#' Forecast
#'
#' Forecast encapsulation
#'
#' @docType class
#' @importFrom R6 R6Class
#'
#' @field .pred List with \itemize{
#'   \item serie: forecasted serie
#'   \item params: corresponding list of parameters (weights, neighbors...)
#'   \item index: corresponding index in data object}
#' @field .dates vector of day indices where forcast occurs
#'
#' @section Methods: \describe{
#' \item{\code{initialize(dates)}}
#'   {Initialize a Forecast object with a series of date indices.}
#' \item{\code{getSize()}}
#'   {Return number of individual forecasts.}
#' \item{\code{append(new_serie, new_params, new_index_in_data)}}
#'   {Acquire a new individual forecast, with its (optimized) parameters and the corresponding
#'   index in the dataset.}
#' \item{\code{getDates()}}
#'   {Get dates where forecast occurs.}
#' \item{\code{getSerie(index)}}
#'   {Get forecasted serie at specified index.}
#' \item{\code{getParams(index)}}
#'   {Get parameters at specified index (for 'Neighbors' method).}
#' \item{\code{getIndexInData(index)}}
#'   {Get index in data which corresponds to current forecast.}}
Forecast = R6::R6Class("Forecast",
	private = list(
		.pred = list(),
		.dates = c()
	),
	public = list(
		initialize = function(dates)
		{
			private$.dates <- dates
			invisible(self)
		},
		getSize = function()
			length(private$.pred)
		,
		append = function(new_serie, new_params, new_index_in_data)
		{
			private$.pred[[length(private$.pred)+1]] <-
				list("serie"=new_serie, "params"=new_params, "index_in_data"=new_index_in_data)
		},
		getDates = function()
			private$.dates
		,
		getSerie = function(index)
		{
			if (is(index,"Date"))
				index = match(index, private$.dates)
			private$.pred[[index]]$serie
		},
		getParams = function(index)
		{
			if (is(index,"Date"))
				index = match(index, private$.dates)
			private$.pred[[index]]$params
		},
		getIndexInData = function(index)
		{
			if (is(index,"Date"))
				index = match(index, private$.dates)
			private$.pred[[index]]$index_in_data
		}
	)
)