X-Git-Url: https://git.auder.net/?p=talweg.git;a=blobdiff_plain;f=pkg%2FR%2FForecaster.R;h=2bd2e4ea0a4dae7ed32b4f695d1a17ae425e39ac;hp=4c8437e195b6bcf6ab501ec187e23bd42d0469cd;hb=a66a84b56467194852f2faee15f4725759b24158;hpb=25b75559e2d9bf84e2de35b851d93fefdae36e17

diff --git a/pkg/R/Forecaster.R b/pkg/R/Forecaster.R
index 4c8437e..2bd2e4e 100644
--- a/pkg/R/Forecaster.R
+++ b/pkg/R/Forecaster.R
@@ -2,70 +2,49 @@
 #'
 #' 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 ?
 #'
-#' @docType class
-#' @importFrom R6 R6Class
+#' @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 = "Data",
-		.pjump = "function"
+		.params = list(),
+		.data = NULL,
+		.pjump = NULL
 	),
 	public = list(
 		initialize = function(data, pjump)
-			initialize(self, private, data, pjump)
-		,
+		{
+			private$.data <- data
+			private$.pjump <- pjump
+			invisible(self)
+		},
 		predictSerie = function(today, memory, horizon, ...)
-			predictSerie(private, today, memory, horizon, ...)
-		,
+		{
+			# Parameters (potentially) computed during shape prediction stage
+			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(private$.data$getSerie(today),1)-predicted_shape[1]+predicted_delta
+		},
 		predictShape = function(today, memory, horizon, ...)
-			predictShape(private, today, memory, horizon, ...)
+			#empty default implementation: to implement in inherited classes
 		,
 		getParameters = function()
-			getParameters(private)
+			private$.params
 	)
 )
-
-#' Initialize (generic) Forecaster object
-#'
-#' @param o Object of class Forecaster
-#' @param private List of private members in o
-#' @param data Object of class Data
-#' @param pjump Function to predict jump
-initialize = function(o, private, data, pjump)
-{
-	.params <<- list()
-	.data <<- data
-	.pjump <<- pjump
-	invisible(o)
-}
-
-#' Obtain a new forecasted time-serie
-#'
-#' @inheritParams initialize
-#' @param today Index for current prediction
-#' @param memory Depth in data (in days)
-#' @param horizon Number of hours to forecast
-predictSerie = function(private, today, memory, horizon, ...)
-{
-	# Parameters (potentially) computed during shape prediction stage
-	predicted_shape = predictShape(today, memory, horizon, ...)
-	predicted_delta = private$.pjump(private$.data, today, memory, horizon, params, ...)
-	# Predicted shape is aligned it on the end of current day + jump
-	predicted_shape + tail(private$.data$getSerie(today),1) - predicted_shape[1] + predicted_delta
-}
-
-#' Shape prediction (centered curve)
-#'
-#' @inheritParams predictSerie
-predictShape = function(private, today, memory, horizon, ...)
-	#empty default implementation: to implement in inherited classes
-
-#' Get parameters list
-#'
-#' @inheritParams initialize
-getParameters = function(private)
-	private$.params