X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FcomputeError.R;h=c3bc4f381da34112eca28f339db3093582ed9d67;hb=cf3bb00128ac8cb930996455faf7c99a3fc102fb;hp=7da103288805fa64d84feecdad8689b60e55de66;hpb=2057c793ad9929ed5bef8663ea28b896c84df0fc;p=talweg.git

diff --git a/pkg/R/computeError.R b/pkg/R/computeError.R
index 7da1032..c3bc4f3 100644
--- a/pkg/R/computeError.R
+++ b/pkg/R/computeError.R
@@ -1,29 +1,32 @@
 #' Compute error
 #'
-#' Obtain the errors between forecast and data
+#' Compute the errors between forecasted and measured series.
 #'
-#' @param data Dataset, object of class \code{Data} output of \code{getData}
-#' @param pred Forecast object, class \code{Forecast} output of \code{computeForecast}
+#' @param data Object of class \code{Data} output of \code{getData}
+#' @param pred Object of class \code{Forecast} output of \code{computeForecast}
 #' @param horizon Horizon where to compute the error
 #'   (<= horizon used in \code{computeForecast})
 #'
-#' @return A list (abs,MAPE) of lists (day,indices)
+#' @return A list (abs,MAPE) of lists (day,indices). The "indices" slots contain series
+#'   of size L where L is the number of predicted days; i-th value is the averaged error
+#'   (absolute or MAPE) on day i. The "day" slots contain curves of errors, for each time
+#'   step, averaged on the L forecasting days.
 #'
 #' @export
-computeError = function(data, pred, horizon=data$getStdHorizon())
+computeError = function(data, pred, predict_from, horizon=length(data$getSerie(1)))
 {
-	L = forecast$getSize()
-	mape_day = rep(0, horizon)
-	abs_day = rep(0, horizon)
+	L = pred$getSize()
+	mape_day = rep(0, horizon-predict_from+1)
+	abs_day = rep(0, horizon-predict_from+1)
 	mape_indices = rep(NA, L)
 	abs_indices = rep(NA, L)
 
 	nb_no_NA_data = 0
 	for (i in seq_len(L))
 	{
-		index = forecast$getIndexInData(i)
-		serie = data$getSerie(index+1)[1:horizon]
-		forecast = pred$getForecast(i)[1:horizon]
+		index = pred$getIndexInData(i)
+		serie = data$getSerie(index)[predict_from:horizon]
+		forecast = pred$getForecast(i)[predict_from:horizon]
 		if (!any(is.na(serie)) && !any(is.na(forecast)))
 		{
 			nb_no_NA_data = nb_no_NA_data + 1