#' Plot a metric over all possible cutoffs from a cutpointr object #' #' If \code{maximize_metric} is used as \code{method} function in cutpointr the computed #' metric values over all possible cutoffs can be plotted. Generally, this #' works for method functions that return a ROC-curve including the metric #' value for every cutpoint along with the optimal cutpoint. #' #' @param x A cutpointr object. #' @param conf_lvl The confidence level of the bootstrap confidence interval. #' Set to 0 to draw no bootstrap confidence interval. #' @examples #' opt_cut <- cutpointr(suicide, dsi, suicide) #' plot_metric(opt_cut) #' @importFrom dplyr %>% #' @family cutpointr plotting functions #' @family cutpointr plotting functions #' @export plot_metric <- function(x, conf_lvl = 0.95) { stopifnot("cutpointr" %in% class(x)) if (!(has_column(x$roc_curve[[1]], "m"))) { stop(paste("The cutpointr object does not include a metric column in", "roc_curve - maybe because a method other than", "maximize_metric or minimize_metric was used")) } if (has_boot_results(x) & conf_lvl != 0) { if (has_column(x, "subgroup")) { roc_b_unnested <- x %>% dplyr::select_(.dots = c("boot", "subgroup")) %>% dplyr::mutate_(boot = ~ prepare_bind_rows(boot)) %>% tidyr::unnest_(unnest_cols = "boot") %>% dplyr::select_(.dots = c("subgroup", "roc_curve_b")) %>% tidyr::unnest_(unnest_cols = "roc_curve_b") roc_b_unnested <- roc_b_unnested[is.finite(roc_b_unnested$x.sorted), ] roc_b_unnested <- roc_b_unnested %>% dplyr::select_(.dots = c("x.sorted", "m", "subgroup")) %>% dplyr::group_by_(.dots = c("x.sorted", "subgroup")) %>% dplyr::summarise_(ymin = ~ stats::quantile(m, (1 - conf_lvl) / 2, na.rm = TRUE), ymax = ~ stats::quantile(m, 1 - (1 - conf_lvl) / 2, na.rm = TRUE)) } else { roc_b_unnested <- x[["boot"]][[1]] %>% tidyr::unnest_(unnest_cols = "roc_curve_b") roc_b_unnested <- roc_b_unnested[is.finite(roc_b_unnested$x.sorted), ] roc_b_unnested <- roc_b_unnested %>% dplyr::select_(.dots = c("x.sorted", "m")) %>% dplyr::group_by_(.dots = "x.sorted") %>% dplyr::summarise_(ymin = ~ stats::quantile(m, (1 - conf_lvl) / 2, na.rm = TRUE), ymax = ~ stats::quantile(m, 1 - (1 - conf_lvl) / 2, na.rm = TRUE)) } } metric_name <- find_metric_name(x) if ("subgroup" %in% colnames(x)) { res_unnested <- x %>% dplyr::select_(.dots = c("roc_curve", "subgroup")) %>% tidyr::unnest_(unnest_cols = "roc_curve") res_unnested <- res_unnested[is.finite(res_unnested$x.sorted), c("x.sorted", "m", "subgroup")] if (has_boot_results(x) & conf_lvl != 0) { res_unnested <- merge(res_unnested, roc_b_unnested[, c("subgroup", "x.sorted", "ymin", "ymax")], by = c("x.sorted", "subgroup")) p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted, y = ~ m, ymin = ~ ymin, ymax = ~ ymax, color = ~ subgroup, fill = ~ subgroup)) + ggplot2::geom_line() + ggplot2::geom_point() + ggplot2::ggtitle("Metric values by cutpoint value", "in-sample results") + ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") + ggplot2::geom_ribbon(alpha = 0.2, size = 0) } else { p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted, y = ~ m, color = ~ subgroup)) + ggplot2::geom_line() + ggplot2::geom_point() + ggplot2::ggtitle("Metric values by cutpoint value", "in-sample results") + ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") } } else { res_unnested <- x %>% dplyr::select_(.dots = "roc_curve") %>% tidyr::unnest_(unnest_cols = "roc_curve") res_unnested <- res_unnested[is.finite(res_unnested$x.sorted), (c("x.sorted", "m"))] if (has_boot_results(x) & conf_lvl != 0) { res_unnested <- merge(res_unnested, roc_b_unnested[, c("x.sorted", "ymin", "ymax")], by = "x.sorted") p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted, y = ~ m, ymax = ~ ymax, ymin = ~ ymin)) + ggplot2::geom_line() + ggplot2::geom_point() + ggplot2::ggtitle("Metric values by cutpoint value", "in-sample results") + ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") + ggplot2::geom_ribbon(alpha = 0.2, size = 0) } else { p <- ggplot2::ggplot(res_unnested, ggplot2::aes_(x = ~ x.sorted, y = ~ m)) + ggplot2::geom_line() + ggplot2::geom_point() + ggplot2::ggtitle("Metric values by cutpoint value", "in-sample results") + ggplot2::ylab(metric_name) + ggplot2::xlab("Cutpoint") } } return(p) }