#' }
#' @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 An object of class Forecast
#' }}
#' @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]
forecaster = forecaster_class_name$new( #.pjump =
getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
-#oo = forecaster$predictSerie(data, integer_indices[1], memory, horizon, ...)
-#browser()
-
- parll=TRUE #FALSE
- if (parll)
+ if (ncores > 1 && requireNamespace("parallel",quietly=TRUE))
{
- library(parallel)
- ppp <- parallel::mclapply(seq_along(integer_indices), function(i) {
+ 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=3)
+ }, mc.cores=ncores)
}
else
{
- ppp <- lapply(seq_along(integer_indices), function(i) {
+ 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] )
})
}
-#browser()
-
-for (i in seq_along(integer_indices))
-{
- pred$append(
- new_serie = ppp[[i]]$forecast,
- new_params = ppp[[i]]$params,
- new_index_in_data = ppp[[i]]$index
- )
-}
+ # TODO: find a way to fill pred in //...
+ for (i in seq_along(integer_indices))
+ {
+ pred$append(
+ new_serie = p[[i]]$forecast,
+ new_params = p[[i]]$params,
+ new_index_in_data = p[[i]]$index
+ )
+ }
pred
}