pkg/R/getData.R

   1 #' getData
   2 #'
   3 #' Acquire data as a Data object; see ?Data.
   4 #'
   5 #' Since series are given in columns (database format), this function builds series one
   6 #' by one and incrementally grows a Data object which is finally returned.
   7 #'
   8 #' @param ts_data Time-series, as a data frame (DB style: 2 columns, first is date/time,
   9 #'   second is value) or a CSV file.
  10 #' @param exo_data Exogenous variables, as a data frame or a CSV file; first column is
  11 #'   dates, next block are measurements for the day, and final block are exogenous
  12 #'   forecasts (for the same day).
  13 #' @param date_format How date/time are stored (e.g. year/month/day hour:minutes;
  14 #'   see ?strptime)
  15 #' @param limit Number of days to extract (default: Inf, for "all")
  16 #'
  17 #' @return An object of class Data
  18 #'
  19 #' @examples
  20 #' ts_data = read.csv(system.file("extdata","pm10_mesures_H_loc.csv",package="talweg"))
  21 #' exo_data = read.csv(system.file("extdata","meteo_extra_noNAs.csv",package="talweg"))
  22 #' data = getData(ts_data, exo_data, limit=120)
  23 #' @export
  24 getData = function(ts_data, exo_data, date_format="%d/%m/%Y %H:%M", limit=Inf)
  25 {
  26     # Sanity checks (not full, but sufficient at this stage)
  27     if ( (!is.data.frame(ts_data) && !is.character(ts_data)) ||
  28             (!is.data.frame(exo_data) && !is.character(exo_data)) )
  29         stop("Bad time-series / exogenous input (data frame or CSV file)")
  30     if (is.character(ts_data))
  31         ts_data = ts_data[1]
  32     if (is.character(exo_data))
  33         exo_data = exo_data[1]
  34     if (!is.character(date_format))
  35         stop("Bad date_format (character)")
  36     date_format = date_format[1]
  37     if (!is.numeric(limit) || limit < 0)
  38         stop("limit: positive integer")
  39
  40     ts_df =
  41         if (is.character(ts_data))
  42             read.csv(ts_data)
  43         else
  44             ts_data
  45     # Convert to GMT (pretend it's GMT; no impact)
  46     dates_POSIXlt = strptime(as.character(ts_df[,1]), date_format, tz="GMT")
  47     ts_df[,1] = format(as.POSIXct(dates_POSIXlt, tz="GMT"), tz="GMT", usetz=TRUE)
  48
  49     exo_df =
  50         if (is.character(exo_data))
  51             read.csv(exo_data)
  52         else
  53             exo_data
  54     # Times in exogenous variables file are ignored: no conversions required
  55
  56     line = 1 #index in PM10 file (24 lines for 1 cell)
  57     nb_lines = nrow(ts_df)
  58     nb_exos = ( ncol(exo_df) - 1 ) / 2
  59     data = Data$new()
  60     i = 1 #index of a cell in data
  61     while (line <= nb_lines)
  62     {
  63         time = c()
  64         serie = c()
  65         repeat
  66         {
  67             {
  68                 time = c(time, ts_df[line,1])
  69                 serie = c(serie, ts_df[line,2])
  70                 line = line + 1
  71             };
  72             if (line >= nb_lines + 1
  73                 || as.POSIXlt(ts_df[line-1,1],tz="GMT")$hour == 0)
  74             {
  75                 break
  76             }
  77         }
  78
  79         # TODO: 2 modes, "operational" and "testing"; would need PM10 predictions
  80         data$append(time=time, value=serie, level_hat=mean(serie,na.rm=TRUE),
  81             exo=exo_df[i,2:(1+nb_exos)], exo_hat=exo_df[i,(1+nb_exos+1):(1+2*nb_exos)])
  82         if (i >= limit)
  83             break
  84         i = i + 1
  85     }
  86     data
  87 }