.. 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 .. image:: https://badge.fury.io/py/gerrychain.svg :target: https://pypi.org/project/gerrychain/ :alt: PyPI Package
GerryChain is a Python library for building ensembles of districting plans
using Markov chain Monte Carlo. It is developed and maintained by the
Metric Geometry and Gerrymandering Group and our network of volunteers.
It is distributed under the 3-Clause BSD License_.
The basic workflow is to start with the geometry of an initial plan 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 among the sampled plans.
.. _Voting Rights Data Institute: http://gerrydata.org/
.. _chain: https://github.com/gerrymandr/cfp_mcmc
.. _Markov chain Monte Carlo: https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo
.. Metric Geometry and Gerrymandering Group: https://www.mggg.org/
.. 3-Clause BSD License: https://opensource.org/licenses/BSD-3-Clause
See our Getting started guide_ for the basics of using GerryChain.
.. _Getting started guide: https://gerrychain.readthedocs.io/en/latest/user/quickstart/
We also highly recommend the resources prepared by Daryl R. DeFord of MGGG
for the 2019 MIT IAP course Computational Approaches for Political Redistricting_.
.. _Computational Approaches for Political Redistricting: https://people.csail.mit.edu/ddeford//CAPR.php
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
The most recent version of GerryChain (as of April 2024) supports
If you do not have one of these versions installed on you machine, we
recommend that you go to the
Python website <https://www.python.org/downloads/> and
download the installer for one of these versions. [1]
A Note for Windows Users ++++++++++++++++++++++++
If you are using Windows and are new to Python, we recommend that you still install Python using the installation package available on the Python website. There are several versions of Python available on the Windows Store, but they can be... finicky, and experience seems to suggest that downloadable available on the Python website produce better results.
In addition, we recommend that you install the
Windows Terminal <https://www.microsoft.com/en-us/p/windows-terminal/9n0dx20hk701?activetab=pivot:overviewtab>
from the Microsoft Store. It is still possible to use PowerShell or
the Command Prompt, but Windows Terminal tends to be more beginner
friendly and allows for a greater range of utility than the natively
installed terminal options (for example, it allows for you to install
the more recent version of PowerShell,
PowerShell 7 <https://docs.microsoft.com/en-us/powershell/scripting/install/installing-powershell>,
and for the use of the Linux Subsystem for Windows).
Once Python is installed on your system, you will want to open the terminal and navigate to the working directory of your project. Here are some brief instructions for doing so on different systems:
MacOS: To open the terminal, you will likely want to use the
Spotlight Search (the magnifying glass in the top right corner of
your screen) to find the "Terminal" application (you can also access
Spotlight Search by pressing "Command (⌘) + Space"). Once you have
the terminal open, type cd followed by the path to your working
directory. For example, if you are working on a project called
my_project in your Documents folder, you may access by typing
the command
.. code-block:: console
cd ~/Documents/my_project
into the terminal (here the ~ is a shortcut for your home directory).
If you do not know what your working directory is, you can find it by
navigating to the desired folder in your file explorer, and clicking
on "Get Info". The path will be labeled "Where" and from there you
can copy the path to your clipboard and paste it in the terminal.
Linux: Most Linux distributions have the keyboard shortcut
Ctrl + Alt + T set to open the terminal. From there you may navigate
to your working directory by typing cd followed by the path to your
working directory. For example, if you are working on a project called
my_project in your Documents folder, you may access this via
the command
.. code-block:: console
cd ~/Documents/my_project
(here the ~ is a shortcut for your home directory). If you do not
know what your working directory is, you can find it by navigating to
the desired folder in your file explorer, and clicking on "Properties".
The path will be labeled "Location" and from there you can copy the path
to your clipboard and paste it in the terminal (to paste in the terminal
in Linux, you will need to use the keyboard shortcut Ctrl + Shift + V
instead of Ctrl + V).
Windows: Open the Windows Terminal and type cd followed by the
path to your working directory. For example, if you are working on a
project called my_project in your Documents folder, you may
access this by typing the command
.. code-block:: console
cd ~\Documents\my_project
into the terminal (here the ~ is a shortcut for your home directory).
If you do not know what your working directory is,
you can find it by navigating to the desired folder in your file
explorer, and clicking on "Properties". The path will be labeled
"Location" and from there you can copy the path to your clipboard
and paste it in the terminal.
Once you have navigated to your working directory, you will want to set up a virtual environment. This is a way of isolating the Python packages you install for this project from the packages you have installed globally on your system. This is useful because it allows you to install different versions of packages for different projects without worrying about compatibility issues. To set up a virtual environment, type the following command into the terminal:
.. code-block:: console
python -m venv .venv
This will create a virtual environment in your working directory which
you can see if you list all the files in your working directory via
the command ls -a (dir on Windows). Now we need to activate the
virtual environment. To do this, type the following command into the
terminal:
.venv\Scripts\activatesource .venv/bin/activateYou should now see (.venv) at the beginning of your terminal prompt
now. This indicates that you are in the virtual environment, and are now
ready to install GerryChain.
To install GerryChain from PyPI_, run pip install gerrychain from
the command line.
If you plan on using GerryChain's GIS functions, such as computing
adjacencies or reading in shapefiles, then run
pip install gerrychain[geo] from the command line.
This approach sometimes fails due to compatibility issues between our
different Python GIS dependencies, like geopandas, pyproj,
fiona, and shapely. If you run into this issue, try installing
the dependencies using the geo_settings.txt <https://github.com/mggg/GerryChain/tree/main/docs/geo_settings.txt>_
file. To do this, run pip install -r geo_settings.txt from the
command line.
.. note::
If you plan on following through the tutorials present within the
remainder of this documentation, you will also need to install
matplotlib from PyPI_. This can also be accomplished with
a simple invocation of pip install matplotlib from the command
line.
.. _PyPI: https://pypi.org/ .. [1] Of course, if you are using a Linux system, you will either need to use your system's package manager or install from source. You may also find luck installing Python directly from the package manager if you find installing from source to be troublesome.
If you are working on a project wherein you would like to ensure particular runs are reproducible, it is necessary to invoke
export PYTHONHASHSEED=0Windows:
$env:PYTHONHASHSEED=0set PYTHONHASHSEED=0before running your code. This will ensure that the hash seed is deterministic which is important for the replication of spanning trees across your runs. If you would prefer to not have to do this every time, then you need to modify the activation script for the virtual environment. Again, this is different depending on your operating system:
MacOS/Linux: Open the file .venv/bin/activate located in your working
directory using your favorite text editor
and add the line export PYTHONHASHSEED=0 after the export PATH command.
So you should see something like::
_OLD_VIRTUAL_PATH="$PATH" PATH="$VIRTUAL_ENV/Scripts:$PATH" export PATH
export PYTHONHASHSEED=0
Then, verify that the hash seed is set to 0 in your Python environment by
running python from the command line and typing
import os; print(os.environ['PYTHONHASHSEED']).
Windows: To be safe, you will need to modify 3 files within your virtual environment:
.venv\Scripts\activate: Add the line export PYTHONHASHSEED=0 after
the export PATH command. So you should see something like::
_OLD_VIRTUAL_PATH="$PATH" PATH="$VIRTUAL_ENV/Scripts:$PATH" export PATH
export PYTHONHASHSEED=0
.venv\Scripts\activate.bat: Add the line set PYTHONHASHSEED=0 to the
end of the file. So you should see something like::
if defined _OLD_VIRTUAL_PATH set PATH=%_OLD_VIRTUAL_PATH% if not defined _OLD_VIRTUAL_PATH set _OLD_VIRTUAL_PATH=%PATH%
set PATH=%VIRTUAL_ENV%\Scripts;%PATH% rem set VIRTUAL_ENV_PROMPT=(.venv) set PYTHONHASHSEED=0
.venv\Scripts\Activate.ps1: Add the line $env:PYTHONHASHSEED=0 to the
end of the before the signature block. So you should see something like::
Copy-Item -Path Env:PATH -Destination Env:_OLD_VIRTUAL_PATH $Env:PATH = "$VenvExecDir$([System.IO.Path]::PathSeparator)$Env:PATH"
$env:PYTHONHASHSEED=0
After you have made these changes, verify that the hash seed is set to 0 in your
Python environment by running python from the command line and typing
import os; print(os.environ['PYTHONHASHSEED']) in the Python prompt.
.. admonition:: A Note on Jupyter :class: note
If you are using a jupyter notebook, you will need to make sure that you have
installed the ipykernel package in your virtual environment as well as
either jypyternotebook or jupyterlab. To install these packages, run
pip install <package-name> from the command line. Then, to use the virtual
python environment in your jupyter notebook, you need to invoke
.. code-block:: console
jupyter notebookor
.. code-block:: console
jupyter labfrom the command line of your working directory while your virtual environment is activated. This will open a jupyter notebook in your default browser. You may then check that the hash seed is set to 0 by running the following code in a cell of your notebook:
.. code-block:: python
import os
print(os.environ['PYTHONHASHSEED'])