make_cores: Identify Cores of a District (Heuristic)

Description

Creates a grouping ID to unite geographies and perform analysis on a smaller set of precincts. It identifies all precincts more than boundary edges of a district district boundary. Each contiguous group of precincts more than boundary steps away from another district gets it own group. Some districts may have multiple, disconnected components that make up the core, but each of these is assigned a separate grouping id so that a call to sf::st_union() would produce only connected pieces.

Usage

make_cores(.data = cur_map(), boundary = 1, focus = NULL)
redist.identify.cores(
  adj,
  plan,
  boundary = 1,
  focus = NULL,
  simplify = TRUE,
  adjacency,
  district_membership
)

Arguments

.data

a redist_map object

boundary

Number of steps to check for. Defaults to 1.

focus

Optional. Integer. A single district to focus on.

adj

zero indexed adjacency list.

plan

An integer vector or matrix column of district assignments.

simplify

Optional. Logical. Whether to return extra information or just grouping ID.

adjacency

Deprecated, use adj. A zero indexed adjacency list.

district_membership

Deprecated, use plan. An integer vector or matrix column of district assignments.

Value

integer vector (if simplify is false). Otherwise it returns a tibble with the grouping variable as group_id and additional information on connected components.

Details

This is a loose interpretation of the NCSL's summary of redistricting criteria to preserve the cores of prior districts. Using the adjacency graph for a given plan, it will locate the precincts on the boundary of the district, within boundary steps of the edge. Each of these is given their own group. Each remaining entry that is not near the boundary of the district is given an id that can be used to group the remainder of the district by connected component. This portion is deemed the core of the district.

Examples

Run this code

# NOT RUN {
data(fl250)
adj <- redist.adjacency(fl250)
plan <- redist.smc(adj = adj, total_pop = fl250$pop,
                  nsims = 1, ndists = 4)$plans
core <- redist.identify.cores(adj = adj, plan = plan)
redist.plot.cores(shp = fl250, plan = plan, core = core)

# }