R/sm_corr_avgErr.R

In smin95/sesR: Create Standalone and Composite Plots in 'ggplot2' for Publications

#' Superimposition of the average point with horizontal and vertical error bars
#' in the correlation plot
#'
#' @param data
#' Data frame variable that is used for plotting.
#' @param x
#' Column of the data frame that represents the x-axis.
#' @param y
#' Column of the data frame that represents the y-axis.
#' @param point.params
#' List of parameters for the mean point, such as color, alpha, fill etc
#'
#' @param errh.params
#' List of parameters for the horizontal error bar, such as color, alpha, fill etc
#'
#' @param errv.params
#' List of parameters for the vertical points, such as color, alpha, fill etc
#'
#' @param errorbar_type
#' This argument determines the error bar type.
#' If it is set to 'se' , standard error bar will be shown.
#' If it is set to 'sd', the error bar will display standard deviation.
#' If it is set to 'ci' (default), the error bar will display 95\% confidence interval.
#'
#' @param ...
#' A generic aesthetic parameter across points and error bars. This is optional.
#'
#'
#' @return A point with error bars representing the average will be returned.
#' @import ggplot2 cowplot Hmisc
#' @importFrom stats sd
#' @importFrom utils modifyList
#' @importFrom dplyr summarise
#' @export
#'
#' @examples
#' library(smplot2)
#' library(ggplot2)
#' ggplot(data = mtcars, mapping = aes(x = drat, y = mpg)) +
#'   geom_point(shape = 21, size = 3) +
#'   sm_corr_avgErr(mtcars, drat, mpg,
#'     errorbar_type = "se",
#'     color = sm_color("red")
#'   )
sm_corr_avgErr <- function(data, x, y,
                           point.params = list(size = 2.5),
                           errh.params = list(height = 0),
                           errv.params = list(width = 0),
                           errorbar_type = "se",
                           ...) {
  params <- list(...)
  point.params <- modifyList(params, point.params)
  errh.params <- modifyList(params, errh.params)
  errv.params <- modifyList(params, errv.params)


  if (errorbar_type == "se") {
    data <- dplyr::summarise(
      .data = data, x_err = sm_stdErr({{ x }}),
      y_err = sm_stdErr({{ y }}),
      x_avg = mean({{ x }}),
      y_avg = mean({{ y }})
    )
  } else if (errorbar_type == "sd") {
    data <- dplyr::summarise(
      .data = data, x_err = sd({{ x }}),
      y_err = sd({{ y }}),
      x_avg = mean({{ x }}),
      y_avg = mean({{ y }})
    )
  } else if (errorbar_type == "ci") {
    data <- dplyr::summarise(
      .data = data, x_err = qt(p = 0.05 / 2, df = length({{ x }}) - 1, lower.tail = F) *
        sm_stdErr({{ x }}),
      y_err = qt(p = 0.05 / 2, df = length({{ x }}) - 1, lower.tail = F) *
        sm_stdErr({{ y }}),
      x_avg = mean({{ x }}),
      y_avg = mean({{ y }})
    )
  }


  pointPlot <- do.call(
    "geom_point",
    modifyList(list(
      data = data,
      aes(y = y_avg, x = x_avg)
    ), point.params)
  )

  errhPlot <- do.call(
    "geom_errorbarh",
    modifyList(
      list(
        data = data,
        aes(
          y = y_avg,
          xmin = x_avg - x_err,
          xmax = x_avg + x_err
        ), inherit.aes = F
      ),
      errh.params
    )
  )

  errvPlot <- do.call(
    "geom_errorbar",
    modifyList(
      list(
        data = data,
        aes(
          x = x_avg,
          ymin = y_avg - y_err,
          ymax = y_avg + y_err
        ), inherit.aes = F
      ),
      errv.params
    )
  )

  list(errhPlot, errvPlot, pointPlot)
}

globalVariables(c("x_err", "y_err", "x_avg", "y_avg"))