X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FcomputeForecast.R;h=1e7911825c916b537856931d0a8b02b561c58b53;hb=2057c793ad9929ed5bef8663ea28b896c84df0fc;hp=d6355602e211bb0245000ce90c9f10c2bf63bed5;hpb=ee8b1b4e3c13f8dcf13a2c8da6a3bef1520c8252;p=talweg.git

diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
index d635560..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
@@ -27,8 +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", ...)
@@ -44,7 +44,7 @@ computeForecast = function(data, indices, forecaster, pjump,
 {
 	# (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(indices, function(i) dateIndexToInteger(i,data))
 	if (any(integer_indices<=0 | integer_indices>data$getSize()))
@@ -53,7 +53,8 @@ computeForecast = function(data, indices, forecaster, pjump,
 		stop("forecaster (name) and pjump (function) should be of class character")
 
 	pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
-	forecaster_class_name = getFromNamespace(paste(forecaster,"Forecaster",sep=""), "talweg")
+	forecaster_class_name = getFromNamespace(
+		paste(forecaster,"Forecaster",sep=""), "talweg")
 	forecaster = forecaster_class_name$new( #.pjump =
 		getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
 
@@ -61,7 +62,8 @@ computeForecast = function(data, indices, forecaster, pjump,
 	{
 		p <- parallel::mclapply(seq_along(integer_indices), function(i) {
 			list(
-				"forecast" = forecaster$predictSerie(data, integer_indices[i], memory, horizon, ...),
+				"forecast" = forecaster$predictSerie(
+					data, integer_indices[i], memory, horizon, ...),
 				"params"= forecaster$getParameters(),
 				"index" = integer_indices[i] )
 			}, mc.cores=ncores)
@@ -70,7 +72,8 @@ computeForecast = function(data, indices, forecaster, pjump,
 	{
 		p <- lapply(seq_along(integer_indices), function(i) {
 			list(
-				"forecast" = forecaster$predictSerie(data, integer_indices[i], memory, horizon, ...),
+				"forecast" = forecaster$predictSerie(
+					data, integer_indices[i], memory, horizon, ...),
 				"params"= forecaster$getParameters(),
 				"index" = integer_indices[i] )
 			})
@@ -80,9 +83,9 @@ computeForecast = function(data, indices, forecaster, pjump,
 	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
+			forecast = p[[i]]$forecast,
+			params = p[[i]]$params,
+			index_in_data = p[[i]]$index
 		)
 	}
 	pred