#' @title Forecaster (abstract class)
#'
#' @description Abstract class to represent a forecaster (they all inherit this)
#'
#' @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"
	),

	methods = list(
		initialize = function(...)
		{
			"Initialize (generic) Forecaster object"

			callSuper(...)
			if (!hasArg(data))
				stop("Forecaster must be initialized with a Data object")
			params <<- list()
		},
		predict = 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 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
		},
		getParameters = function()
		{
			"Get parameters list"

			params
		}
	)
)