X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2FForecaster.R;h=da8579b7312bfcc520d8e2a8504202bb68ff2cbd;hp=2955479007e57eb5b4a63f7d520631e651a7d0bd;hb=98e958cab563866f8e00886b54336018a2e8bc97;hpb=af3b84f4cacade7d83221ca0249b546c50ddf340

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
index 2955479..da8579b 100644
--- a/pkg/R/Forecaster.R
+++ b/pkg/R/Forecaster.R
@@ -5,45 +5,41 @@
 #' @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}
+#' @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}
+#' \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.}}
+#' \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()