#' @title get Forecast #' #' @description 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 forecaster Name of the main forcaster #' \itemize{ #' \item Persistence : use values of last (similar, next) day #' \item Neighbors : use values from the k closest neighbors' tomorrows #' \item Average : global average of all the (similar) "tomorrow of past" #' \item Zero : just output 0 (benchmarking purpose) #' } #' @param pjump How to predict the jump at the interface between two days ? #' \itemize{ #' \item Persistence : use last (similar) day values #' \item Neighbors: re-use the weights optimized in corresponding forecaster #' \item Zero: just output 0 (no adjustment) #' } #' @param memory Data depth (in days) to be used for prediction #' @param horizon Number of time steps to predict #' @param ... Additional parameters for the forecasting models #' #' @return An object of class Forecast #' #' @examples #' data = getData(ts_data="data/pm10_mesures_H_loc.csv", exo_data="data/meteo_extra_noNAs.csv", #' input_tz = "Europe/Paris", working_tz="Europe/Paris", predict_at=7) #' pred = getForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12) #' \dontrun{#Sketch for real-time mode: #' data = new("Data", ...) #' forecaster = new(..., data=data) #' repeat { #' data$append(some_new_data) #' pred = forecaster$predict(data$getSize(), ...) #' #do_something_with_pred #' }} #' @export getForecast = function(data, indices, forecaster, pjump=NULL, memory=Inf, horizon=data$getStdHorizon(), ...) { # (basic) Arguments sanity checks horizon = as.integer(horizon)[1] if (horizon<=0 || horizon>length(data$getCenteredSerie(2))) stop("Horizon too short or too long") indices = sapply( seq_along(indices), function(i) dateIndexToInteger(indices[i], data) ) if (any(indices<=0 | indices>data$getSize())) stop("Indices out of range") indices = sapply(indices, dateIndexToInteger, data) if (!is.character(forecaster)) stop("forecaster (name) should be of class character") #pjump could be NULL pred = list() forecaster = new(paste(forecaster,"Forecaster",sep=""), data=data, pjump = if (is.null(pjump)) function() {} else getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")) for (today in indices) { #pred$append(...) is slow; TODO: use R6 class pred[[length(pred)+1]] = list( "serie" = forecaster$predict(today, memory, horizon, ...), "params" = forecaster$getParameters(), "index" = today ) } new("Forecast",pred=pred) }