X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FF_Neighbors.R;h=c9eda053820615485e19079b493fefa7329b1172;hb=eef545170c5a76b710184db6b695c15b20759177;hp=c55291aa996838a2a02535725f72c4fb8709b922;hpb=aa059de77cbcd28a3a66c7ff29ebe0346882867b;p=talweg.git

diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index c55291a..c9eda05 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -22,8 +22,8 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			fdays = getNoNA2(data, max(today-memory,1), today-1)
 
 			# Get optional args
-			local = ifelse(hasArg("local"), list(...)$local, FALSE) #same level + season?
-			simtype = ifelse(hasArg("simtype"), list(...)$simtype, "mix") #or "endo", or "exo"
+			local = ifelse(hasArg("local"), list(...)$local, TRUE) #same level + season?
+			simtype = ifelse(hasArg("simtype"), list(...)$simtype, "none") #or "endo", or "exo"
 			if (hasArg("window"))
 			{
 				return ( private$.predictShapeAux(data,
@@ -34,7 +34,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			cv_days = getSimilarDaysIndices(today, data, limit=20, same_season=FALSE,
 				days_in=fdays)
 
-			# Optimize h : h |--> sum of prediction errors on last 45 "similar" days
+			# Optimize h : h |--> sum of prediction errors on last N "similar" days
 			errorOnLastNdays = function(window, simtype)
 			{
 				error = 0
@@ -54,32 +54,30 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				return (error / nb_jours)
 			}
 
-			if (simtype != "endo")
-			{
-				best_window_exo = optimize(
-					errorOnLastNdays, c(0,7), simtype="exo")$minimum
-			}
-			if (simtype != "exo")
+			# TODO: 7 == magic number
+			if (simtype=="endo" || simtype=="mix")
 			{
 				best_window_endo = optimize(
 					errorOnLastNdays, c(0,7), simtype="endo")$minimum
 			}
-
-			if (simtype == "endo")
-			{
-				return (private$.predictShapeAux(data, fdays, today, horizon, local,
-					best_window_endo, "endo", TRUE))
-			}
-			if (simtype == "exo")
-			{
-				return (private$.predictShapeAux(data, fdays, today, horizon, local,
-					best_window_exo, "exo", TRUE))
-			}
-			if (simtype == "mix")
+			if (simtype=="exo" || simtype=="mix")
 			{
-				return(private$.predictShapeAux(data, fdays, today, horizon, local,
-					c(best_window_endo,best_window_exo), "mix", TRUE))
+				best_window_exo = optimize(
+					errorOnLastNdays, c(0,7), simtype="exo")$minimum
 			}
+
+			best_window =
+				if (simtype == "endo")
+					best_window_endo
+				else if (simtype == "exo")
+					best_window_exo
+				else if (simtype == "mix")
+					c(best_window_endo,best_window_exo)
+				else #none: value doesn't matter
+					1
+
+			return(private$.predictShapeAux(data, fdays, today, horizon, local,
+				best_window, simtype, TRUE))
 		}
 	),
 	private = list(
@@ -100,9 +98,9 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					return (NA)
 				levelToday = data$getLevel(today)
 				distances = sapply(fdays, function(i) abs(data$getLevel(i)-levelToday))
-				#TODO: 2, 3, 5, 10 magic numbers here...
+				#TODO: 2, 10, 3, 12 magic numbers here...
 				dist_thresh = 2
-				min_neighbs = min(3,length(fdays))
+				min_neighbs = min(10,length(fdays))
 				repeat
 				{
 					same_pollution = (distances <= dist_thresh)
@@ -112,7 +110,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					dist_thresh = dist_thresh + 3
 				}
 				fdays = fdays[same_pollution]
-				max_neighbs = 10
+				max_neighbs = 12
 				if (nb_neighbs > max_neighbs)
 				{
 					# Keep only max_neighbs closest neighbors
@@ -133,7 +131,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			else
 				fdays = fdays_cut #no conditioning
 
-			if (simtype != "exo")
+			if (simtype == "endo" || simtype == "mix")
 			{
 				# Compute endogen similarities using given window
 				window_endo = ifelse(simtype=="mix", window[1], window)
@@ -154,10 +152,10 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				simils_endo = exp(-distances2/(sd_dist*window_endo^2))
 			}
 
-			if (simtype != "endo")
+			if (simtype == "exo" || simtype == "mix")
 			{
 				# Compute exogen similarities using given window
-				h_exo = ifelse(simtype=="mix", window[2], window)
+				window_exo = ifelse(simtype=="mix", window[2], window)
 
 				M = matrix( nrow=1+length(fdays), ncol=1+length(data$getExo(today)) )
 				M[1,] = c( data$getLevel(today), as.double(data$getExo(today)) )
@@ -192,8 +190,10 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					simils_exo
 				else if (simtype == "endo")
 					simils_endo
-				else #mix
+				else if (simtype == "mix")
 					simils_endo * simils_exo
+				else #none
+					rep(1, length(fdays))
 			similarities = similarities / sum(similarities)
 
 			prediction = rep(0, horizon)
@@ -209,8 +209,10 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 						window_endo
 					else if (simtype=="exo")
 						window_exo
-					else #mix
+					else if (simtype=="mix")
 						c(window_endo,window_exo)
+					else #none
+						1
 			}
 
 			return (prediction)