R/getBarPlots.R

In MetaClean: Detection of Low-Quality Peaks in Untargeted Metabolomics Data

#' Generate Bar Plots for the Seven Evaluation Measures
#'
#' Wrapper function for generating bar plots for each classifiers for each of the seven evaluation measures.
#'
#' @param evalMeasuresDF A dataframe with the following columns: Model, RepNum, PosClass.FScore, PosClass.Recall, PosClass.Precision,
#' NegClass.FScore, NegClass.Recall, NegClass.Precision, and Accuracy. The rows of the dataframe will correspond to the results of
#' a particular model and a particular round of cross-validation.
#' @param emNames A list of names of the evaluation measures to visualize. Accepts the following: PosClass.FScore, PosClass.Recall,
#' PosClass.Precision, NegClass.FScore, NegClass.Recall, NegClass.Precision, and Accuracy. Default is "All".
#' @return A list of up to seven bar plots (one for each evaluation measure).
#'
#' @import ggplot2
#'
#' @examples
#' # Create a list of bar plots for each evaluation measure
#' \donttest{makeBarPlots(evalMeasuresDF = test_evalMeasures)}
#'
#' @export

getBarPlots <- function(evalMeasuresDF, emNames = "All"){

  Mean <- Model <- SE <- NULL

  evalMeasureNameList = c("Pass_FScore", "Pass_Precision", "Pass_Recall", "Fail_FScore", "Fail_Precision", "Fail_Recall",
                          "Accuracy")

  if(emNames == "All"){
    emNames = evalMeasureNameList
  }
  if(any(emNames %in% evalMeasureNameList)==FALSE){
    stop("Unrecognized value for emNames - only the following names allowed:
         Pass_FScore, Pass_Precision, Pass_Recall, Fail_FScore, Fail_Precision, Fail_Recall, Accuracy")
  }

  rounds = unique(as.numeric(as.character(evalMeasuresDF$RepNum)))

  modelNames <- unique(as.character(evalMeasuresDF$Model))
  numModels <- length(modelNames)

  # calculate mean and standard error of all rounds for each model
  summaryStatsList <-  lapply(1:numModels, summaryStats, evalMeasuresDF=evalMeasuresDF, emNames=emNames, modelNames=modelNames)
  barplotSum_df <- as.data.frame(do.call(rbind, summaryStatsList))
  barplotSum_df$Mean <- as.numeric(as.character(barplotSum_df$Mean))
  barplotSum_df$SE <- as.numeric(as.character(barplotSum_df$SE))
  barplotSum_df$Model <- as.character(barplotSum_df$Model)


  # separate models by metric set
  m4_barplot_df <- barplotSum_df[endsWith(barplotSum_df$Model, "_M4"),]
  m7_barplot_df <- barplotSum_df[endsWith(barplotSum_df$Model, "_M7"),]
  m11_barplot_df <- barplotSum_df[endsWith(barplotSum_df$Model, "_M11"),]

  bp_df_list <- list()
  bp_names <- c()
  idx <- 1
  if(nrow(m4_barplot_df) != 0){
    bp_df_list[[idx]] <- m4_barplot_df
    idx <- idx + 1
    bp_names <- c(bp_names, "M4")
  }
  if(nrow(m7_barplot_df) != 0){
    bp_df_list[[idx]] <- m7_barplot_df
    idx <- idx + 1
    bp_names <- c(bp_names, "M7")
  }
  if(nrow(m11_barplot_df) != 0){
    bp_df_list[[idx]] <- m11_barplot_df
    idx <- idx + 1
    bp_names <- c(bp_names, "M11")
  }
  names(bp_df_list) <- bp_names

  ms_bar_plot_list <- list()
  for(ms in bp_names){
    barPlots <- list()
    bp_df <- bp_df_list[[ms]]
    for(i in 1:length(emNames)){
      emn <- emNames[i]
      df <- bp_df[bp_df$evalMeasure==emn,]
      g <- ggplot(df, aes(x = 1, y = Mean, fill = Model)) +
        geom_bar(stat = "identity", position = position_dodge()) +
        geom_errorbar(aes(ymax = Mean + SE, ymin = Mean - SE), position = position_dodge(width = 0.9), width = 0.2)
      g <- g + ggtitle(emn)
      g <- g + theme(axis.title.x=element_blank(),
                     axis.text.x=element_blank(),
                     axis.ticks.x=element_blank())
      g <- g + geom_text(aes(label=round(Mean,2)), position=position_dodge(width=0.9), vjust=-0.25, size=5)
      g <- g + theme(plot.title = element_text(size = 25, face = "bold"),
                     legend.title=element_text(size=15, face="bold"),
                     legend.text=element_text(size=12),
                     axis.text=element_text(size=12),
                     axis.title=element_text(size=15, face="bold"))
      g <- g + ylim(0,1)

      barPlots[[emn]] <- g

    }
    ms_bar_plot_list[[ms]] <- barPlots

  }


  return(ms_bar_plot_list)

}