redistricting-analysis

Redistricting simulations in R use redistverse packages to load Census data, build adjacency graphs, and run SMC or mergesplit ensembles. This automates the end-to-end pipeline from redist_map creation to plan comparison.

Comparing enacted redistricting plans against simulated ensembles uses redistmetrics to compute compactness and partisan fairness metrics. The pipeline generates comparison visuals to assess plan diversity and evaluate enacted maps against baseline simulations.

ALARM-based redistricting analysis is supported through pre-built state maps like alarm_50state_map. You can reproduce standard analyses, add enacted plans with alarm_add_plan, and customize pipelines for state or district-level studies.

Constraints and convergence diagnostics apply directly to redistricting SMC ensembles within the redistverse pipeline. The workflow supports constraint application during simulation and provides diagnostics to validate ensemble results before computing metrics.

Census data and adjacency graphs are required before building redist_map objects for redistricting analysis. The pipeline automates data loading and adjacency graph construction as foundational steps before running simulations or computing plan metrics.

Redistricting plan visualization in R is limited to redistverse-supported outputs for comparison visuals and interactive plan drawing. The workflow depends on R-based environments and Census data availability, constraining analysis to compatible geographic frameworks.