Scoring functions for redist_shortburst — scorer_group

The output of these functions may be passed into redist_shortburst() as score_fn. Scoring functions have type redist_scorer and may be combined together using basic arithmetic operations.

Usage

scorer_group_pct(map, group_pop, total_pop, k = 1)

scorer_pop_dev(map)

scorer_splits(map, counties)

scorer_multisplits(map, counties)

scorer_frac_kept(map)

scorer_polsby_popper(map, perim_df = NULL, areas = NULL, m = 1)

scorer_status_quo(map, existing_plan = get_existing(map))

Arguments

map: A redist_map object.
group_pop: A numeric vector with the population of the group for every precinct.
total_pop: A numeric vector with the population for every precinct.
k: the k-th from the top group fraction to return as the score.
counties: A numeric vector with an integer from 1:n_counties
perim_df: perimeter distance dataframe from redistmetrics::prep_perims()
areas: area of each precinct (ie st_area(map))
m: the m-th from the bottom Polsby Popper to return as the score. Defaults to 1, the minimum Polsby Popper score
existing_plan: A vector containing the current plan.

Value

A scoring function of class redist_scorer which returns a single numeric value per plan. Larger values are generally better for frac_kept, group_pct, and polsby_popper and smaller values are better for splits and pop_dev.

Details

Function details:

scorer_group_pct returns the k-th top group percentage across districts. For example, if the group is Democratic voters and k=3, then the function returns the 3rd-highest fraction of Democratic voters across all districts. Can be used to target k VRA districts or partisan gerrymanders.
scorer_pop_dev returns the maximum population deviation within a plan. Smaller values are closer to population parity, so use maximize=FALSE with this scorer.
scorer_splits returns the fraction of counties that are split within a plan. Higher values have more county splits, so use maximize=FALSE with this scorer.
scorer_frac_kept returns the fraction of edges kept in each district. Higher values mean more compactness.
scorer_polsby_popper returns the m-th Polsby Popper score within a plan. Higher scores correspond to more compact districts. Use m=ndists/2 to target the median compactness, m=1 to target the minimum compactness.
scorer_status_quo returns 1 - the rescaled variation of information distance between the plan and the existing_plan. Larger values indicate the plan is closer to the existing plan.

Examples

# \donttest{
data(iowa)
iowa_map <- redist_map(iowa, existing_plan = cd_2010, pop_tol = 0.05, total_pop = pop)

scorer_frac_kept(iowa_map)
#> function (plans) 
#> {
#>     (edges - n_removed(adj, plans, ndists))/edges
#> }
#> <bytecode: 0x00000282a6f0e660>
#> <environment: 0x00000282a2c1daf0>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
scorer_status_quo(iowa_map)
#> function (plans) 
#> {
#>     1 - 0.5 * var_info_vec(plans, existing_plan, pop)/log(ndists)
#> }
#> <bytecode: 0x00000282a2aa51c0>
#> <environment: 0x00000282a2aa59d8>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
scorer_group_pct(iowa_map, dem_08, tot_08, k = 2)
#> function (plans) 
#> {
#>     group_pct_top_k(plans, group_pop, total_pop, k, ndists)
#> }
#> <bytecode: 0x00000282a29863c0>
#> <environment: 0x00000282a2986cb8>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
1.5*scorer_frac_kept(iowa_map) + 0.4*scorer_status_quo(iowa_map)
#> function (plans) 
#> {
#>     fn1(plans) + fn2(plans)
#> }
#> <bytecode: 0x00000282a293eb68>
#> <environment: 0x00000282a293f348>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
1.5*scorer_frac_kept(iowa_map) + scorer_frac_kept(iowa_map)*scorer_status_quo(iowa_map)
#> function (plans) 
#> {
#>     fn1(plans) + fn2(plans)
#> }
#> <bytecode: 0x00000282a293eb68>
#> <environment: 0x00000282a28b6548>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
cbind(
    comp = scorer_frac_kept(iowa_map),
    sq = scorer_status_quo(iowa_map)
)
#> function (plans) 
#> {
#>     do.call(cbind, c(lapply(fns, function(fn) {
#>         fn(plans)
#>     }), list(deparse.level = deparse.level)))
#> }
#> <bytecode: 0x00000282a2865708>
#> <environment: 0x00000282a28662a0>
#> attr(,"class")
#> [1] "redist_scorer" "function"     
# }