R/be_io_met_monthly.R

In environmentalinformatics-marburg/metTools:

#' PREPROCESS METEOROLOGICAL READ DATA
#' @export be_io_met_monthly
#'
be_io_met_monthly <- function(filepath, ...){
  df_met <- read.table(filepath, header = TRUE, sep = ",", dec = ".")

  # Define grouping by month-year
  df_met$g_ma <- paste0(substr(as.character(df_met$datetime), 6, 7), "-",
                        substr(as.character(df_met$datetime), 1, 4))

  # Define grouping by year
  df_met$g_a <- substr(as.character(df_met$datetime), 1, 4)

  # Define grouping by month
  df_met$g_m <- substr(df_met$datetime, 6, 7)

  # Define grouping by exploratory and land cover type
  df_met$g_belc <- substr(as.character(df_met$plotID), 1, 3)

  # Define grouping by exploratory, land cover type and month
  df_met$g_belcm <- paste0(substr(as.character(df_met$plotID), 1, 3),
                           "_", substr(as.character(df_met$datetime), 6, 7))

  # Define grouping by plot and month
  df_met$g_pm <- paste0(as.character(df_met$plotID), "_",
                        substr(as.character(df_met$datetime), 6, 7))

  # Define grouping by plot and year
  df_met$g_pa <- paste0(as.character(df_met$plotID), "_",
                        substr(as.character(df_met$datetime), 1, 4))

  df_met$datetime = strptime(paste0(df_met$datetime, "-01"), format = "%Y-%m-%d")

  colnames(df_met)[which(colnames(df_met) == "plotID")] = "EPID"
  return(df_met)
}