path: root/R/TOXSWA_cwa.R

# Copyright (C) 2014,2015,2016,2017,2018  Johannes Ranke
# Contact: jranke@uni-bremen.de
# This file is part of the R package pfm

# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.

# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more
# details.

# You should have received a copy of the GNU General Public License along with
# this program. If not, see <http://www.gnu.org/licenses/>
if(getRversion() >= '2.15.1') utils::globalVariables(c("cwa"))

#' Read TOXSWA surface water concentrations
#'
#' Read TOXSWA hourly concentrations of a chemical substance in a specific
#' segment of a TOXSWA surface water body. Per default, the data for the last
#' segment are imported. As TOXSWA 4 reports the values at the end of the hour
#' (ConLiqWatLayCur) in its summary file, we use this value as well instead
#' of the hourly averages (ConLiqWatLay).
#'
#' @param filename The filename of the cwa file (TOXSWA 2.x.y  or similar) or the
#'  out file (FOCUS TOXSWA 4, i.e. TOXSWA 4.4.2 or similar).
#' @param basedir The path to the directory where the cwa file resides.
#' @param zipfile Optional path to a zip file containing the cwa file.
#' @param segment The segment for which the data should be read. Either "last", or
#'   the segment number.
#' @param total Set this to TRUE in order to read total concentrations as well. This is
#'   only necessary for .out files as generated by TOXSWA 4.4.2 or similar, not for .cwa
#'   files. For .cwa files, the total concentration is always read as well.
#' @param substance For TOXSWA 4 .out files, the default value "parent" leads
#'   to reading concentrations of the parent compound. Alternatively, the substance
#'   of interested can be selected by its code name.
#' @param windows Numeric vector of width of moving windows in days, for calculating
#'   maximum time weighted average concentrations and areas under the curve.
#' @param thresholds Numeric vector of threshold concentrations in µg/L for
#'   generating event statistics.
#' @importFrom readr read_fwf fwf_empty
#' @importFrom grDevices dev.cur
#' @return An instance of an R6 object of class
#' \code{\link{TOXSWA_cwa}}.
#' @export
#' @author Johannes Ranke
#' @examples
#' H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
#'                                  basedir = "SwashProjects/project_H_sw/TOXSWA",
#'                                  zipfile = system.file("testdata/SwashProjects.zip",
#'                                                        package = "pfm"))
read.TOXSWA_cwa <- function(filename, basedir = ".", zipfile = NULL,
                            segment = "last", substance = "parent",
                            total = FALSE,
                            windows = NULL, thresholds = NULL)
{
  if (!missing(filename)) {
    cwa <- TOXSWA_cwa$new(filename, basedir, zipfile,
                          substance = substance, total = total)
    if (!is.null(windows[1])) cwa$moving_windows(windows)
    if (!is.null(thresholds[1])) cwa$get_events(thresholds)
    invisible(cwa)
  } else {
    message("You need to specify a filename for the cwa file to be read")
  }
}

#' Plot TOXSWA surface water concentrations
#'
#' Plot TOXSWA hourly concentrations of a chemical substance in a specific
#' segment of a TOXSWA surface water body.
#'
#' @import graphics
#' @param x The TOXSWA_cwa object to be plotted.
#' @param xlab,ylab Labels for x and y axis.
#' @param time_column What should be used for the time axis. If "t_firstjan" is chosen,
#'   the time is given in days relative to the first of January in the first year.
#' @param add Should we add to an existing plot?
#' @param threshold_factor The factor by which the data have to be lower than the maximum
#'   in order to get thinned for plotting (see next argument).
#' @param thin_low If an integer greater than 1, the data close to zero (smaller than
#'   1/threshold_factor of the maximum) in the series will be thinned by this factor
#'   in order to decrease the amount of data that is included in the plots
#' @param total Should the total concentration in water be plotted, including substance sorbed
#'   to suspended matter?
#' @param LC_TIME Specification of the locale used to format dates
#' @param ... Further arguments passed to \code{plot} if we are not adding to an existing plot
#' @export
#' @author Johannes Ranke
#' @examples
#' H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
#'   basedir = "SwashProjects/project_H_sw/TOXSWA",
#'   zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
#' plot(H_sw_D4_pond)
#' plot(H_sw_D4_pond, time_column = "t")
#' plot(H_sw_D4_pond, time_column = "t_firstjan")
#' plot(H_sw_D4_pond, time_column = "t_rel_to_max")
#'
#' H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
#'   basedir = "SwashProjects/project_H_sw/TOXSWA",
#'   zipfile = system.file("testdata/SwashProjects.zip", package = "pfm"))
#' plot(H_sw_R1_stream, time_column = "t_rel_to_max")
plot.TOXSWA_cwa <- function(x, time_column = c("datetime", "t", "t_firstjan", "t_rel_to_max"),
                            xlab = "default", ylab = "default",
                            add = FALSE,
                            threshold_factor = 1000, thin_low = 1,
                            total = FALSE, LC_TIME = "C", ...)
{
  time_column = match.arg(time_column)
  cwa_column = ifelse(total, "cwa_tot_mug_per_L", "cwa_mug_per_L")
  plot_data <- x$cwas[c(time_column, cwa_column)]

  # Thin out the data that are less than 1/1000 of the maximum
  names(plot_data) <- c("time", "cwa")
  threshold <- max(plot_data$cwa) / threshold_factor
  plot_data_low <- subset(plot_data, cwa < threshold)
  plot_data_high <- subset(plot_data, cwa >= threshold)
  plot_data_low_thin <- plot_data_low[seq(from = 1, to = nrow(plot_data_low), by = thin_low), ]
  plot_data_combined <- rbind(plot_data_low_thin, plot_data_high)
  plot_data <- plot_data_combined[order(plot_data_combined$time), ]

  lct <- Sys.getlocale("LC_TIME")
  tmp <- Sys.setlocale("LC_TIME", LC_TIME)
  if (identical(xlab, "default")) {
    xlab = switch(time_column,
                datetime = "Time",
                t = "Time [days]",
                t_firstjan = "Time since first of January [days]",
                t_rel_to_max = "Time relative to maximum concentration [days]")
  }
  if (identical(ylab, "default")) {
    # Use LateX if the current plotting device is tikz
    if (names(dev.cur()) == "tikz output") {
      ylab = paste( ifelse(total, "Total concentration", "Concentration"), "[$\\mu$g/L]")
    } else {
      conc_string <- ifelse(total, "Total concentration", "Concentration")
      ylab = bquote(.(conc_string) ~ group("[", mu*g/L, "]"))
    }
  }
  if (add) {
    lines(plot_data, xlab = xlab, ylab = ylab, ...)
  } else{
    if (time_column == "datetime") {
      plot(plot_data, type = "l",
           xlab = xlab, ylab = ylab, xaxt = "n", ...)
      seq_x <- seq(min(x$cwas$datetime), max(x$cwas$datetime), by = "quarter")
      axis(1, at = seq_x, labels = format(seq_x, "%b %Y"))
    } else {
      plot(plot_data, type = "l",
           xlab = xlab, ylab = ylab, ...)
    }
  }
  tmp <- Sys.setlocale("LC_TIME", lct)
}

#' R6 class for holding TOXSWA cwa concentration data and associated statistics
#'
#' An R6 class for holding TOXSWA cwa concentration data and some associated statistics.
#' Usually, an instance of this class will be generated by \code{\link{read.TOXSWA_cwa}}.
#'
#' @docType class
#' @importFrom R6 R6Class
#' @export
#' @format An \code{\link{R6Class}} generator object.
#' @field filename Length one character vector.
#' @field basedir Length one character vector.
#' @field segment Length one integer, specifying for which segment the cwa data were read.
#' @field cwas Dataframe holding the concentrations.
#' @field events List of dataframes holding the event statistics for each threshold.
#' @field windows Matrix of maximum time weighted average concentrations (TWAC_max)
#'   and areas under the curve in µg/day * h (AUC_max_h) or µg/day * d (AUC_max_d)
#'   for the requested moving window sizes in days.
#' @section Methods:
#' \describe{
#'   \item{\code{get_events(threshold, total = FALSE)}}{
#'         Populate a datataframe with event information for the specified threshold value
#'         in µg/L. If \code{total = TRUE}, the total concentration including the amount
#'         adsorbed to suspended matter will be used. The resulting dataframe is stored in the
#'         \code{events} field of the object.
#'         }
#'   \item{\code{moving_windows(windows, total = FALSE)}}{
#'         Add to the \code{windows} field described above.
#'         Again, if \code{total = TRUE}, the total concentration including the amount
#'         adsorbed to suspended matter will be used.
#'         }
#' }
#' @examples
#' H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
#'                                  basedir = "SwashProjects/project_H_sw/TOXSWA",
#'                                  zipfile = system.file("testdata/SwashProjects.zip",
#'                                              package = "pfm"))
#' H_sw_R1_stream$get_events(c(2, 10))
#' H_sw_R1_stream$moving_windows(c(7, 21))
#' print(H_sw_R1_stream)
#' @keywords data

TOXSWA_cwa <- R6Class("TOXSWA_cwa",
  public = list(
    filename = NULL,
    basedir = NULL,
    zipfile = NULL,
    segment = NULL,
    substance = NULL,
    cwas = NULL,
    windows = NULL,
    events = list(),
    initialize = function(filename, basedir, zipfile = NULL,
                          segment = "last", substance = "parent", total = FALSE) {
      self$filename <- filename
      self$basedir <- basedir
      self$zipfile <- zipfile
      if (!is.null(zipfile)) {
        try(file_connection <- unz(zipfile, paste0(basedir, "/", filename)))
      } else {
        try(file_connection <- file(file.path(basedir, filename), "rt"))
      }


      if (grepl(".cwa$", filename)) {
        # cwa file from FOCUS TOXSWA 3 (TOXSWA 2.x.y)
        cwa_all_segments <- try(
          read.table(file_connection,
          sep = "", skip = 40,
          encoding = "UTF-8",
          colClasses = c("character", "numeric",
                         "integer", rep("numeric", 5)),
          col.names = c("datetime", "t", "segment",
                        "xcd", "cwa_tot", "cwa", "Xss", "Xmp")))

        if (is.null(zipfile)) close(file_connection) # only needed for files

        if (!inherits(cwa_all_segments, "try-error")) {
          available_segments = 1:max(cwa_all_segments$segment)
          if (segment == "last") segment = max(available_segments)
          if (!segment %in% available_segments) stop("Invalid segment specified")
          self$segment <- segment
          cwa <- subset(cwa_all_segments, segment == self$segment,
                        c("datetime", "t", "segment", "cwa", "cwa_tot"))
          lct <- Sys.getlocale("LC_TIME"); Sys.setlocale("LC_TIME", "C")
          cwa$datetime <- strptime(cwa$datetime, "%d-%b-%Y-%H:%M", tz = "UTC")
          Sys.setlocale("LC_TIME", lct)
          startyear = format(cwa$datetime[1], "%Y")
          firstjan <- strptime(paste0(startyear, "-01-01"), "%Y-%m-%d",
                               tz = "UTC")
          cwa$t_firstjan <- as.numeric(difftime(cwa$datetime,
                                                      firstjan, units = "days"))

          t_max = cwa[which.max(cwa$cwa), "t"]
          cwa$t_rel_to_max = cwa$t - t_max
          cwa$cwa_mug_per_L <- cwa$cwa * 1000
          cwa$cwa_tot_mug_per_L <- cwa$cwa_tot * 1000
          self$cwas <- cwa[c("datetime", "t", "t_firstjan",
                                          "t_rel_to_max",
                                          "cwa_mug_per_L",
                                          "cwa_tot_mug_per_L")]
        } else {
          stop("Could not read ", filename)
        }
      } else {
        # out file from FOCUS TOXSWA 4 (TOXSWA 4.4.2 or similar)
        outfile <- try(readLines(file_connection))

        close(file_connection) # only needed for files

        if (inherits(outfile, "try-error")) {
          stop("Could not read ", filename)
        } else {
          # Get the substance name(s)
          sub_lines <- grep(".*0.000.*ConLiqWatLayCur_", outfile[1:50], value = TRUE)
          substances <- gsub(".*ConLiqWatLayCur_(.*?) +[0-9].*", "\\1", sub_lines)
          if (!substance %in% c("parent", substances)) {
            stop("No data for substance ", substance, " present in the .out file.")
          }

          # Generate field name for the concentrations at end of hour for the
          # substance of interest
          if (substance == "parent") {
            cwa_string = paste0("ConLiqWatLayCur_", substances[1])
          } else {
            cwa_string = paste0("ConLiqWatLayCur_", substance)
          }

          cwa_lines <- grep(cwa_string, outfile, value = TRUE)

          cwa_all_segments <- read_fwf(paste(cwa_lines, collapse = "\n"),
                                       fwf_empty(paste(tail(cwa_lines), collapse = "\n")))


          available_segments = 1:(ncol(cwa_all_segments) - 3)
          if (segment == "last") segment = max(available_segments)
          if (!segment %in% available_segments) stop("Invalid segment specified")
          self$segment <- segment
          cwa <- data.frame(
            datetime = as.character(cwa_all_segments$X2),
            t = cwa_all_segments$X1,
            cwa = cwa_all_segments[[3 + segment]],
            stringsAsFactors = FALSE
          )

          # Append time "-00h00" to datetime if there is no time (only 11 characters)
          # The fact that the time is missing at 00h00 was reported to Mark
          # Liedekerke, Wim Beltman, Paulien Adriaanse, and Chris Lythgo
          # on 14 December 2016
          cwa <- within(cwa,
            datetime <- ifelse(nchar(datetime) == 11,
              paste0(datetime, "-00h00"),
              datetime))

          if (total) {
            cwa_tot_lines <- outfile[grep("ConSysWatLay_", outfile)] # hourly total conc.
            cwa_tot_all_segments <- read.table(text = cwa_lines)
            cwa$cwa_tot = cwa_tot_all_segments[[3 + segment]]
          }
          lct <- Sys.getlocale("LC_TIME"); Sys.setlocale("LC_TIME", "C")
          cwa$datetime <- strptime(cwa$datetime, "%d-%b-%Y-%Hh%M", tz = "UTC")
          Sys.setlocale("LC_TIME", lct)

          startyear = format(cwa$datetime[1], "%Y")
          firstjan <- strptime(paste0(startyear, "-01-01"), "%Y-%m-%d",
                               tz = "UTC")
          cwa$t_firstjan <- as.numeric(difftime(cwa$datetime,
                                                firstjan, units = "days"))
          t_max = cwa[which.max(cwa$cwa), "t"]
          cwa$t_rel_to_max = cwa$t - t_max
          cwa$cwa_mug_per_L <- cwa$cwa * 1000
          self$cwas <- cwa[c("datetime", "t", "t_firstjan",
                                          "t_rel_to_max",
                                          "cwa_mug_per_L")]
          if (total) {
            self$cwas$cwa_tot_mug_per_L <- cwa$cwa_tot * 1000
          }
        }
      }
    },
    moving_windows = function(windows, total = FALSE) {
      window_names = paste(windows, "days")
      n = length(window_names)
      self$windows <- data.frame(window = window_names,
                                 max_TWAC = numeric(n),
                                 max_AUC_h = numeric(n),
                                 max_AUC_d = numeric(n))
      if (missing(windows)) {
        stop("You need to specify at least one moving window size in days")
      }
      cwa_column = ifelse(total, "cwa_tot_mug_per_L", "cwa_mug_per_L")
      for (i in seq_along(windows)) {
        window_size = windows[i]
        filter_size = window_size * 24
        max_TWAC = max(filter(self$cwas[cwa_column], rep(1/filter_size, filter_size),
                            "convolution"), na.rm = TRUE)
        max_AUC_h = max_TWAC * filter_size
        max_AUC_d = max_TWAC * window_size

        self$windows[i, -1] = c(max_TWAC, max_AUC_h, max_AUC_d)
      }
      invisible(self)
    },
    get_events = function(thresholds, total = FALSE) {
      if (missing(thresholds)) {
        stop("You need to specify at least one threshold concentration in \u03bcg/L")
      }
      for (threshold in thresholds) {
        events = data.frame(t_start = numeric(), cwa_max = numeric(),
                            duration = numeric(), pre_interval = numeric(),
                            AUC_h = numeric(), AUC_d = numeric())
        cwa_column = ifelse(total, "cwa_tot_mug_per_L", "cwa_mug_per_L")

        event_end = 0
        event = FALSE
        event_max = 0
        event_nr = 0
        n_rows = nrow(self$cwas)
        for (i in 1:n_rows) {
          cwa_cur = self$cwas[i, cwa_column]
          if (event == FALSE) {
            if (cwa_cur > threshold) {
              event_start = self$cwas[i, "t"]
              pre_interval = event_start - event_end
              i_start = i
              event = TRUE
              event_max = cwa_cur
            }
          } else {
            if (cwa_cur > event_max) event_max = cwa_cur
            if (cwa_cur < threshold || i == n_rows) {
              event_nr = event_nr + 1
              i_end = i
              if (i == n_rows) i_end = i
              event_end = self$cwas[i_end, "t"]
              event_length = event_end - event_start
              event_cwas <- self$cwas[i_start:(i_end - 1), cwa_column]
              event_AUC_h = sum(event_cwas)
              event_AUC_d = event_AUC_h / 24
              events[event_nr, ] = c(event_start, event_max, event_length,
                                     pre_interval, event_AUC_h, event_AUC_d)
              event = FALSE
            }
          }
        }

        self$events[[as.character(threshold)]] <- events
      }
      invisible(self)
    },
    print = function() {
      cat("<TOXSWA_cwa> data from file", self$filename, "segment", self$segment, "\n")
      print(head(self$cwas))
      cat("Moving window analysis\n")
      print(self$windows)
      for (threshold in names(self$events)) {
        cat("Event statistics for threshold", threshold, "\n")
        if (nrow(self$events[[threshold]]) == 0) cat("No events found\n")
        else print(self$events[[threshold]])
      }
    }
  )
)
# vim: set ts=2 sw=2 expandtab: