X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FcomputeForecast.R;h=24f114ea9be978a29b5187e846ac4125f8a36214;hb=445e7bbc18aa739ec0b3caba4d8710a9d9e1a43c;hp=3537e8a8c2ba090b46989a3aafc88605f2840682;hpb=5e838b3e17465c376ca075b766cf2543c82e9864;p=talweg.git

diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
index 3537e8a..24f114e 100644
--- a/pkg/R/computeForecast.R
+++ b/pkg/R/computeForecast.R
@@ -19,6 +19,7 @@
 #' }
 #' @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
@@ -26,8 +27,7 @@
 #' @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", ...)
@@ -39,7 +39,7 @@
 #' }}
 #' @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]
@@ -56,27 +56,33 @@ computeForecast = function(data, indices, forecaster, pjump,
 	forecaster = forecaster_class_name$new( #.pjump =
 		getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
 
-#oo = forecaster$predictSerie(data, integer_indices[1], memory, horizon, ...)
-#browser()
-
-	library(parallel)
-	ppp <- parallel::mclapply(seq_along(integer_indices), function(i) {
-		list(
-			"forecast" = forecaster$predictSerie(data, integer_indices[i], memory, horizon, ...),
-			"params"= forecaster$getParameters(),
-			"index" = integer_indices[i] )
-		}, mc.cores=3)
-
-#browser()
-
-for (i in seq_along(integer_indices))
-{
-	pred$append(
-			new_serie = ppp[[i]]$forecast,
-			new_params = ppp[[i]]$params,
-			new_index_in_data = ppp[[i]]$index
-	)
-}
+	if (ncores > 1 && requireNamespace("parallel",quietly=TRUE))
+	{
+		p <- parallel::mclapply(seq_along(integer_indices), function(i) {
+			list(
+				"forecast" = forecaster$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$append(
+			new_serie = p[[i]]$forecast,
+			new_params = p[[i]]$params,
+			new_index_in_data = p[[i]]$index
+		)
+	}
 	pred
 }