new version, persistence -7 days

[talweg.git] / R / F_Neighbors.R

diff --git a/R/S_Neighbors.R b/R/F_Neighbors.R
similarity index 88%
rename from R/S_Neighbors.R
rename to R/F_Neighbors.R
index b8e32cc..f1aecb5 100644 (file)
--- a/R/S_Neighbors.R
+++ b/R/F_Neighbors.R
@@ -1,19 +1,19 @@
-#' @include ShapeForecaster.R
+#' @include Forecaster.R
 #'
-#' @title Neighbors Shape Forecaster
+#' @title Neighbors Forecaster
 #'
 #' @description Predict tomorrow as a weighted combination of "futures of the past" days.
-#'   Inherits \code{\link{ShapeForecaster}}
-NeighborsShapeForecaster = setRefClass(
-       Class = "NeighborsShapeForecaster",
-       contains = "ShapeForecaster",
+#'   Inherits \code{\link{Forecaster}}
+NeighborsForecaster = setRefClass(
+       Class = "NeighborsForecaster",
+       contains = "Forecaster",
 
        methods = list(
                initialize = function(...)
                {
                        callSuper(...)
                },
-               predict = function(today, memory, horizon, ...)
+               predictShape = function(today, memory, horizon, ...)
                {
                        # (re)initialize computed parameters
                        params <<- list("weights"=NA, "indices"=NA, "window"=NA)
@@ -67,8 +67,8 @@ NeighborsShapeForecaster = setRefClass(
                        mix_strategy = ifelse(hasArg("mix_strategy"), list(...)$mix_strategy, "neighb") #or "mult"
                        same_season = ifelse(hasArg("same_season"), list(...)$same_season, TRUE)
                        if (hasArg(h_window))
-                               return (.predictAux(fdays_indices, today, horizon, list(...)$h_window, kernel, simtype,
-                                       simthresh, mix_strategy, FALSE))
+                               return (.predictShapeAux(fdays_indices, today, horizon, list(...)$h_window, kernel,
+                                       simtype, simthresh, mix_strategy, FALSE))
                        #END GET
 
                        # Indices for cross-validation; TODO: 45 = magic number
@@ -87,8 +87,8 @@ NeighborsShapeForecaster = setRefClass(
                                        {
                                                nb_jours = nb_jours + 1
                                                # mix_strategy is never used here (simtype != "mix"), therefore left blank
-                                               prediction = .predictAux(fdays_indices, i, horizon, h, kernel, simtype, simthresh,
-                                                       "", FALSE)
+                                               prediction = .predictShapeAux(fdays_indices, i, horizon, h, kernel, simtype,
+                                                       simthresh, "", FALSE)
                                                if (!is.na(prediction[1]))
                                                        error = error + mean((data$getCenteredSerie(i+1)[1:horizon] - prediction)^2)
                                        }
@@ -110,22 +110,22 @@ NeighborsShapeForecaster = setRefClass(
 
                        if (simtype == "endo")
                        {
-                               return (.predictAux(fdays_indices, today, horizon, h_best_endo, kernel, "endo",
+                               return (.predictShapeAux(fdays_indices, today, horizon, h_best_endo, kernel, "endo",
                                        simthresh, "", TRUE))
                        }
                        if (simtype == "exo")
                        {
-                               return (.predictAux(fdays_indices, today, horizon, h_best_exo, kernel, "exo",
+                               return (.predictShapeAux(fdays_indices, today, horizon, h_best_exo, kernel, "exo",
                                        simthresh, "", TRUE))
                        }
                        if (simtype == "mix")
                        {
-                               return (.predictAux(fdays_indices, today, horizon, c(h_best_endo,h_best_exo), kernel,
-                                       "mix", simthresh, mix_strategy, TRUE))
+                               return (.predictShapeAux(fdays_indices, today, horizon, c(h_best_endo,h_best_exo),
+                                       kernel, "mix", simthresh, mix_strategy, TRUE))
                        }
                },
                # Precondition: "today" is full (no NAs)
-               .predictAux = function(fdays_indices, today, horizon, h, kernel, simtype, simthresh,
+               .predictShapeAux = function(fdays_indices, today, horizon, h, kernel, simtype, simthresh,
                        mix_strategy, final_call)
                {
                        dat = data$data #HACK: faster this way...