Learn R Programming

redist: Simulation Methods for Legislative Redistricting

This R package enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package supports various constraints in the redistricting process, such as geographic compactness and population parity requirements. Tools for analysis, including computation of various summary statistics and plotting functionality, are also included.

Authors:

Contributors:

Papers:

Installation Instructions

redist is available on CRAN and can be installed using:

install.packages("redist")

You can also install the most recent development version of redist (which is usually quite stable) using the remotes package.

if (!require(remotes)) install.packages("remotes")
remotes::install_github("alarm-redist/redist@dev", dependencies=TRUE)

Getting started

A basic analysis has two steps. First, you define a redistricting plan using redist_map. Then you simulate plans using one of the algorithm functions: redist_smc, redist_flip, and redist_mergesplit.

library(redist)
library(dplyr)

data(iowa)

# set a 0.1% population constraint
iowa_map = redist_map(iowa, existing_plan=cd_2010, pop_tol=0.001, total_pop = pop)
# simulate 500 plans using the SMC algorithm
iowa_plans = redist_smc(iowa_map, nsims=500)
#> SEQUENTIAL MONTE CARLO
#> Sampling 500 99-unit maps with 4 districts and population between 760,827 and 762,350.

After generating plans, you can use redist’s plotting functions to study the geographic and partisan characteristics of the simulated ensemble.

library(ggplot2)
library(patchwork) # for plotting

redist.plot.plans(iowa_plans, draws=c("cd_2010", "1", "2", "3"), shp=iowa_map)


iowa_plans = iowa_plans %>%
    mutate(Compactness = comp_polsby(pl(), iowa_map),
           `Population deviation` = plan_parity(iowa_map),
           `Democratic vote` = group_frac(iowa_map, dem_08, tot_08))
#> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE

hist(iowa_plans, `Population deviation`) + hist(iowa_plans, Compactness) +
    plot_layout(guides="collect") +
    plot_annotation(title="Simulated plan characteristics")

redist.plot.scatter(iowa_plans, `Population deviation`, Compactness) +
    labs(title="Population deviation and compactness by plan")


plot(iowa_plans, `Democratic vote`, size=0.5, color_thresh=0.5) +
    scale_color_manual(values=c("black", "tomato2", "dodgerblue")) +
    labs(title="Democratic vote share by district")

A more detailed introduction to redistricting methods and the package can be found in the Get Started page. The package vignettes contain more detailed information and guides to specific workflows.

Copy Link

Version

Install

install.packages('redist')

Monthly Downloads

1,547

Version

4.3.1

License

GPL (>= 2)

Maintainer

Christopher T. Kenny

Last Published

October 1st, 2025

Functions in redist (4.3.1)

plans_diversity

Calculate the diversity of a set of plans
merge_by

Merge map units
rbind.redist_plans

Combine multiple sets of redistricting plans
pullback

Pull back plans to unmerged units
match_numbers

Renumber districts to match an existing plan
prec_assignment

Extract the district assignments for a precinct across all simulated plans
plot.redist_plans

Summary plots for \link{redist_plans}
last_plan

Extract the last plan from a set of plans
get_plans_matrix

Extract the matrix of district assignments from a redistricting simulation
get_plans_weights

Extract the sampling weights from a redistricting simulation.
print.redist_map

Generic to print redist_map
redist.adjacency

Adjacency List functionality for redist
print.redist_constr

Generic to print redist_constr
redist-package

redist: Simulation Methods for Legislative Redistricting
redist.calc.frontier.size

Calculate Frontier Size
print.redist_plans

Print method for redist_plans
is_contiguous

Check that a redist_map object is contiguous
is_county_split

Identify which counties are split by a plan
plan_distances

Compute Distance between Partitions
redist.dist.pop.overlap

Compare the Population Overlap Across Plans at the District Level
plot.redist_classified

Plot a plan classification
min_move_parity

Calculates Sparse Population Moves to Minimize Population Deviation
plot.redist_constr

Visualize constraints
redist.diagplot

Diagnostic plotting functionality for MCMC redistricting.
redist.crsg

Redistricting via Compact Random Seed and Grow Algorithm
redist.ipw

Inverse probability reweighting for MCMC Redistricting
competitiveness

Compute Competitiveness
redist.constraint.helper

Create Constraints for SMC
redist.county.id

Create County IDs
pl

Access the Current redist_plans() Object
redist.county.relabel

Relabel Discontinuous Counties
print.redist_classified

Print redist_classified objects
prec_cooccurrence

Compute a matrix of precinct co-occurrences
redist.coarsen.adjacency

Coarsen Adjacency List
proj

Calculate Projective Distributions, Averages, and Contrasts for a Summary Statistic
redist.init.enumpart

Initialize enumpart
redist.mcmc.mpi

MCMC Redistricting Simulator using MPI
redist.plot.penalty

(Deprecated) Visualize Group Power Penalty
redist.plot.map

Plot a Map
group_frac

Calculate Group Proportion by District
freeze

Freeze Parts of a Map
redist.plot.plans

Plot a district assignment
redist.district.splits

Counts the Number of Counties within a District
redist.uncoarsen

Uncoarsen a District Matrix
redist.plot.scatter

Scatter plot of plan summary statistics
redist.plot.cores

Plot Cores
redist.parity

Calculates Maximum Deviation from Population Parity
redist.reduce.adjacency

Reduce Adjacency List
redist.enumpart

Enumerate All Parititions (Fifield et al. 2020)
muni_splits

Counts the Number of Municipalities Split Between Districts
redist.plot.distr_qtys

Plot quantities by district
county_splits

Count County Splits
redist.plot.wted.adj

Plot Weighted Border Adjacency
redist.subset

Subset a shp
redist.prec.pop.overlap

Compare the Population Overlap Across Plans at the Precinct Level
redist.prep.enumpart

Prepares a run of the enumpart algorithm by ordering edges
redist.find.target

Find Majority Minority Remainder
plot.redist_map

Plot a redist_map
redist.combine.mpi

Combine successive runs of redist.mcmc.mpi
redist.findparams

Run parameter testing for redist_flip
partisan_metrics

Calculate gerrymandering metrics for a set of plans
distr_compactness

Calculate compactness measures for a set of plans
redist.wted.adj

Create Weighted Adjacency Data
redist.read.enumpart

Read Results from enumpart
make_cores

Identify Cores of a District (Heuristic)
redist.sink.plan

Sink Plans to 1:ndists
redist_flip_anneal

Flip MCMC Redistricting Simulator using Simulated Annealing
redist.smc_is_ci

(Deprecated) Confidence Intervals for Importance Sampling Estimates
redist_flip

'Flip' Markov Chain Monte Carlo Redistricting Simulation (Fifield et al. 2020)
redist.plot.majmin

Majority Minority Plots
redist.reorder

Reorders district numbers
redist.plot.hist

Plot a histogram of a summary statistic
redist.rsg

Redistricting via Random Seed and Grow Algorithm
redist.run.enumpart

Runs the enumpart algorithm
redist_ci

Confidence Intervals for SMC and MCMC Estimates
redist.random.subgraph

Return a random subgraph of a shape
redist.plot.trace

Make a traceplot for a summary statistic
redist.multisplits

Counts the Number of Counties Split Between 3 or More Districts
redist.plot.adj

Creates a Graph Overlay
redist.plot.contr_pfdr

Plot a Projective Contrast with positive False Discovery Rate (pFDR) Control
redist_smc

SMC Redistricting Sampler (McCartan and Imai 2023)
segregation_index

Segregation index calculation for MCMC redistricting.
summary.redist_plans

Diagnostic information on sampled plans
redist_mergesplit_parallel

Parallel Merge-Split/Recombination MCMC Redistricting Sampler
redist_plans

A set of redistricting plans
reexports

Objects exported from other packages
tally_var

Tally a variable by district
redist_map

Create a redist_map object.
redist_mergesplit

Merge-Split/Recombination MCMC Redistricting Sampler (Carter et al. 2019)
redist.plot.varinfo

Static Variation of Information Plot
scorer_group_pct

Scoring functions for redist_shortburst
redist_quantile_trunc

Helper function to truncate importance weights
redist_constr

Set up constraints for sampling
redist_shortburst

Redistricting Optimization through Short Bursts
scorer-arith

Scoring function arithmetic
scorer-combine

Combine scoring functions
subset_sampled

Subset to sampled or reference draws
fl25_adj

Florida 25 Precinct File
fl25_enum

All Partitions of 25 Precincts into 3 Congressional Districts (No Population Constraint)
avg_by_prec

Average a variable by precinct (Deprecated)
classify_plans

Hierarchically classify a set of redistricting plans
constraints

Sampling constraints
EPSG

EPSG Table
add_reference

Add a reference plan to a set of plans
compare_plans

Make a comparison between two sets of plans
fl25

Florida 25 Precinct Shape File
fl250

Florida 250 Precinct Shape File
get_target

Extract the target district population from a redist_map object
get_existing

Extract the existing district assignment from a redist_map object
get_mh_acceptance_rate

Extract the Metropolis Hastings Acceptance Rate
iowa

Iowa County File
fl70

Florida 70 Precinct Shape File
get_sampling_info

Extract the sampling information from a redistricting simulation
get_adj

Get and set the adjacency graph from a redist_map object
get_pop_tol

Get and set the population tolerance from a redist_map object
number_by

Renumber districts to match a quantity of interest