R/plot_penalty.R

In kosukeimai/redist: Simulation Methods for Legislative Redistricting

#' (Deprecated) Visualize Group Power Penalty
#'
#' Plots the shape of the [add_constr_grp_pow()] penalty.
#'
#' This function allows you to plot the un-exponentiated penalty implemented as
#' [add_constr_grp_pow()]. The function takes two key inputs,
#' `tgt_min` and `tgt_other` which center the minimum penalty spots. A higher y-value
#' indicates a higher penalty and incentivizes moving towards a spot with a lower y-value.
#' The x-axis indicates the group population proportion in a given district.
#'
#' @param tgt_min double, defaults to 0.55. The minority target percent.
#' @param tgt_other double, defaults to 0.25. The other group target percent.
#' @param strength_vra double, strength of the VRA constraint.
#' @param pow_vra double, exponent of the VRA constraint.
#' @param limits Whether to limit y axis to 0,500. Default is TRUE for
#' comparability across values.
#'
#' @return ggplot
#'
#' @concept prepare
#' @export
#'
#' @importFrom ggplot2 lims labs geom_path
redist.plot.penalty <- function(tgt_min = 0.55, tgt_other = 0.25,
                                strength_vra = 2500, pow_vra = 1.5, limits = TRUE) {
    .Deprecated("plot.redist_constr")

    tb <- tibble(x = seq(0, 1, by = .001))
    tb <- tb %>% mutate(y = strength_vra*(abs(x - tgt_min)^pow_vra)*(abs(x - tgt_other)^pow_vra))


    if (limits) {
        ret <- tb %>% filter(y < 500) %>%
            ggplot(aes(x = x, y = y)) +
            geom_path() +
            theme_bw() +
            lims(x = c(0, 1), y = c(0, 500)) +
            labs(x = "Group Population", y = "Penalty Size")
    } else {
        ret <- tb %>%
            ggplot(aes(x = x, y = y)) +
            geom_path() +
            theme_bw() +
            labs(x = "Group Population", y = "Penalty Size")
    }


    ret
}

globalVariables(c("x", "y"))