R/plot_histogram.R

In grafify: Easy Graphs for Data Visualisation and Linear Models for ANOVA

#' Plot data distribution as histograms.
#'
#' This function takes a data table, a quantitative variable (`ycol`) and a grouping variable (`group`), if available, and plots a histogram graph using \code{\link{geom_histogram}}).  Alternatives are \code{\link{plot_histogram}}, or \code{\link{plot_qqline}}. 
#' 
#' Note that the function requires the quantitative Y variable first, and groups them based on a categorical variable passed on via the `group` argument. The grouping variable is mapped to the \code{fill} aesthetics in \code{geom_histogram}.
#' 
#' ColPal & ColRev options are applied to both `fill` and `colour` scales. Colours available can be seen quickly with \code{\link{plot_grafify_palette}}.
#' Colours can be changed using `ColPal`, `ColRev` or `ColSeq` arguments. 
#' `ColPal` can be one of the following: "okabe_ito", "dark", "light", "bright", "pale", "vibrant,  "muted" or "contrast".
#' `ColRev` (logical TRUE/FALSE) decides whether colours are chosen from first-to-last or last-to-first from within the chosen palette. 
#' `ColSeq` decides whether colours are picked by respecting the order in the palette or the most distant ones using \code{\link[grDevices]{colorRampPalette}}.
#'
#' @param data a data table e.g. data.frame or tibble.
#' @param ycol name of the column containing the quantitative variable whose histogram distribution is to be plotted.
#' @param group name of the column containing a categorical grouping variable.
#' @param facet add another variable from the data table to create faceted graphs using \code{ggplot2}[facet_wrap].
#' @param BinSize number of distinct bins to use on X-axis, default set to 30.
#' @param c_alpha fractional opacity of colour filled within histograms, default set to 0.8 (i.e. 80% opacity).
#' @param TextXAngle orientation of text on X-axis; default 0 degrees. Change to 45 or 90 to remove overlapping text.
#' @param facet_scales whether or not to fix scales on X & Y axes for all facet facet graphs. Can be `fixed` (default), `free`, `free_y` or `free_x` (for Y and X axis one at a time, respectively).
#' @param fontsize parameter of \code{base_size} of fonts in \code{theme_classic}, default set to size 20.
#' @param linethick thickness of symbol border, default set to `fontsize`/22.
#' @param alpha deprecated old argument for `c_alpha`; retained for backward compatibility.
#' @param ColPal grafify colour palette to apply, default "okabe_ito"; see \code{\link{graf_palettes}} for available palettes.
#' @param ColSeq logical TRUE or FALSE. Default TRUE for sequential colours from chosen palette. Set to FALSE for distant colours, which will be applied using  \code{scale_fill_grafify2}.
#' @param ColRev whether to reverse order of colour within the selected palette, default F (FALSE); can be set to T (TRUE).
#' @param ... any additional arguments to pass to \code{ggplot2}[geom_histogram].
#'
#' @return This function returns a \code{ggplot2} object of class "gg" and "ggplot".
#' @export plot_histogram
#' @import ggplot2
#'
#' @examples
#' #Basic usage
#' plot_histogram(data = data_t_pratio, 
#' ycol = Cytokine, group = Genotype, 
#' BinSize = 10)
#' #with log transformation
#' plot_histogram(data = data_t_pratio, 
#' ycol = log(Cytokine), group = Genotype, 
#' BinSize = 10)

plot_histogram <- function(data, ycol, group, facet, BinSize = 30, c_alpha = 0.8, TextXAngle = 0, facet_scales = "fixed", fontsize = 20, linethick, alpha, ColPal = c("okabe_ito", "all_grafify", "bright",  "contrast",  "dark",  "fishy",  "kelly",  "light",  "muted",  "pale",  "r4",  "safe",  "vibrant"), ColSeq = TRUE, ColRev = FALSE, ...){
  if(missing(linethick)) {linethick = fontsize/22}
  if (!missing("alpha")) {
    warning("Use `c_alpha` argument instead, as `alpha` is deprecated.")
    c_alpha <- substitute(alpha)}
  ColPal <- match.arg(ColPal)
  if(missing(group)) {
    suppressWarnings(P <- ggplot2::ggplot(data, 
                         aes({{ ycol }}))+
      geom_histogram(size = linethick,
                     alpha = c_alpha,
                     bins = BinSize,
                     colour = "black",
                     linewidth = linethick,
                     fill = "#E69F00")+
      theme_grafify(base_size = fontsize)+
      theme(strip.background = element_blank())+
      guides(x = guide_axis(angle = TextXAngle)))
  } else {
    suppressWarnings(P <- ggplot2::ggplot(data, 
                         aes({{ ycol }}))+
      geom_histogram(size = linethick,
                     alpha = c_alpha,
                     colour = "black",
                     linewidth = linethick,
                     bins = BinSize,
                     aes(fill = factor({{ group }})))+
      theme_grafify(base_size = fontsize)+
      guides(x = guide_axis(angle = TextXAngle))+
      scale_fill_grafify(palette = ColPal, 
                         reverse = ColRev, 
                         ColSeq = ColSeq))
    }
  if(!missing(facet)) {
    P <- P + facet_wrap(vars({{ facet }}), 
                        scales = facet_scales, 
                        ...)
  }
  P <- P +
    labs(fill = enquo(group))
  P
}