R/plot_density_species_per_bottle.R

In LEEF-UZH/LEEF.analysis: Access Functions, Tests and Basic Analysis of the RRD Data from the LEEF Project

#' Plot diagnostic plot to check number of species per timestamp
#'
#' @param db fully qualified path to the sqlite database. Default, read from option \code{RRDdb}.
#'   If not set, defaults to option \code{RRDdb}; if this is not set, defaults to \code{LEEF.RRD.sqlite}
#' @param transform_density_4throot if \code{TRUE}, density is transformed using 4th root transformation.
#' @param measurement the measurement to be plotted. If \code{NULL},
#'   the default, they are plotted by temperature treatment (constant & increasing)
#' @param species_set_id name of the set of species
#'
#' @return \code{ggplot} object of the plot
#'
#' @importFrom dplyr collect mutate
#' @importFrom rlang !!
#' @import ggplot2
#'
#' @export
#'
#' @examples
plot_density_species_per_bottle_per_timestamp <- function(
  db = getOption("RRDdb", "LEEF.RRD.sqlite"),
  transform_density_4throot = TRUE,
  measurement = "bemovi_mag_16",
  species_set_id = NULL
){
  options(dplyr.summarise.inform = FALSE)

  spid <- species_set(species_set_id)
  data <- db_read_density(db) %>%
    dplyr::filter(measurement == !!measurement) %>%
    dplyr::filter(
      ifelse(
        is.null(species_set_id),
        TRUE,
        species %in% !!spid
      )
    ) %>%
    dplyr::collect()
    if (nrow(data) < 1) {
      warning("No data for available!")
    } else {
      data <- data %>% dplyr::mutate(timestamp = convert_timestamp(timestamp)) %>%
        dplyr::mutate(bottle = fix_bottle(bottle)) %>%
        dplyr::mutate(
          density = if (transform_density_4throot) {
            exp(log(density)/4)
          } else {
            density
          }
        ) %>%
        group_by(day, bottle, species, composition, temperature) %>%
        summarise(density = mean(density))

      data$temperature[data$temperature == "increasing"] <- "decreasing light"
      data$temperature[data$temperature == "constant"]   <- "constant light"

      ls <- db_read_light_decline(db) %>% collect()

      p <- ggplot2::ggplot(data, ggplot2::aes(x = .data$day, y = .data$density)) +
        ggplot2::geom_line(ggplot2::aes(y = .data$density, colour = .data$species)) +
        ggplot2::facet_grid(rows = vars(composition), cols = vars(temperature), scales = "free_y") +
        ggplot2::geom_text(
          data = data,
          ggplot2::aes(x = -Inf, y = Inf, label = bottle, group = bottle),
          hjust = -0.5,
          vjust = 1.4,
          size = 3
        ) +
        ggplot2::scale_colour_manual(values = 1:40) +
        ggplot2::xlab("Day of Experiment") +
        ggplot2::ylab(ifelse(transform_density_4throot, "4th root density", "density")) +
        ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45)) +
      geom_vline(xintercept = range(ls$day), colour = "lightgrey")
      p
    }
}