R/projected_shade_class.R

In Jellest/wmoSC: WMO air temperature Siting Classification of automatic weather stations

#'Projected shade classes
#'
#'@title Projected shade classes
#'@description Projected shade classes
#'@param name coordidnate in RD New or WGS84 (LON)
#'@param data.path data path of shadow angles csv
#'@param AHN3 Default TRUE. Set to FALSE if AHN2 needs to be used.
#'@author Jelle Stuurman
#'@return  data frame with all Projected shading Cass of all calculated shadow angles
projected_shade_classes <- function(name, data.path, AHN3 = TRUE, name.supplement = "", criteria_columnName = "Criteria_Value"){
  if(missing(name)){
    name <- ""
  }
  if(AHN3 == TRUE){
    AHN <- "AHN3"
  } else {
    AHN <- "AHN2"
  }
  
  name_trim <- getName_trim(name = name, name.supplement = name.supplement)
  
  df <- fread(data.path, data.table = FALSE)
  
  tshac <- dplyr::filter(guideline_criteria, Variable == "temperature" & Criteria_Type == "shading")
  tshac <- check_criteria(df = tshac, criteria_columnName = criteria_columnName)
  
  class_1_filter <-  filter(tshac, Class == "1")
  class_1_cv <- as.numeric(class_1_filter[,criteria_columnName][1])
  
  class_2_filter <-  filter(tshac, Class == "2")
  class_2_cv <- as.numeric(class_2_filter[,criteria_columnName][1])
  
  class_3_filter <-  filter(tshac, Class == "3")
  class_3_cv <- as.numeric(class_3_filter[,criteria_columnName][1])
  
  class_2_3_cv <- as.numeric(class_2_filter[,criteria_columnName][1]) 
  
  class_4_filter <-  filter(tshac, Class == "4")
  class_4_cv <- as.numeric(class_4_filter[,criteria_columnName][1])
  
  class_5_filter <-  filter(tshac, Class == "5")
  class_5_cv <- as.numeric(class_5_filter[,criteria_columnName][1])
  
  # class_1_cv <- 2
  # class_2_cv <- 2.2
  # class_3_cv <- 2.6
  # class_4_cv <- 2.8
  # class_5_cv <- 3.0

  # class_1_shading <-subset(solar_shading_angles, elevation > class_1_cv)
  # class_2_shading <- subset(solar_shading_angles, elevation > class_2_cv)
  # class_3_shading <- subset(solar_shading_angles, elevation > class_3_cv)
  # class_2_3_shading <- subset(solar_shading_angles, elevation > class_2_cv) 
  # class_4_shading <- subset(solar_shading_angles, elevation > class_4_cv)
  
  for(n in seq(1, nrow(df), 1)){
    df[n,"meet_class1"] <- TRUE
    df[n,"meet_class2"] <- TRUE
    df[n,"meet_class3"] <- TRUE
    df[n,"meet_class4"] <- TRUE
    df[n,"meet_class5"] <- TRUE
    
    #class 1
    if(df[n,"shadow_angle"] < class_1_cv & df[n,"shadow_angle"] > df[n,"elevation"]){
      df[n,"meet_class1"] <- TRUE
      df[n,"meet_class2"] <- TRUE
      df[n,"meet_class3"] <- TRUE
      df[n,"meet_class4"] <- TRUE
      df[n,"meet_class5"] <- TRUE
    }
    
    #class 2
    if(df[n,"shadow_angle"] >= class_1_cv & df[n,"shadow_angle"] < class_2_3_cv & df[n,"shadow_angle"] > df[n,"elevation"]){
      df[n,"meet_class1"] <- FALSE
      df[n,"meet_class2"] <- TRUE
      df[n,"meet_class3"] <- TRUE
      df[n,"meet_class4"] <- TRUE
      df[n,"meet_class5"] <- TRUE
    }
    
    #class 3
    if(df[n,"shadow_angle"] >= class_2_cv & df[n,"shadow_angle"] < class_3_cv & df[n,"shadow_angle"] > df[n,"elevation"]){
      df[n,"meet_class1"] <- FALSE
      df[n,"meet_class2"] <- FALSE
      df[n,"meet_class3"] <- FALSE
      df[n,"meet_class4"] <- TRUE
      df[n,"meet_class5"] <- TRUE
    }
    
    #class 4
    if(df[n,"shadow_angle"] >= class_3_cv & df[n,"shadow_angle"] < class_4_cv & df[n,"shadow_angle"] > df[n,"elevation"]){
      df[n,"meet_class1"] <- FALSE
      df[n,"meet_class2"] <- FALSE
      df[n,"meet_class3"] <- FALSE
      df[n,"meet_class4"] <- TRUE
      df[n,"meet_class5"] <- TRUE
    }
    
    #class 5
    if(df[n,"shadow_angle"] >= class_4_cv & df[n,"shadow_angle"] > df[n,"elevation"]){
      df[n,"meet_class1"] <- FALSE
      df[n,"meet_class2"] <- FALSE
      df[n,"meet_class3"] <- FALSE
      df[n,"meet_class4"] <- FALSE
      df[n,"meet_class5"] <- TRUE
    }
    
    if(df[n,"meet_class5"] == TRUE){
      df[n,"final_indiv_class"] <- 5
    }
    if(df[n,"meet_class4"] == TRUE){
      df[n,"final_indiv_class"] <- 4
    }
    if(df[n,"meet_class3"] == TRUE){
      df[n,"final_indiv_class"] <- 3
    }
    if(df[n,"meet_class2"] == TRUE){
      df[n,"final_indiv_class"] <- 2
    }
    if(df[n,"meet_class1"] == TRUE){
      df[n,"final_indiv_class"] <- 1
    }

  }

  class1_count <- sum(1 == df[,"final_indiv_class"])
  class2_count <- sum(2 == df[,"final_indiv_class"])
  class3_count <- sum(3 == df[,"final_indiv_class"])  
  class4_count <- sum(4 == df[,"final_indiv_class"])
  class5_count <- sum(5 == df[,"final_indiv_class"])
  
  for(c in seq(1, nrow(df), 1)){
    df[c,"class1_count"] <- class1_count
    df[c,"class2_count"] <- class2_count
    df[c,"class3_count"] <- class3_count  
    df[c,"class4_count"] <- class4_count
    df[c,"class5_count"] <- class5_count
  }
  
  final_class <- max(df[,"final_indiv_class"]) 
  #print(final_class)
  df$final_class <- final_class 
  if(name_trim == ""){
    dir.create("output/solar_shadow_angles", showWarnings = FALSE)
  }
  if(!dir.exists(paste0("output/", name_trim))){
    dir.create(paste0("output/", name_trim), showWarnings = FALSE)
  }
  if(!dir.exists(paste0("output/", name_trim, "/solar_shadow_angles"))){
    dir.create(paste0("output/", name_trim, "/solar_shadow_angles"), showWarnings = FALSE)
  }
  
  if(name != ""){
    fwrite(df, paste0("output/", name_trim, "/solar_shadow_angles/", name_trim, "_", AHN, "_ah_solar_shadow_angles_classes.csv"))
  } else {
    fwrite(df, paste0("output/solar_shadow_angles/", AHN, "_ah_solar_shadow_angles_classes.csv"))
  }
  #View(df)
  message(paste0("Shading passed criteria for class ", final_class, "."))
  return (df)
}