inst/extdata/scripts/the_tool2.R

In KWB-R/kwb.misa: Functions to be Used in Project MiSa

################################################################################
# Where is the "the_tool_functions2.R" - File?
functionsFile <- "Y:/Z-Exchange/Malte/MISA/TheTool_for_Scenarios/"
  # paste0("C:/Users/", Sys.info()["user"], "/Desktop/R_Development/RScripts/MISA/")


################################################################################
# 1. read Data -----------------------------------------------------------------
input_path <- "Y:/Z-Exchange/Malte/MISA/TheTool_for_Scenarios/input/"
files <- "all"
year <- 2007
tBeg <- paste0(year, "-01-01")
tEnd <- paste0(year, "-12-31")
sites <- ""

# 2. prepare Data ---------------------------------------------------------------
time_resolution <- 15 # in minutes 
TimeInt_for_interpolation <- 1 # maximal time interval for data interpolation in hours

# 3. get results ---------------------------------------------------------------
thresholds <- c(0.5, 1, 1.5, 2, 5) # in mgg O2/L
event_seperating_hours <- 5 * 24 # in hours
min_deficiency_hours <- 0.25 # in hours
allowed_missing_values <- 25 # in percent (if more values are missing --> no assessment)
reference_site_name <- "MUE" # column name of reference oxygen concentration

################################################################################
source(file = paste0(functionsFile, "the_tool_functions2.R"))
################################################################################

# 1. read Data -----------------------------------------------------------------
if(!("data_comp" %in% ls())){
  data_comp <- read_misa_files(input_path = input_path, files = files)
}
data_comp_f <- filter_data(dataFrame = data_comp, 
                           tBeg = tBeg, 
                           tEnd = tEnd, 
                           sites = sites)
# 2. prepare Data --------------------------------------------------------------
if(!("dl" %in% ls())){
  dl <- continuousTimeIntervals(dataFrame = data_comp_f, res = time_resolution)
  
  dl <- lapply(dl, interpolateParameter, 
               max_na_hours = TimeInt_for_interpolation)
  
  dl <- summer_time(dl = dl)
}

# 3. get results ---------------------------------------------------------------
# Assessment: Deficiency time
deficiencyTime <- do.call(
  rbind, 
  lapply(X = dl, FUN = yearly_deficiency_time, 
         thresholds = thresholds, 
         max_missing = allowed_missing_values))
  
# Assessment: Number of critical events
critEvents <- do.call(
  rbind,
  lapply(X = dl, FUN = yearly_crit_Events, 
         thresholds = c(1.5), 
         seperating_hours = event_seperating_hours, 
         deficiency_hours = min_deficiency_hours,
         max_missing = allowed_missing_values))
  
# Assessment: negative deviation from reference (Mühlendammschleuse)
NegDev <- do.call(
  rbind, 
  lapply(X = dl, FUN = yearly_negative_deviation, 
         oxygen_ref = dl[[reference_site_name]][["oxygen"]], 
         max_missing = allowed_missing_values))

# Details about critical events
chosenSite <- "S2_storage_2020"

EventDetails <- list_CritEvents(
  dataFrame = dl[[chosenSite]], oxygen_colname = "oxygen", 
  seperating_hours = event_seperating_hours, 
  thresholds = c(1.5), 
  year = year)

# Example event no 1, treshold 1.5 mg/L
min_time <- min(EventDetails[["th_1.5"]][[1]]$posixDateTime) - 5 * 60 * 60
max_time <- max(EventDetails[["th_1.5"]][[1]]$posixDateTime) + 5 * 60 * 60

plot_rows <- 
  which(dl[[chosenSite]]$posixDateTime == min_time): 
  which(dl[[chosenSite]]$posixDateTime == max_time)

plot(x = dl[[chosenSite]]$posixDateTime[plot_rows], 
     y = dl[[chosenSite]]$oxygen[plot_rows], type = "l", lwd = 2, 
     xlab = "Zeit", ylab = "O2-Konzentration [mg/L]", main = chosenSite)
axis(side = 3, at = c(min_time, max_time), 
     labels = format(c(min_time, max_time), "%d.%m.%y %H:%M"))
abline(h = 1.5, lty = "dashed")