R/coverage_plot.R

In richardjtelford/traitstrap: Bootstrap Trait Values to Calculate Moments

#' Coverage plot of filled Traits
#' @description Function calculates the trait coverage of the community
#' for each level of the sampling hierarchy and makes a barplot.
#' @param object output from `trait_fill()`.
#' @param other_col_how what to do with the other columns in other data.
#'  Options are to `filter` by one of the columns, add them to the x-`axis`,
#' `facet` by them, or to `ignore`.
#' @param ... optional filters for use with `other_col_how = "filter"`
#' @description Shows at which level the data are coming from in each plot.
#'
#' @return a ggplot2 plot
#'
#' @importFrom dplyr group_by summarise distinct bind_cols ungroup
#' @importFrom rlang .data
#' @importFrom ggplot2 autoplot ggplot geom_col facet_wrap aes
#' @importFrom ggplot2 scale_y_continuous labs facet_grid
#' @importFrom glue glue
#' @examples
#' require("ggplot2")
#' data(community)
#' data(trait)
#' filled_traits <- trait_fill(
#'   comm = community, traits = trait,
#'   scale_hierarchy = c("Site", "PlotID"),
#'   taxon_col = "Taxon", value_col = "Value",
#'   trait_col = "Trait", abundance_col = "Cover"
#' )
#' autoplot(filled_traits)
#' @export

autoplot.filled_trait <- function(object, other_col_how, ...) {
  # get scale_hierarchy and concatenate to make an ID
  attrib <- attr(object, "attrib")

  if (length(attrib$other_col) > 0 && missing(other_col_how)) {
    stop(
      glue("Autoplot needs to know what to do with the other_col. Options are:
            axis: add to x-axis labels
            facet: add facets in the plot
            filter: filter out one value of interest
            ignore: ignore")
    )
  }

  if (!missing(other_col_how)) {
    other_col_how <- match.arg(
      arg = other_col_how,
      choices = c("axis", "facet", "filter", "ignore")
    )
  }

  filled_traits_summary <- fortify_filled_trait(
    object,
    other_col_how,
    ...
  )

  plot <- ggplot(filled_traits_summary, aes(
    x = .data$.id,
    y = .data$s, fill = .data$level
  )) +
    geom_col() +
    scale_y_continuous(expand = c(0, 0)) +
    labs(x = "Plot", y = "Proportion of cover", fill = "Data source")

  # add facets
  if (!missing(other_col_how) && other_col_how == "facet") {
    plot <- plot +
      facet_grid(rows = attrib$trait_col, cols = attrib$other_col)
  } else {
    plot <- plot + facet_wrap(facets = attrib$trait_col)
  }

  return(plot)
}