#' \itemize{
#' \item Persistence : use last (similar) day
#' \item Neighbors: re-use the weights from F_Neighbors
-#' \item Zero: just output 0 (no adjustment)
+#' \item LastValue: start serie with last observed value
+#' \item Zero: no adjustment => use shape prediction only
#' }
-#' If pjump=NULL, then no adjustment is performed (output of \code{predictShape()} is
-#' used directly).
#' @param predict_from First time step to predict.
#' @param memory Data depth (in days) to be used for prediction.
#' @param horizon Last time step to predict.
#' @param ncores Number of cores for parallel execution (1 to disable).
+#' @param verbose TRUE to print basic traces (runs beginnings)
#' @param ... Additional parameters for the forecasting models.
#'
#' @return An object of class Forecast
#' 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, limit=200)
-#' pred <- computeForecast(data, 100:130, "Persistence", "Zero",
+#' pred <- computeForecast(data, 100:130, "Persistence", "LastValue",
#' predict_from=8, memory=50, horizon=12, ncores=1)
#' \dontrun{
#' #Sketch for real-time mode:
#' } }
#' @export
computeForecast = function(data, indices, forecaster, pjump, predict_from,
- memory=Inf, horizon=length(data$getSerie(1)), ncores=3, ...)
+ memory=Inf, horizon=length(data$getSerie(1)), ncores=3, verbose=FALSE, ...)
{
# (basic) Arguments sanity checks
predict_from = as.integer(predict_from)[1]
stop("Indices out of range")
if (!is.character(forecaster))
stop("forecaster (name): character")
- if (!is.null(pjump) && !is.character(pjump))
- stop("pjump (function): character or NULL")
+ if (!is.character(pjump))
+ stop("pjump (function): character")
pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) )
forecaster_class_name = getFromNamespace(
paste(forecaster,"Forecaster",sep=""), "talweg")
- if (!is.null(pjump))
- pjump <- getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")
+ pjump <- getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")
forecaster = forecaster_class_name$new(pjump)
computeOneForecast <- function(i)
{
+ if (verbose)
+ print(paste("Index",i))
list(
"forecast" = forecaster$predictSerie(data,i,memory,predict_from,horizon,...),
"params" = forecaster$getParameters(),