| 1 | #' @title get Forecast |
| 2 | #' |
| 3 | #' @description Predict time-series curves for the selected days indices (lines in data). |
| 4 | #' |
| 5 | #' @param data Dataset, object of type \code{Data} output of \code{getData} |
| 6 | #' @param indices Days indices where to forecast (the day after) |
| 7 | #' @param forecaster Name of the main forcaster |
| 8 | #' \itemize{ |
| 9 | #' \item Persistence : use values of last (similar, next) day |
| 10 | #' \item Neighbors : use values from the k closest neighbors' tomorrows |
| 11 | #' \item Average : global average of all the (similar) "tomorrow of past" |
| 12 | #' \item Zero : just output 0 (benchmarking purpose) |
| 13 | #' \item Level : output a flat serie repeating the last observed level |
| 14 | #' } |
| 15 | #' @param pjump How to predict the jump at the interface between two days ? |
| 16 | #' \itemize{ |
| 17 | #' \item Persistence : use last (similar) day values |
| 18 | #' \item Neighbors: re-use the weights optimized in corresponding forecaster |
| 19 | #' \item Zero: just output 0 (no adjustment) |
| 20 | #' } |
| 21 | #' @param memory Data depth (in days) to be used for prediction |
| 22 | #' @param horizon Number of time steps to predict |
| 23 | #' @param ... Additional parameters for the forecasting models |
| 24 | #' |
| 25 | #' @return An object of class Forecast |
| 26 | #' |
| 27 | #' @examples |
| 28 | #' data = getData(ts_data="data/pm10_mesures_H_loc.csv", exo_data="data/meteo_extra_noNAs.csv", |
| 29 | #' input_tz = "Europe/Paris", working_tz="Europe/Paris", predict_at=7) |
| 30 | #' pred = getForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12) |
| 31 | #' \dontrun{#Sketch for real-time mode: |
| 32 | #' data = new("Data", ...) |
| 33 | #' forecaster = new(..., data=data) |
| 34 | #' repeat { |
| 35 | #' data$append(some_new_data) |
| 36 | #' pred = forecaster$predict(data$getSize(), ...) |
| 37 | #' #do_something_with_pred |
| 38 | #' }} |
| 39 | #' @export |
| 40 | getForecast = function(data, indices, forecaster, pjump=NULL, |
| 41 | memory=Inf, horizon=data$getStdHorizon(), ...) |
| 42 | { |
| 43 | # (basic) Arguments sanity checks |
| 44 | horizon = as.integer(horizon)[1] |
| 45 | if (horizon<=0 || horizon>length(data$getCenteredSerie(2))) |
| 46 | stop("Horizon too short or too long") |
| 47 | indices = sapply( seq_along(indices), function(i) dateIndexToInteger(indices[i], data) ) |
| 48 | if (any(indices<=0 | indices>data$getSize())) |
| 49 | stop("Indices out of range") |
| 50 | indices = sapply(indices, dateIndexToInteger, data) |
| 51 | if (!is.character(forecaster)) |
| 52 | stop("forecaster (name) should be of class character") #pjump could be NULL |
| 53 | |
| 54 | pred = list() |
| 55 | forecaster = new(paste(forecaster,"Forecaster",sep=""), data=data, |
| 56 | pjump = |
| 57 | if (is.null(pjump)) |
| 58 | function() {} |
| 59 | else |
| 60 | getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")) |
| 61 | for (today in indices) |
| 62 | { |
| 63 | pred[[length(pred)+1]] = list( |
| 64 | "serie" = forecaster$predict(today, memory, horizon, ...), |
| 65 | "params" = forecaster$getParameters(), |
| 66 | "index" = today |
| 67 | ) |
| 68 | } |
| 69 | new("Forecast",pred=pred) |
| 70 | } |