A redist_plans object is essentially a data frame of summary information on each district and each plan, along with the matrix of district assignments and information about the simulation process used to generate the plans.

redist_plans(plans, map, algorithm, wgt = NULL, ...)

Arguments

plans

a matrix with n_precinct columns and n_sims rows, or a single vector of precinct assignments.

map

a redist_map object

algorithm

the algorithm used to generate the plans (usually "smc" or "mcmc")

wgt

the weights to use, if any.

...

Other named attributes to set

Value

a new redist_plans object.

Details

The first two columns of the data frame will be draw, a factor indexing the simulation draw, and district, an integer indexing the districts within a plan. The data frame will therefore have n_sims*ndists rows. As a data frame, the usual dplyr methods will work.

Other useful methods for redist_plans objects:

Examples

data(iowa) iowa = redist_map(iowa, existing_plan=cd_2010, pop_tol=0.05, total_pop = pop) rsg_plan = redist.rsg(iowa$adj, iowa$pop, ndists=4, pop_tol=0.05)$plan
#> #> ==================== #> redist.rsg(): Automated Redistricting Starts #> #> #> 4 districts built using 99 precincts in 0.28 seconds... #>
redist_plans(rsg_plan, iowa, "rsg")
#> 1 sampled plan with 4 districts from a 99-unit map, #> drawn using random seed-and-grow #> Plans matrix: int [1:99, 1] 2 2 3 1 2 3 4 2 3 4 ... #> # A tibble: 4 × 3 #> draw district total_pop #> * <fct> <int> <dbl> #> 1 1 1 732928 #> 2 1 2 784093 #> 3 1 3 742404 #> 4 1 4 786930