[talweg.git] / pkg / R / computeError.R

#' @title Get error
#'
#' @description Obtain the errors between forecast and data
#'
#' @param data Dataset, object of class \code{Data} output of \code{getData}
#' @param forecast Forecast object, class \code{Forecast} output of \code{computeForecast}
#' @param horizon Horizon where to compute the error (<= horizon used in \code{computeForecast})
#'
#' @return A list (abs,MAPE) of lists (day,indices)
#'
#' @export
computeError = function(data, forecast, horizon=data$getStdHorizon())
{
	L = forecast$getSize()
	mape_day = rep(0, horizon)
	abs_day = rep(0, horizon)
	mape_indices = rep(NA, L)
	abs_indices = rep(NA, L)

	nb_no_NA_data = 0
	for (i in seq_len(L))
	{
		index = forecast$getIndexInData(i)
		serie = data$getSerie(index+1)[1:horizon]
		pred = forecast$getSerie(i)[1:horizon]
		if (!any(is.na(serie)) && !any(is.na(pred)))
		{
			nb_no_NA_data = nb_no_NA_data + 1
			mape_increment = abs(serie - pred) / serie
			mape_increment[is.nan(mape_increment)] = 0. # 0 / 0
			mape_increment[!is.finite(mape_increment)] = 1. # >0 / 0
			mape_day = mape_day + mape_increment
			abs_increment = abs(serie - pred)
			abs_day = abs_day + abs_increment
			mape_indices[i] = mean(mape_increment)
			abs_indices[i] = mean(abs_increment)
		}
	}

	list(
		"abs" = list(
			"day" = abs_day / nb_no_NA_data,
			"indices" = abs_indices),
		"MAPE" = list(
			"day" = mape_day / nb_no_NA_data,
			"indices" = mape_indices) )
}
Commit	Line	Data
	1	#' @title Get error
	2	#'
	3	#' @description Obtain the errors between forecast and data
	4	#'
	5	#' @param data Dataset, object of class \code{Data} output of \code{getData}
	6	#' @param forecast Forecast object, class \code{Forecast} output of \code{computeForecast}
	7	#' @param horizon Horizon where to compute the error (<= horizon used in \code{computeForecast})
	8	#'
	9	#' @return A list (abs,MAPE) of lists (day,indices)
	10	#'
	11	#' @export
	12	computeError = function(data, forecast, horizon=data$getStdHorizon())
	13	{
	14	L = forecast$getSize()
	15	mape_day = rep(0, horizon)
	16	abs_day = rep(0, horizon)
	17	mape_indices = rep(NA, L)
	18	abs_indices = rep(NA, L)
	19
	20	nb_no_NA_data = 0
	21	for (i in seq_len(L))
	22	{
	23	index = forecast$getIndexInData(i)
	24	serie = data$getSerie(index+1)[1:horizon]
	25	pred = forecast$getSerie(i)[1:horizon]
	26	if (!any(is.na(serie)) && !any(is.na(pred)))
	27	{
	28	nb_no_NA_data = nb_no_NA_data + 1
	29	mape_increment = abs(serie - pred) / serie
	30	mape_increment[is.nan(mape_increment)] = 0. # 0 / 0
	31	mape_increment[!is.finite(mape_increment)] = 1. # >0 / 0
	32	mape_day = mape_day + mape_increment
	33	abs_increment = abs(serie - pred)
	34	abs_day = abs_day + abs_increment
	35	mape_indices[i] = mean(mape_increment)
	36	abs_indices[i] = mean(abs_increment)
	37	}
	38	}
	39
	40	list(
	41	"abs" = list(
	42	"day" = abs_day / nb_no_NA_data,
	43	"indices" = abs_indices),
	44	"MAPE" = list(
	45	"day" = mape_day / nb_no_NA_data,
	46	"indices" = mape_indices) )
	47	}