X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FForecaster.R;h=da8579b7312bfcc520d8e2a8504202bb68ff2cbd;hb=ff5df8e310b73883565761ab4b1aa5a0672e9f27;hp=d5d5280c997a735f59215a09d464c3bdc2bf0eea;hpb=1e20780ee1505fac6c7ed68d340892c497524561;p=talweg.git

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
index d5d5280..da8579b 100644
--- a/pkg/R/Forecaster.R
+++ b/pkg/R/Forecaster.R
@@ -1,50 +1,48 @@
-#' @title Forecaster (abstract class)
+#' Forecaster
 #'
-#' @description Abstract class to represent a forecaster (they all inherit this)
+#' Forecaster (abstract class, implemented by all forecasters)
 #'
-#' @field params List of computed parameters, for post-run analysis (dev)
-#' @field data Dataset, object of class Data
-#' @field pjump Function: how to predict the jump at day interface ?
-Forecaster = setRefClass(
-	Class = "Forecaster",
-
-	fields = list(
-		params = "list",
-		data = "Data",
-		pjump = "function"
+#' @docType class
+#' @importFrom R6 R6Class
+#'
+#' @field .params List of computed parameters, for post-run analysis (dev)
+#' @field .pjump Function: how to predict the jump at day interface ?
+#'
+#' @section Methods:
+#' \describe{
+#' \item{\code{initialize(data, pjump)}}{
+#'   Initialize a Forecaster object with a Data object and a jump prediction function.}
+#' \item{\code{predictSerie(today,memory,horizon,...)}}{
+#'   Predict a new serie of \code{horizon} values at day index \code{today}
+#'   using \code{memory} days in the past.}
+#' \item{\code{predictShape(today,memory,horizon,...)}}{
+#'   Predict a new shape of \code{horizon} values at day index \code{today}
+#'   using \code{memory} days in the past.}
+#' \item{\code{getParameters()}}{
+#'   Return (internal) parameters.}}
+Forecaster = R6::R6Class("Forecaster",
+	private = list(
+		.params = list(),
+		.pjump = NULL
 	),
-
-	methods = list(
-		initialize = function(...)
+	public = list(
+		initialize = function(pjump)
 		{
-			"Initialize (generic) Forecaster object"
-
-			callSuper(...)
-			if (!hasArg(data))
-				stop("Forecaster must be initialized with a Data object")
-			params <<- list()
+			private$.pjump <- pjump
+			invisible(self)
 		},
-		predict = function(today, memory, horizon, ...)
+		predictSerie = function(data, today, memory, horizon, ...)
 		{
-			"Obtain a new forecasted time-serie"
-
 			# Parameters (potentially) computed during shape prediction stage
-			predicted_shape = predictShape(today, memory, horizon, ...)
-			predicted_delta = pjump(data, today, memory, horizon, params, ...)
+			predicted_shape = self$predictShape(data, today, memory, horizon, ...)
+			predicted_delta = private$.pjump(data,today,memory,horizon,private$.params,...)
 			# Predicted shape is aligned it on the end of current day + jump
-			predicted_shape + tail(data$getSerie(today),1) - predicted_shape[1] + predicted_delta
-		},
-		predictShape = function(today, memory, horizon, ...)
-		{
-			"Shape prediction (centered curve)"
-
-			#empty default implementation: to implement in inherited classes
+			predicted_shape+tail(data$getSerie(today),1)-predicted_shape[1]+predicted_delta
 		},
+		predictShape = function(data, today, memory, horizon, ...)
+			NULL #empty default implementation: to implement in inherited classes
+		,
 		getParameters = function()
-		{
-			"Get parameters list"
-
-			params
-		}
+			private$.params
 	)
 )