X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2FF_Neighbors.R;h=7a3fbe525352405837e55c1fe7b69350768257ed;hp=4b6b7e7f3f80ca67e04ba997c0fe9852271707bd;hb=af3b84f4cacade7d83221ca0249b546c50ddf340;hpb=5d83d8150dc135347d5ef39e5015b88f33fa9ee3

diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index 4b6b7e7..7a3fbe5 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -13,6 +13,9 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			# (re)initialize computed parameters
 			private$.params <- list("weights"=NA, "indices"=NA, "window"=NA)
 
+			# Determine indices of no-NAs days followed by no-NAs tomorrows
+			fdays = private$.data$getCoupleDays(max(today-memory,1), today-1)
+
 			# Get optional args
 			simtype = ifelse(hasArg("simtype"), list(...)$simtype, "mix") #or "endo", or "exo"
 			kernel = ifelse(hasArg("kernel"), list(...)$kernel, "Gauss") #or "Epan"
@@ -22,12 +25,6 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					fdays, today, horizon, list(...)$h_window, kernel, simtype, TRUE) )
 			}
 
-			# Determine indices of no-NAs days followed by no-NAs tomorrows
-			first_day = max(today - memory, 1)
-			fdays = (first_day:(today-1))[ sapply(first_day:(today-1), function(i) {
-				!any(is.na(data$getSerie(i)) | is.na(data$getSerie(i+1)))
-			}) ]
-
 			# Indices of similar days for cross-validation; TODO: 45 = magic number
 			sdays = getSimilarDaysIndices(today, limit=45, same_season=FALSE)
 
@@ -43,25 +40,39 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					if (!is.na(prediction[1]))
 					{
 						nb_jours = nb_jours + 1
-						error = error + mean((data$getCenteredSerie(i+1)[1:horizon] - prediction)^2)
+						error = error +
+							mean((private$.data$getCenteredSerie(i+1)[1:horizon] - prediction)^2)
 					}
 				}
 				return (error / nb_jours)
 			}
 
 			if (simtype != "endo")
-				h_best_exo = optimize(errorOnLastNdays, c(0,10), kernel=kernel, simtype="exo")$minimum
+			{
+				h_best_exo = optimize(
+					errorOnLastNdays, c(0,10), kernel=kernel, simtype="exo")$minimum
+			}
 			if (simtype != "exo")
-				h_best_endo = optimize(errorOnLastNdays, c(0,10), kernel=kernel, simtype="endo")$minimum
+			{
+				h_best_endo = optimize(
+					errorOnLastNdays, c(0,10), kernel=kernel, simtype="endo")$minimum
+			}
 
 			if (simtype == "endo")
-				return(private$.predictShapeAux(fdays,today,horizon,h_best_endo,kernel,"endo",TRUE))
+			{
+				return (private$.predictShapeAux(
+					fdays, today, horizon, h_best_endo, kernel, "endo", TRUE))
+			}
 			if (simtype == "exo")
-				return(private$.predictShapeAux(fdays,today,horizon,h_best_exo,kernel,"exo",TRUE))
+			{
+				return (private$.predictShapeAux(
+					fdays, today, horizon, h_best_exo, kernel, "exo", TRUE))
+			}
 			if (simtype == "mix")
 			{
 				h_best_mix = c(h_best_endo,h_best_exo)
-				return(private$.predictShapeAux(fdays,today,horizon,h_best_mix,kernel,"mix",TRUE))
+				return(private$.predictShapeAux(
+					fdays, today, horizon, h_best_mix, kernel, "mix", TRUE))
 			}
 		}
 	),
@@ -74,6 +85,8 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			if (length(fdays) < 3)
 				return (NA)
 
+			data = private$.data #shorthand
+
 			if (simtype != "exo")
 			{
 				h_endo = ifelse(simtype=="mix", h[1], h)