R/produce_site_observedProperties_pie.R

In oggioniale/ReLTER: An Interface for the eLTER Community

#' Produce a pie chart of the observed properties collected in a site LTER.
#' @description `r lifecycle::badge("stable")`
#' Return a pie chart of Environmental observed properties, as
#' a stored in \href{https://deims.org/}{DEIMS-SDR catalogue}, of a single
#' eLTER site.
#' @param deimsid A `character`. It is the DEIMS ID of site/network from
#' DEIMS-SDR website. DEIMS ID information
#' \href{https://deims.org/docs/deimsid.html}{here}.
#' @return The output of the function is a pie chart and a `tibble`. The
#' percentages, as a label in the pie charts and in the output table (
#' column 'perc'), refer to the number of the observed properties, belonging
#' to a type (e.g. biological, atmospheric, etc.), measured compared to all of
#' observed properties measured into selected eLTER site. This function allows
#' to show what type of observed properties are most measured into a site. In
#' the example below the atmospheric observed properties corresponds to the
#' 15 percent of all observed properties measured into the site.
#' @author Alessandro Oggioni, phD (2020) \email{oggioni.a@@irea.cnr.it}
#' @importFrom tibble as_tibble
#' @importFrom dplyr group_by tally mutate filter lag
#' @importFrom RColorBrewer brewer.pal
#' @importFrom ggplot2 theme_minimal theme element_blank element_text ggplot
#' @importFrom ggplot2 geom_text aes coord_fixed scale_x_continuous
#' @importFrom ggplot2 scale_y_continuous scale_color_manual labs
#' @importFrom ggforce geom_arc_bar
#' @importFrom Rdpack reprompt
#' @references
#'   \insertRef{tibbleR}{ReLTER}
#'
#'   \insertRef{dplyrR}{ReLTER}
#'
#'   \insertRef{RColorBrewerR}{ReLTER}
#'
#'   \insertRef{ggplot2R}{ReLTER}
#'
#'   \insertRef{ggforceR}{ReLTER}
#' @export
#' @examples
#' \dontrun{
#' pie <- produce_site_observedProperties_pie(
#'   deimsid = "https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe"
#' )
#' pie
#' }
#'
#' @section The function output:
#' \figure{produce_site_parameters_pie_fig.png}{Observed properties pie chart}
#'
### function produce_site_observedProperties_pie
produce_site_observedProperties_pie <- function(deimsid) {
  # TODO add this by SPARQL query
  site <- ReLTER::get_site_info(
    deimsid = deimsid,
    category = "observedProperties"
  )
  paramsDeims <- tibble::as_tibble(site$observedProperties[[1]])
  if (length(paramsDeims) != 0) {
    params <- tibble::as_tibble(paramsDeims)
    params$parameterGroups <- paste0(
      parametersStructureEnvThes$category[
        match(params$observedPropertiesLabel, parametersStructureEnvThes$parameter)
      ],
      "s"
    )
    groupsIsNa <- params %>% dplyr::filter(is.na(parameterGroups))
    # observed properties ----
    params <- params %>%
      dplyr::group_by(parameterGroups) %>%
      dplyr::tally() %>%
      dplyr::mutate(
        freq = n / sum(n),
        perc = paste0(round(freq, 2) * 100, "%"),
        end = 2 * pi * cumsum(freq) / sum(freq),
        start = dplyr::lag(end, default = 0),
        middle = 0.5 * (start + end),
        hjust = ifelse(middle > pi, 1, 0),
        vjust = ifelse(
          middle < pi / 2 | middle > 3 * pi / 2, 0, 1
        )
      )
    # Pie Graph ----
    blank_theme <- ggplot2::theme_minimal() +
      ggplot2::theme(
        axis.title.x = ggplot2::element_blank(),
        axis.title.y = ggplot2::element_blank(),
        panel.border = ggplot2::element_blank(),
        panel.grid = ggplot2::element_blank(),
        axis.ticks = ggplot2::element_blank(),
        plot.title = ggplot2::element_text(
          size = 14, face = "bold"
        )
      )
    mycolors <- c(
      RColorBrewer::brewer.pal(
        name = "Set1",
        n = 9
      ),
      RColorBrewer::brewer.pal(
        name = "Set2",
        n = 8
      ),
      RColorBrewer::brewer.pal(
        name = "Set3",
        n = 12
      )
    )
    pie <- ggplot2::ggplot(params) +
      ggforce::geom_arc_bar(
        ggplot2::aes(
          x0 = 0,
          y0 = 0,
          r0 = 0,
          r = 1,
          start = start,
          end = end,
          fill = parameterGroups
        )
      ) +
      ggplot2::labs(
        title =
          paste0(
            "Percentage of observed properties type measured in the ",
            site$title
          )
      ) +
      ggplot2::geom_text(
        ggplot2::aes(
          x = 1.05 * sin(middle),
          y = 1.05 * cos(middle),
          label = perc,
          hjust = hjust,
          vjust = vjust
        )
      ) +
      ggplot2::coord_fixed() +
      ggplot2::scale_x_continuous(
        limits = c(-1.5, 1.5), # Adjust so labels are not cut off
        name = "",
        breaks = NULL,
        labels = NULL
      ) +
      ggplot2::scale_y_continuous(
        limits = c(-1, 1.1), # Adjust so labels are not cut off
        name = "",
        breaks = NULL,
        labels = NULL
      ) +
      blank_theme +
      ggplot2::scale_color_manual(
        values = mycolors
      )
    # warning about the Insufficient values in manual scale
    if (length(groupsIsNa$observedPropertiesLabel) == 0) {
      message("")
    } else {
      message(
        "This observed properties are not included, please contact the
        development of the package by GitHub.\n",
        "Paste this message into the GitHub issue.\n",
        "I am using the produce_site_observedProperties_pie function and need
        to add the following observed properties in the mapping:\n",
        paste(groupsIsNa$observedPropertiesLabel, collapse = "\n")
      )
    }
    print(pie)
    params %>%
      dplyr::select(parameterGroups, n, freq, perc)
  } else {
    message("\n----\nThe requested page could not be found.
Please check again the DEIMS ID\n----\n")
    pie <- NULL
    params <- NULL
  }
}