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 0.01 seconds...
#> 
redist_plans(rsg_plan, iowa, "rsg")
#> A <redist_plans> containing 1 sampled plan
#> Plans have 4 districts from a 99-unit map, and were drawn using random seed-and-grow.
#> Plans matrix: int [1:99, 1] 3 1 4 2 1 4 4 1 4 2 ...
#> # A tibble: 4 × 3
#>   draw  district total_pop
#> * <fct>    <int>     <dbl>
#> 1 1            1    765122
#> 2 1            2    770985
#> 3 1            3    774658
#> 4 1            4    735590