Multiple ROC curves using ggplot2 and pROC

ggrocs.R

#' Functions plots multiple 'roc' objects into one plot
#' @param rocs
#'   A list of 'roc' objects. Every list item has a name.
#' @param breaks
#'   A vector of integers representing ticks on the x- and y-axis
#' @param legentTitel
#'   A string which is used as legend titel
ggrocs <- function(rocs, breaks = seq(0,1,0.1), legendTitel = "Legend") {
  if (length(rocs) == 0) {
    stop("No ROC objects available in param rocs.")
  } else {
    require(plyr)
    # Store all sensitivities and specifivities in a data frame
    # which an be used in ggplot
    RocVals <- plyr::ldply(names(rocs), function(rocName) {
      if(class(rocs[[rocName]]) != "roc") {
        stop("Please provide roc object from pROC package")
      }
      data.frame(
        fpr = rev(rocs[[rocName]]$specificities),
        tpr = rev(rocs[[rocName]]$sensitivities),
        names = rep(rocName, length(rocs[[rocName]]$sensitivities)),
        stringAsFactors = T
      )
    })
    
    aucAvg <- mean(sapply(rocs, "[[", "auc"))

    rocPlot <- ggplot(RocVals, aes(x = fpr, y = tpr, colour = names)) +
      geom_segment(aes(x = 0, y = 1, xend = 1,yend = 0), alpha = 0.5, colour = "gray") + 
      geom_step() +
      scale_x_reverse(name = "False Positive Rate (1 - Specificity)",limits = c(1,0), breaks = breaks) + 
      scale_y_continuous(name = "True Positive Rate (Sensitivity)", limits = c(0,1), breaks = breaks) +
      theme_bw() + 
      coord_equal() + 
      annotate("text", x = 0.1, y = 0.1, vjust = 0, label = paste("AUC =",sprintf("%.3f",aucAvg))) +
      guides(colour = guide_legend(legendTitel)) +
      theme(axis.ticks = element_line(color = "grey80"))
    
    rocPlot
  }
}