X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2FF_Neighbors.R;h=5b2c8990a850d2dff0d75c23d67815e7393ccd07;hp=238274bd5f8b1202ab601c8ecea5aad83fc4b578;hb=5e838b3e17465c376ca075b766cf2543c82e9864;hpb=98e958cab563866f8e00886b54336018a2e8bc97

diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index 238274b..5b2c899 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -4,6 +4,7 @@
 #'
 #' Predict tomorrow as a weighted combination of "futures of the past" days.
 #' Inherits \code{\link{Forecaster}}
+#'
 NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 	inherit = Forecaster,
 
@@ -13,6 +14,10 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			# (re)initialize computed parameters
 			private$.params <- list("weights"=NA, "indices"=NA, "window"=NA)
 
+			# Do not forecast on days with NAs (TODO: softer condition...)
+			if (any(is.na(data$getCenteredSerie(today))))
+				return (NA)
+
 			# Determine indices of no-NAs days followed by no-NAs tomorrows
 			fdays = getNoNA2(data, max(today-memory,1), today-1)
 
@@ -28,21 +33,25 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			# Indices of similar days for cross-validation; TODO: 45 = magic number
 			sdays = getSimilarDaysIndices(today, limit=45, same_season=FALSE)
 
+			cv_days = intersect(fdays,sdays)
+			# Limit to 20 most recent matching days (TODO: 20 == magic number)
+			cv_days = sort(cv_days,decreasing=TRUE)[1:min(20,length(cv_days))]
+
 			# Function to optimize h : h |--> sum of prediction errors on last 45 "similar" days
 			errorOnLastNdays = function(h, kernel, simtype)
 			{
 				error = 0
 				nb_jours = 0
-				for (i in intersect(fdays,sdays))
+				for (i in seq_along(cv_days))
 				{
 					# mix_strategy is never used here (simtype != "mix"), therefore left blank
 					prediction = private$.predictShapeAux(data,
-						fdays, i, horizon, h, kernel, simtype, FALSE)
+						fdays, cv_days[i], horizon, h, kernel, simtype, FALSE)
 					if (!is.na(prediction[1]))
 					{
 						nb_jours = nb_jours + 1
 						error = error +
-							mean((data$getCenteredSerie(i+1)[1:horizon] - prediction)^2)
+							mean((data$getCenteredSerie(cv_days[i]+1)[1:horizon] - prediction)^2)
 					}
 				}
 				return (error / nb_jours)
@@ -91,22 +100,24 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				h_endo = ifelse(simtype=="mix", h[1], h)
 
 				# Distances from last observed day to days in the past
-				distances2 = rep(NA, length(fdays))
-				for (i in seq_along(fdays))
-				{
-					delta = data$getCenteredSerie(today) - data$getCenteredSerie(fdays[i])
-					# Require at least half of non-NA common values to compute the distance
-					if (sum(is.na(delta)) <= 0) #length(delta)/2)
-						distances2[i] = mean(delta^2) #, na.rm=TRUE)
-				}
+				serieToday = data$getSerie(today)
+				distances2 = sapply(fdays, function(i) {
+					delta = serieToday - data$getSerie(i)
+					mean(delta^2)
+				})
 
 				sd_dist = sd(distances2)
 				if (sd_dist < .Machine$double.eps)
+				{
+#					warning("All computed distances are very close: stdev too small")
 					sd_dist = 1 #mostly for tests... FIXME:
+				}
 				simils_endo =
 					if (kernel=="Gauss")
 						exp(-distances2/(sd_dist*h_endo^2))
-					else { #Epanechnikov
+					else
+					{
+						# Epanechnikov
 						u = 1 - distances2/(sd_dist*h_endo^2)
 						u[abs(u)>1] = 0.
 						u
@@ -126,18 +137,23 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				sigma_inv = solve(sigma) #TODO: use pseudo-inverse if needed?
 
 				# Distances from last observed day to days in the past
-				distances2 = rep(NA, nrow(M)-1)
-				for (i in 2:nrow(M))
-				{
-					delta = M[1,] - M[i,]
-					distances2[i-1] = delta %*% sigma_inv %*% delta
-				}
+				distances2 = sapply(seq_along(fdays), function(i) {
+					delta = M[1,] - M[i+1,]
+					delta %*% sigma_inv %*% delta
+				})
 
 				sd_dist = sd(distances2)
+				if (sd_dist < .Machine$double.eps)
+				{
+#					warning("All computed distances are very close: stdev too small")
+					sd_dist = 1 #mostly for tests... FIXME:
+				}
 				simils_exo =
 					if (kernel=="Gauss")
 						exp(-distances2/(sd_dist*h_exo^2))
-					else { #Epanechnikov
+					else
+					{
+						# Epanechnikov
 						u = 1 - distances2/(sd_dist*h_exo^2)
 						u[abs(u)>1] = 0.
 						u
@@ -154,7 +170,7 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 
 			prediction = rep(0, horizon)
 			for (i in seq_along(fdays))
-				prediction = prediction + similarities[i] * data$getSerie(fdays[i]+1)[1:horizon]
+				prediction = prediction + similarities[i] * data$getCenteredSerie(fdays[i]+1)[1:horizon]
 			prediction = prediction / sum(similarities, na.rm=TRUE)
 
 			if (final_call)
@@ -162,13 +178,12 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 				private$.params$weights <- similarities
 				private$.params$indices <- fdays
 				private$.params$window <-
-					if (simtype=="endo") {
+					if (simtype=="endo")
 						h_endo
-					} else if (simtype=="exo") {
+					else if (simtype=="exo")
 						h_exo
-					} else { #mix
+					else #mix
 						c(h_endo,h_exo)
-					}
 			}
 
 			return (prediction)