on the way to R6 class + remove truncated days (simplifications)

[talweg.git] / pkg / R / getData.R

diff --git a/pkg/R/getData.R b/pkg/R/getData.R
index 5139a4d..da4b459 100644 (file)
--- a/pkg/R/getData.R
+++ b/pkg/R/getData.R
@@ -14,22 +14,30 @@
 #'   see \code{strptime})
 #' @param working_tz Timezone to work with ("GMT" or e.g. "Europe/Paris")
 #' @param predict_at When does the prediction take place ? Integer, in hours. Default: 0
+#' @param limit Number of days to extract (default: Inf, for "all")
 #'
 #' @return An object of class Data
 #'
+#' @examples
+#' ts_data = read.csv(system.file("extdata","pm10_mesures_H_loc.csv",package="talweg"))
+#' exo_data = read.csv(system.file("extdata","meteo_extra_noNAs.csv",package="talweg"))
+#' getData(ts_data, exo_data, input_tz="Europe/Paris", working_tz="Europe/Paris", limit=150)
 #' @export
-getData = function(ts_data, exo_data,
-       input_tz="GMT", date_format="%d/%m/%Y %H:%M", working_tz="GMT", predict_at=0)
+getData = function(ts_data, exo_data, input_tz="GMT", date_format="%d/%m/%Y %H:%M",
+       working_tz="GMT", predict_at=0, limit=Inf)
 {
        # Sanity checks (not full, but sufficient at this stage)
        if (!is.character(input_tz) || !is.character(working_tz))
                stop("Bad timezone (see ?timezone)")
        input_tz = input_tz[1]
        working_tz = working_tz[1]
-       if (!is.data.frame(ts_data) && !is.character(ts_data))
-               stop("Bad time-series input (data frame or CSV file)")
+       if ( (!is.data.frame(ts_data) && !is.character(ts_data)) ||
+                       (!is.data.frame(exo_data) && !is.character(exo_data)) )
+               stop("Bad time-series / exogenous input (data frame or CSV file)")
        if (is.character(ts_data))
                ts_data = ts_data[1]
+       if (is.character(exo_data))
+               exo_data = exo_data[1]
        predict_at = as.integer(predict_at)[1]
        if (predict_at<0 || predict_at>23)
                stop("Bad predict_at (0-23)")
@@ -38,17 +46,15 @@ getData = function(ts_data, exo_data,
        date_format = date_format[1]
 
        ts_df =
-               if (is.character(ts_data)) {
+               if (is.character(ts_data))
                        read.csv(ts_data)
-               } else {
+               else
                        ts_data
-               }
        exo_df =
-               if (is.character(exo_data)) {
+               if (is.character(exo_data))
                        read.csv(exo_data)
-               } else {
+               else
                        exo_data
-               }
        # Convert to the desired timezone (usually "GMT" or "Europe/Paris")
        formatted_dates_POSIXlt = strptime(as.character(ts_df[,1]), date_format, tz=input_tz)
        ts_df[,1] = format(as.POSIXct(formatted_dates_POSIXlt), tz=working_tz, usetz=TRUE)
@@ -56,7 +62,7 @@ getData = function(ts_data, exo_data,
        line = 1 #index in PM10 file (24 lines for 1 cell)
        nb_lines = nrow(ts_df)
        nb_exos = ( ncol(exo_df) - 1 ) / 2
-       data = list() #new("Data")
+       data = Data$new()
        i = 1 #index of a cell in data
        while (line <= nb_lines)
        {
@@ -73,24 +79,22 @@ getData = function(ts_data, exo_data,
                                break
                }
 
-               # NOTE: if predict_at does not cut days at midnight,
-               # for the exogenous to be synchronized they need to be shifted
-               if (predict_at > 0)
-               {
-                       exo_hat = as.data.frame(exo_df[max(1,i-1),(1+nb_exos+1):(1+2*nb_exos)])
-                       exo_Dm1 = if (i>=3) as.data.frame(exo_df[i-1,2:(1+nb_exos)]) else NA
-               } else
-               {
-                       exo_hat = as.data.frame(exo_df[i,(1+nb_exos+1):(1+2*nb_exos)])
-                       exo_Dm1 = if (i>=2) as.data.frame(exo_df[i-1,2:(1+nb_exos)]) else NA
-               }
-               i = i + 1
-               #center data
+               exo = as.data.frame( exo_df[i,2:(1+nb_exos)] )
+               exo_hat = as.data.frame( exo_df[i,(1+nb_exos+1):(1+2*nb_exos)] )
                level = mean(serie, na.rm=TRUE)
                centered_serie = serie - level
-#              data$append(time, centered_serie, level, exo_hat, exo_Jm1) #TODO: slow: why ?
-               data[[length(data)+1]] = list("time"=time, "serie"=centered_serie, "level"=level,
-                       "exo_hat"=exo_hat, "exo_Dm1"=exo_Dm1)
+               data$append(time, centered_serie, level, exo, exo_hat)
+               if (i >= limit)
+                       break
+               i = i + 1
        }
-       new("Data",data=data)
+       if (length(data$getCenteredSerie(1)) < length(data$getCenteredSerie(1)))
+               data$removeFirst()
+       if (length(data$getCenteredSerie( data$getSize() )) <
+               length(data$getCenteredSerie( data$getSize()-1 )))
+       {
+               data$removeLast()
+       }
+
+       data
 }