comp_schwartz: Calculate Schwartzberg Compactness

In redistmetrics: Redistricting Metrics

Calculate Schwartzberg Compactness

Description

Calculate Schwartzberg Compactness

Usage

comp_schwartz(
  plans,
  shp,
  use_Rcpp,
  perim_path,
  perim_df,
  epsg = 3857,
  ncores = 1
)

Arguments

plans	A redist_plans object or plans_matrix where each row indicates a district assignment and each column is a plan.
shp	A redist_map object, tibble, or data frame with an sf geometry column.
use_Rcpp	Logical. Use Rcpp?
perim_path	path to perimeter tibble saved by prep_perims()
perim_df	tibble of perimeters from prep_perims()
epsg	Numeric EPSG code to use to project the shapefile, if needed. Default is 3857.
ncores	Integer number of cores to use. Default is 1.

Value

A numeric vector. Can be shaped into a district-by-plan matrix.

References

Schwartzberg, Joseph E. 1966. Reapportionment, Gerrymanders, and the Notion of Compactness. Minnesota Law Review. 1701.

Examples

data(nh)
data(nh_m)
# For a single plan:
comp_schwartz(plans = nh$r_2020, shp = nh)

# Or many plans:
comp_schwartz(plans = nh_m[, 3:5], shp = nh)

redistmetrics documentation built on May 29, 2024, 8:02 a.m.