https://github.com/cran/cutpointr
Tip revision: 7e56c827a694247d212e9a0167a119f917e1f31b authored by Christian Thiele on 31 August 2018, 15:50:10 UTC
version 0.7.4
version 0.7.4
Tip revision: 7e56c82
plot_x.R
#' Plot the distribution of the independent variable per class from a cutpointr object
#'
#' Given a \code{cutpointr} object this function plots the distribution(s) of the
#' independent variable(s) and the respective cutpoints per class.
#' @param x A cutpointr object.
#' @param display_cutpoint (logical) Whether or not to display the optimal
#' cutpoint as a vertical line.
#' @param ... Additional arguments (unused).
#' @examples
#' opt_cut <- cutpointr(suicide, dsi, suicide)
#' plot_x(opt_cut)
#'
#' ## With subgroup
#' opt_cut_2groups <- cutpointr(suicide, dsi, suicide, gender)
#' plot_x(opt_cut_2groups)
#' @family cutpointr plotting functions
#' @export
plot_x <- function(x, display_cutpoint = TRUE, ...) {
args <- list(...)
predictor <- as.name(x$predictor[1])
outcome <- as.name(x$outcome[1])
if (!(has_column(x, "subgroup"))) {
dts <- "data"
dts_cutpoint <- "optimal_cutpoint"
fll <- NULL
clr <- NULL
clr_roc <- NULL
transparency <- 1
} else {
dts <- c("data", "subgroup")
dts_cutpoint <- c("subgroup", "optimal_cutpoint")
fll <- "subgroup"
clr <- "subgroup"
clr_roc <- ~ subgroup
transparency <- 0.6
}
res_unnested <- x %>%
dplyr::select_(.dots = dts) %>%
tidyr::unnest_(unnest_cols = "data")
if (!(has_column(x, "subgroup"))) {
col <- NULL
} else {
res_unnested <- dplyr::full_join(res_unnested,
x[, c("optimal_cutpoint", "subgroup")],
by = "subgroup")
col <- ~ subgroup
}
if (all(na_inf_omit(unlist(dplyr::select_(res_unnested, .dots = predictor))) %% 1 == 0) |
only_one_unique(
na_inf_omit(unlist(dplyr::select_(res_unnested, .dots = predictor)))
)) {
all_integer = TRUE
dist_plot <- ggplot2::geom_bar(alpha = transparency, position = "identity")
} else {
all_integer = FALSE
dist_plot <- ggplot2::geom_density(alpha = transparency)
}
dist <- ggplot2::ggplot(res_unnested,
ggplot2::aes_string(x = predictor,
fill = fll, color = clr)) +
dist_plot +
# facet by class because always 2
ggplot2::facet_wrap(outcome, scales = "free_y") +
ggplot2::ggtitle("Independent variable",
"optimal cutpoint and distribution by class") +
ggplot2::xlab("value")
if (display_cutpoint) {
cutpoint_dat <- x %>%
dplyr::select_(.dots = dts_cutpoint)
if (is.list(x$optimal_cutpoint)) {
cutpoint_dat <- tidyr::unnest_(cutpoint_dat)
}
dist <- dist +
ggplot2::geom_vline(data = cutpoint_dat,
ggplot2::aes_(xintercept = ~ optimal_cutpoint,
color = col), show.legend = FALSE)
}
if (!all_integer) dist <- dist + ggplot2::geom_rug(alpha = 0.5)
return(dist)
}