add realtime option, slightly refactor data acquisition

[talweg.git] / pkg / R / computeForecast.R

diff --git a/pkg/R/computeForecast.R b/pkg/R/computeForecast.R
index d635560..198f6ec 100644 (file)
--- a/pkg/R/computeForecast.R
+++ b/pkg/R/computeForecast.R
@@ -20,15 +20,15 @@
 #' @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
+#' @param ... Additional parameters for the forecasting models;
+#'   In particular, realtime=TRUE to use predictions instead of measurements
 #'
 #' @return An object of class Forecast
 #'
 #' @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