X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FForecaster.R;h=cedb2b69130b9fb380e437bb36fe528b45a362ad;hb=546b0cb65870355a2a2c3705c91418570499d3a6;hp=47160b561647cc80c454de929384f41df412166f;hpb=5d83d8150dc135347d5ef39e5015b88f33fa9ee3;p=talweg.git

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
index 47160b5..cedb2b6 100644
--- a/pkg/R/Forecaster.R
+++ b/pkg/R/Forecaster.R
@@ -5,43 +5,43 @@
 #' @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 ?
+#' @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.}
+#' }
 #'
-#' @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
 	),
 	public = list(
-		initialize = function(data, pjump)
+		initialize = function(pjump)
 		{
-			private$.data <- data
 			private$.pjump <- pjump
 			invisible(self)
 		},
-		predictSerie = function(today, memory, horizon, ...)
+		predictSerie = function(data, today, memory, horizon, ...)
 		{
 			# Parameters (potentially) computed during shape prediction stage
-			predicted_shape = self$predictShape(today, memory, horizon, ...)
-			predicted_delta = private$.pjump(private$.data,today,memory,horizon,private$.params,...)
+			predicted_shape = self$predictShape(data, today, memory, horizon, ...)
+			predicted_delta = private$.pjump(data,today,memory,horizon,private$.params,...)
 			# Predicted shape is aligned it on the end of current day + jump
-			predicted_shape+tail(private$.data$getSerie(today),1)-predicted_shape[1]+predicted_delta
+			predicted_shape+tail(data$getSerie(today),1)-predicted_shape[1]+predicted_delta
 		},
-		predictShape = function(today, memory, horizon, ...)
+		predictShape = function(data, today, memory, horizon, ...)
 			NULL #empty default implementation: to implement in inherited classes
 		,
 		getParameters = function()