X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FcomputeForecast.R;h=1e7911825c916b537856931d0a8b02b561c58b53;hb=2057c793ad9929ed5bef8663ea28b896c84df0fc;hp=f43019074fbdaae2aa0ae2e1097e71663f38aedc;hpb=af3b84f4cacade7d83221ca0249b546c50ddf340;p=talweg.git

diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
index f430190..1e79118 100644
--- a/pkg/R/computeForecast.R
+++ b/pkg/R/computeForecast.R
@@ -2,8 +2,9 @@
 #'
 #' 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 data Object of type \code{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 forcaster
 #' \itemize{
 #'   \item Persistence : use values of last (similar, next) day
@@ -19,6 +20,7 @@
 #' }
 #' @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 +28,7 @@
 #' @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", ...)
@@ -39,28 +40,52 @@
 #' }}
 #' @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$getCenteredSerie(2)))
+	if (horizon<=0 || horizon>length(data$getCenteredSerie(1)))
 		stop("Horizon too short or too long")
-	integer_indices = sapply(seq_along(indices), function(i) dateIndexToInteger(indices[i],data))
+	integer_indices = sapply(indices, function(i) dateIndexToInteger(i,data))
 	if (any(integer_indices<=0 | integer_indices>data$getSize()))
 		stop("Indices out of range")
 	if (!is.character(forecaster) || !is.character(pjump))
 		stop("forecaster (name) and pjump (function) should be of class character")
 
-	pred = Forecast$new( dates=sapply( indices, integerIndexToDate, data ) )
-	forecaster_class_name = getFromNamespace(paste(forecaster,"Forecaster",sep=""), "talweg")
-	forecaster = forecaster_class_name$new(.data=data,
-		.pjump = getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
-	for (today in integer_indices)
+	pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
+	forecaster_class_name = getFromNamespace(
+		paste(forecaster,"Forecaster",sep=""), "talweg")
+	forecaster = forecaster_class_name$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$getParameters(),
-			new_index = today
+			forecast = p[[i]]$forecast,
+			params = p[[i]]$params,
+			index_in_data = p[[i]]$index
 		)
 	}
 	pred