R/plot_annotated.R

In TalhoukLab/biostatUtil: Utility Functions Used in Biostatistics Projects

#' Annotated Barplot
#'
#' Function to provide a barplot from a table of categorical variable with
#' labels wrapped
#' @param tx table of a categorical variable
#' @param ttl the title of the boxplot
#' @author Aline Talhouk
#' @export
barplotSum <- function(tx, ttl = "") {
  wr.lap <- wrap.labels(names(tx), 35)
  graphics::barplot(prop.table(tx) * 100, border = "white", horiz = TRUE,
                    las = 2, names.arg = wr.lap, offset = 0, main = ttl,
                    xlab = "%", cex.names = 0.5, col = "lightblue")
}

#' Wrap labels
#' @noRd
wrap.labels <- function(x, len) {
  purrr::map_chr(x, ~ paste(strwrap(.x, len), collapse = "\n"))
}

#' Annotated Boxplot
#'
#' Function to provide a boxplot annotated with a 5 point summary.
#' @param var the variable to be plotted (must be numerical)
#' @param ttl the title of the boxplot
#' @param digit the number of digits used for rounding (defaults to 1)
#' @author Aline Talhouk
#' @export
boxplotSum <- function(var, ttl = "", digit = 1) {
  bxp <- graphics::boxplot(var, col = "lightgrey", border = "darkgrey",
                           horizontal = TRUE, axes = FALSE, main = ttl)
  graphics::mtext(c("", "Q1", "Med", "Q3", ""), side = 3, at = bxp$stats,
                  line = -2, cex = 0.8)
  graphics::mtext(round(bxp$stats, digit), side = 3, at = bxp$stats,
                  line = -8, cex = 0.8)
}

#' Summary histogram
#'
#' Function to create an annotated histogram, with density plot
#' @param var  a variable to be plotted
#' @param xlab X axis label
#' @param txt  text to be used in the title (defaults to none)
#' @param sub  a sublabel (defaults to none)
#' @param digit number of digits used in rounding (defaults to 1)
#' @author Aline Talhouk
#' @export
histSum <- function(var, xlab = "", txt = "", sub = "", digit = 1) {
  h <- graphics::hist(
    var, main = paste("Mean", round(mean(var, na.rm = TRUE), digit),
                      "SD", round(stats::sd(var, na.rm = TRUE), digit),
                      "Missing", sum(is.na(var))),
    prob = FALSE, xlab = xlab, col = "white", border = "grey",
    sub = sub, cex = 0.8
  )
  xfit <- seq(min(var, na.rm = TRUE), max(var, na.rm = TRUE), length = 50)
  yfit <- stats::dnorm(xfit, mean = mean(var, na.rm = TRUE),
                       sd = stats::sd(var, na.rm = TRUE))
  yfit <- yfit * diff(h$mids[1:2]) * length(var)
  graphics::lines(xfit, yfit, col = "blue", lwd = 2)
  graphics::mtext(txt, side = 3, outer = TRUE, line = -3)
}