R/plot_TP.R

In donco/odeqstatusandtrends: Analyze and Report on Water Quality Status and Trends

#' Create Total Phosphorus plots to display status and trend.
#'
#'
#' @param data Dataframe to determine status from. Must have 'excursion' column generated.
#' @param seaKen Results of Seasonal Kendall Analysis
#' @param station The station to plot
#' @param max_date The max date to show on the plot
#' @return dataframe of stations with sufficient data
#' @export
#' @examples
#' plot_TP(data = data.frame, seaKen, station)

plot_TP <- function(data, seaKen, station, max_date = min(data$sample_datetime, na.rm = TRUE)){
  # subset seaken table to parameter and significant trends
  if(NROW(seaKen) > 0){
    seaken_TP <- seaKen %>% dplyr::filter(Char_Name == odeqstatusandtrends::AWQMS_Char_Names('TP'),
                                          significance != "No Significant Trend",
                                          MLocID == station)
  } else {seaken_TP <- data.frame()}

  # obtain data range limits for plotting
  result_max <- max(c(data$Result_cen, data$target_value), na.rm = TRUE)
  xmin <- min(data$sample_datetime, na.rm = TRUE)
  xmax <- max_date
  ymin <- 0
  ymax <- ifelse(result_max > 0.15, result_max * 1.1, 0.15)
  data$excursion <- dplyr::if_else(!is.na(data$excursion_cen),
                                   dplyr::if_else(data$excursion_cen == 1, "Excursion", "Result"),
                                   "Result") # change numeric value to descriptor

  # obtain plotting values for trend line if applicable
  if(nrow(seaken_TP) > 0){
    slope <- round(seaken_TP[, "slope"], digits=3)
    trend <- seaken_TP[, "trend"]
    p_val <- round(seaken_TP[, "p_value"], digits=3)
    x_delta <- as.numeric((xmax-xmin)/2)
    y_median <- median(data$Result_cen, na.rm = TRUE)
    sk_min <- y_median - x_delta*slope/365.25
    sk_max <- y_median + x_delta*slope/365.25
  }

  p <- ggplot2::ggplot(data)

  # add TMDL TP Target line
  if(any(!is.na(data$target_value))){
    target_periods <- unique(data[!is.na(data$start_datetime),c("start_datetime", "end_datetime", "target_value")])
    for(i in 1:NROW(target_periods)){
      p <- p + ggplot2::geom_segment(x=target_periods$start_datetime[i], xend=target_periods$end_datetime[i],
                                     y=target_periods$target_value[i], yend=target_periods$target_value[i],
                                     aes(color = "TMDL Target", linetype = "TMDL Target", shape = "TMDL Target"))
    }
  }

  stat_base <- odeqstatusandtrends::simpleCap(dplyr::if_else(!is.na(unique(data$target_stat_base)), unique(data$target_stat_base), ""))
  title <- paste(station, unique(data$StationDes))
  subtitle <- paste0("Assessment Unit: ", unique(data$AU_ID), " ", unique(data$AU_Name))

  # plot data with excursion colors
  p <- p + ggplot2::geom_point(aes(x=sample_datetime, y=Result_cen, color = excursion, linetype = excursion, shape = excursion)) +
    ggplot2::ggtitle(title, subtitle = subtitle) +
    ggplot2::ylab(paste0(stat_base, " Total Phosphorus (mg/L)")) +
    ggplot2::xlab("Datetime")

  # plot the trend line if applicable
  if(nrow(seaken_TP) > 0){
    p <- p + ggplot2::geom_segment(aes(x=xmin, xend=xmax, y=sk_min, yend=sk_max, color = "Trend", linetype = "Trend", shape = "Trend"), lwd = 1) +
      ggplot2::annotate("text", x = xmin, y = ymax, label = paste0("Trend Results: ", trend, ",  Z-Stat: ", p_val, ",  Slope: ", slope), hjust = 0, vjust = 0)
  }

  # apply color, shape, line types, and range limits
  p <- p +
    ggplot2::scale_color_manual(name = "",
                                values =    c('Excursion' = 'red', 'Result' = 'black', "Trend" = 'blue', "TMDL Target" = 'black')) +
    ggplot2::scale_linetype_manual(name = "",
                                   values = c('Excursion' = 0, 'Result' = 0, "Trend" = 2, "TMDL Target" = 1)) +
    ggplot2::scale_shape_manual(name = "",
                                values =    c('Excursion' = 4, 'Result' = 16, "Trend" = 32, "TMDL Target" = 32)) +
    ggplot2::ylim(c(ymin, ymax)) +
    ggplot2::xlim(c(xmin, xmax)) +
    ggplot2::scale_x_datetime(date_labels = "%b-%Y")+
    ggplot2::theme_linedraw() +
    ggplot2::theme(legend.position="bottom", legend.direction = "horizontal", legend.box = "horizontal",
                   panel.grid.major = element_line(color = "gray"),
                   panel.grid.minor = element_line(color = "gray"))

  return(p)
}