#' Compute forecast
#'
-#' Predict time-series curves for the selected days indices (lines in data).
+#' Predict time-series curves ("tomorrows") at the selected days indices ("todays").
+#' This function just runs a loop over all requested indices, and stores the individual
+#' forecasts into a list which is then turned into a Forecast object.
#'
-#' @param data Object of type \code{Data}, output of \code{getData()}.
+#' @param data Object of class Data, output of \code{getData()}.
#' @param indices Indices where to forecast (the day after); integers relative to the
#' beginning of data, or (convertible to) Date objects.
#' @param forecaster Name of the main forecaster; more details: ?F_<forecastername>
#' @examples
#' ts_data <- system.file("extdata","pm10_mesures_H_loc.csv",package="talweg")
#' exo_data <- system.file("extdata","meteo_extra_noNAs.csv",package="talweg")
-#' data <- getData(ts_data, exo_data, input_tz="GMT", working_tz="GMT", predict_at=7)
-#' pred <- computeForecast(data, 2200:2230, "Persistence", "Zero",
-#' memory=500, horizon=12, ncores=1)
+#' data <- getData(ts_data, exo_data, input_tz="GMT", working_tz="GMT",
+#' predict_at=7, limit=200)
+#' pred <- computeForecast(data, 100:130, "Persistence", "Zero",
+#' memory=50, horizon=12, ncores=1)
#' \dontrun{#Sketch for real-time mode:
#' data <- Data$new()
-#' # Initialize: first day has no predictions attached
-#' data$initialize()
#' forecaster <- MyForecaster$new(myJumpPredictFunc)
#' repeat {
-#' # During the night between days j and j+1:
-#' data$appendExoHat(exogenous_predictions)
#' # In the morning 7am+ or afternoon 1pm+:
-#' data$setMeasures(
-#' data$getSize()-1,
+#' data$append(
#' times_from_H+1_yersteday_to_Hnow,
#' PM10_values_of_last_24h,
-#' exogenous_measures_for_yersteday)
-#' pred <- forecaster$predictSerie(data, data$getSize()-1, ...)
+#' exogenous_measures_of_last_24h,
+#' exogenous_predictions_for_next_24h)
+#' pred <- forecaster$predictSerie(data, data$getSize(), ...)
#' #do_something_with_pred
#' }}
#' @export