-#' @title get Forecast
+#' Compute forecast
#'
-#' @description Predict time-series curves for the selected days indices (lines in data).
+#' Predict time-series curves for the selected days indices (lines in data).
#'
#' @param data Dataset, object of type \code{Data} output of \code{getData}
#' @param indices Days indices where to forecast (the day after)
#' }
#' @param memory Data depth (in days) to be used for prediction
#' @param horizon Number of time steps to predict
+#' @param ncores Number of cores for parallel execution (1 to disable)
#' @param ... Additional parameters for the forecasting models
#'
-#' @return A list with the following items
-#' \itemize{
-#' \item serie: forecasted serie
-#' \item params: corresponding list of parameters (weights, neighbors...)
-#' \item index: corresponding index in data object
-#' }
+#' @return An object of class Forecast
#'
#' @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 = "Europe/Paris",
-#' working_tz="Europe/Paris", predict_at=7)
+#' data = getData(ts_data, exo_data, input_tz="GMT", working_tz="GMT", predict_at=7)
#' pred = computeForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12)
#' \dontrun{#Sketch for real-time mode:
#' data = new("Data", ...)
#' }}
#' @export
computeForecast = function(data, indices, forecaster, pjump,
- memory=Inf, horizon=data$getStdHorizon(), ...)
+ memory=Inf, horizon=data$getStdHorizon(), ncores=3, ...)
{
# (basic) Arguments sanity checks
horizon = as.integer(horizon)[1]
if (horizon<=0 || horizon>length(data$getCenteredSerie(2)))
stop("Horizon too short or too long")
- indices = sapply( seq_along(indices), function(i) dateIndexToInteger(indices[i], data) )
- if (any(indices<=0 | indices>data$getSize()))
+ integer_indices = sapply(indices, function(i) dateIndexToInteger(i,data))
+ if (any(integer_indices<=0 | integer_indices>data$getSize()))
stop("Indices out of range")
- indices = sapply(indices, dateIndexToInteger, data)
- if (!is.character(forecaster))
- stop("forecaster (name) should be of class character") #pjump could be NULL
+ if (!is.character(forecaster) || !is.character(pjump))
+ stop("forecaster (name) and pjump (function) should be of class character")
- pred = Forecast$new()
+ pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
forecaster_class_name = getFromNamespace(paste(forecaster,"Forecaster",sep=""), "talweg")
- forecaster = forecaster_class_name$new(data=data,
- pjump = getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
- for (today in indices)
+ forecaster = forecaster_class_name$new( #.pjump =
+ getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
+
+ if (ncores > 1 && requireNamespace("parallel",quietly=TRUE))
+ {
+ p <- parallel::mclapply(seq_along(integer_indices), function(i) {
+ list(
+ "forecast" = forecaster$predictSerie(data, integer_indices[i], memory, horizon, ...),
+ "params"= forecaster$getParameters(),
+ "index" = integer_indices[i] )
+ }, mc.cores=ncores)
+ }
+ else
+ {
+ p <- lapply(seq_along(integer_indices), function(i) {
+ list(
+ "forecast" = forecaster$predictSerie(data, integer_indices[i], memory, horizon, ...),
+ "params"= forecaster$getParameters(),
+ "index" = integer_indices[i] )
+ })
+ }
+
+ # TODO: find a way to fill pred in //...
+ for (i in seq_along(integer_indices))
{
pred$append(
- new_serie = forecaster$predictSerie(today, memory, horizon, ...),
- new_params = forecaster$getParameters(),
- new_index = today
+ new_serie = p[[i]]$forecast,
+ new_params = p[[i]]$params,
+ new_index_in_data = p[[i]]$index
)
}
pred