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https://github.com/dfm/markovpy

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https://github.com/dfm/markovpy

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README

          

#MarkovPy

##AUTHOR

Daniel Foreman-Mackey - danfm at nyu dot edu

If you find this code useful in your research, please let me know and
consider citing this package. Thanks!

##INTRODUCTION

MarkovPy is an extensible, pure-Python implementation of Markov chain
Monte Carlo (MCMC) curve fitting. The calling syntax is designed to be
like scipy.optimize so that it can (almost) be a drop in replacement.

There are currently no plans to port the included ensemble sampler to
PyMC or any other platforms but such ports would (of course) be welcomed.

##INSTALLATION

Navigate to this directory and run

`% python setup.py install`

on the command line to install a module called markovpy in the default
Python path.

##DEPENDENCIES

This package requires [NumPy](http://numpy.scipy.org/) and it has been
tested on Python 2.6.5.

##USAGE

[Quickstart](https://github.com/dfm/MarkovPy/wiki/Quickstart)

See the [wiki](http://github.com/dfm/MarkovPy/wiki) for information tutorials, documentation and sample code.

##LICENSE

MarkovPy 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.

MarkovPy 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 MarkovPy. If not, see [http://www.gnu.org/licenses/](http://www.gnu.org/licenses/).