X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FForecaster.R;h=2bd2e4ea0a4dae7ed32b4f695d1a17ae425e39ac;hb=a66a84b56467194852f2faee15f4725759b24158;hp=71cb667430a94a1a2f91e807c7231bf795f709ae;hpb=469529710f56c790ae932b45d13fed2e34bcabf2;p=talweg.git

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
index 71cb667..2bd2e4e 100644
--- a/pkg/R/Forecaster.R
+++ b/pkg/R/Forecaster.R
@@ -1,48 +1,50 @@
-#' @title Forecaster (abstract class)
+#' Forecaster
 #'
-#' @description Abstract class to represent a forecaster (they all inherit this)
+#' Forecaster (abstract class, implemented by all forecasters)
+#'
+#' @docType class
+#' @importFrom R6 R6Class
 #'
 #' @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"
+#'
+#' @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(),
+		.data = NULL,
+		.pjump = NULL
 	),
-
-	methods = list(
-		initialize = function(...)
+	public = list(
+		initialize = function(data, pjump)
 		{
-			"Initialize (generic) Forecaster object"
-
-			callSuper(...)
-			if (!hasArg(data))
-				stop("Forecaster must be initialized with a Data object")
-			params <<- list()
+			private$.data <- data
+			private$.pjump <- pjump
+			invisible(self)
 		},
-		predict = function(today, memory, horizon, ...)
+		predictSerie = function(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 = o$predictShape(today, memory, horizon, ...)
+			predicted_delta = private$.pjump(private$.data,today,memory,horizon,private$.params,...)
 			# Predicted shape is aligned it on the end of current day + jump
-			predicted_shape + tail(data$getSerie(today),1) - predicted_shape[1] + predicted_delta
+			predicted_shape+tail(private$.data$getSerie(today),1)-predicted_shape[1]+predicted_delta
 		},
 		predictShape = function(today, memory, horizon, ...)
-		{
-			"Shape prediction (centered curve)"
-
 			#empty default implementation: to implement in inherited classes
-		},
+		,
 		getParameters = function()
-		{
-			params
-		}
+			private$.params
 	)
 )