Metadata-Version: 2.1
Name: gerrychain
Version: 0.2.0
Summary: Use Markov chain Monte Carlo to analyze districting plans and gerrymanders
Home-page: https://github.com/mggg/GerryChain
Author: Metric Geometry and Gerrymandering Group
Author-email: gerrymandr@gmail.com
License: UNKNOWN
Keywords: GerryChain
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Description-Content-Type: text/x-rst
Requires-Dist: pandas
Requires-Dist: networkx
Requires-Dist: geopandas
Requires-Dist: pysal

===============================
GerryChain
===============================

.. image:: https://circleci.com/gh/mggg/GerryChain.svg?style=svg
    :target: https://circleci.com/gh/mggg/GerryChain
    :alt: Build Status
.. image:: https://codecov.io/gh/mggg/GerryChain/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/mggg/GerryChain
   :alt: Code Coverage
.. image:: https://readthedocs.org/projects/gerrychain/badge/?version=latest
   :target: https://gerrychain.readthedocs.io/en/latest
   :alt: Documentation Status

GerryChain is a Python library for building ensembles of districting plans
using `Markov chain Monte Carlo`_.

The basic workflow is to start with the geometry of an initial plan, perhaps one
that is currently enacted in your state or municipality, and generate a large
collection of sample plans for comparison. Usually, we will constrain these
sampled plans in such a way that they perform at least as well as the initial
plan according to traditional districting principles, such as population balance
or compactness. Comparing the initial plan to the ensemble provides quantitative
tools for measuring whether or not it is an outlier similar plans.

The development of this package began at the `Voting Rights Data Institute`_
as a Python rewrite of the chain_ C++ program, originally by Maria Chikina, Alan
Frieze and Wesley Pegden for their paper `"Assessing significance in a Markov chain without mixing."`_

.. _`Voting Rights Data Institute`: http://gerrydata.org/
.. _chain: https://github.com/gerrymandr/cfp_mcmc
.. _`"Assessing significance in a Markov chain without mixing."`: http://www.pnas.org/content/114/11/2860
.. _`Markov chain Monte Carlo`: https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo


Getting started
===============

See our `Getting started guide`_ for the basics of using GerryChain.

.. _`Getting started guide`: https://gerrychain.readthedocs.io/en/latest/quickstart


Useful links
============

- `Documentation`_
- `Bug reports and feature requests`_
- `Contributions welcome!`_

.. _`Documentation`: https://gerrychain.readthedocs.io/en/latest/
.. _`Bug reports and feature requests`: https://github.com/mggg/gerrychain/issues
.. _`Contributions welcome!`: https://github.com/mggg/gerrychain/pulls


Installation
============

To install GerryChain from PyPI_, just run ``pip install gerrychain``.

.. _PyPI: https://pypi.org/

