1 (2015-05-03)
        ++++++++++++++++++
        
        * Python 3 support
        * Minor fixes
        * Improved documentation
        
        0.1.0 (2015-04-28)
        ++++++++++++++++++
        
        * First release
Keywords: abcpmc
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
