Commit | Line | Data |
---|---|---|
af3b84f4 | 1 | #' Compute forecast |
3d69ff21 | 2 | #' |
af3b84f4 | 3 | #' Predict time-series curves for the selected days indices (lines in data). |
3d69ff21 | 4 | #' |
e169b5d5 | 5 | #' @param data Object of type \code{Data}, output of \code{getData()}. |
2057c793 | 6 | #' @param indices Indices where to forecast (the day after); integers relative to the |
e169b5d5 BA |
7 | #' beginning of data, or (convertible to) Date objects. |
8 | #' @param forecaster Name of the main forecaster; more details: ?F_<forecastername> | |
3d69ff21 | 9 | #' \itemize{ |
e169b5d5 BA |
10 | #' \item Persistence : use last (similar, next) day |
11 | #' \item Neighbors : weighted tomorrows of similar days | |
12 | #' \item Average : average tomorrow of all same day-in-week | |
e030a6e3 | 13 | #' \item Zero : just output 0 (benchmarking purpose) |
3d69ff21 | 14 | #' } |
e169b5d5 BA |
15 | #' @param pjump Function to predict the jump at the interface between two days; |
16 | #' more details: ?J_<functionname> | |
3d69ff21 | 17 | #' \itemize{ |
e169b5d5 BA |
18 | #' \item Persistence : use last (similar, next) day |
19 | #' \item Neighbors: re-use the weights from F_Neighbors | |
3d69ff21 BA |
20 | #' \item Zero: just output 0 (no adjustment) |
21 | #' } | |
e169b5d5 BA |
22 | #' @param memory Data depth (in days) to be used for prediction. |
23 | #' @param horizon Number of time steps to predict. | |
24 | #' @param ncores Number of cores for parallel execution (1 to disable). | |
25 | #' @param ... Additional parameters for the forecasting models. | |
3d69ff21 | 26 | #' |
a66a84b5 | 27 | #' @return An object of class Forecast |
3d69ff21 BA |
28 | #' |
29 | #' @examples | |
e169b5d5 BA |
30 | #' ts_data <- system.file("extdata","pm10_mesures_H_loc.csv",package="talweg") |
31 | #' exo_data <- system.file("extdata","meteo_extra_noNAs.csv",package="talweg") | |
32 | #' data <- getData(ts_data, exo_data, input_tz="GMT", working_tz="GMT", predict_at=7) | |
33 | #' pred <- computeForecast(data, 2200:2230, "Persistence", "Zero", | |
34 | #' memory=500, horizon=12, ncores=1) | |
3d69ff21 | 35 | #' \dontrun{#Sketch for real-time mode: |
e169b5d5 BA |
36 | #' data <- Data$new() |
37 | #' # Initialize: first day has no predictions attached | |
38 | #' data$initialize() | |
39 | #' forecaster <- MyForecaster$new(myJumpPredictFunc) | |
3d69ff21 | 40 | #' repeat { |
e169b5d5 BA |
41 | #' # During the night between days j and j+1: |
42 | #' data$appendExoHat(exogenous_predictions) | |
43 | #' # In the morning 7am+ or afternoon 1pm+: | |
44 | #' data$setMeasures( | |
45 | #' data$getSize()-1, | |
46 | #' times_from_H+1_yersteday_to_Hnow, | |
47 | #' PM10_values_of_last_24h, | |
48 | #' exogenous_measures_for_yersteday) | |
49 | #' pred <- forecaster$predictSerie(data, data$getSize()-1, ...) | |
3d69ff21 BA |
50 | #' #do_something_with_pred |
51 | #' }} | |
52 | #' @export | |
25b75559 | 53 | computeForecast = function(data, indices, forecaster, pjump, |
ee8b1b4e | 54 | memory=Inf, horizon=data$getStdHorizon(), ncores=3, ...) |
3d69ff21 | 55 | { |
e030a6e3 | 56 | # (basic) Arguments sanity checks |
3d69ff21 | 57 | horizon = as.integer(horizon)[1] |
72b9c501 | 58 | if (horizon<=0 || horizon>length(data$getCenteredSerie(1))) |
3d69ff21 | 59 | stop("Horizon too short or too long") |
98e958ca | 60 | integer_indices = sapply(indices, function(i) dateIndexToInteger(i,data)) |
a66a84b5 | 61 | if (any(integer_indices<=0 | integer_indices>data$getSize())) |
3d69ff21 | 62 | stop("Indices out of range") |
a66a84b5 BA |
63 | if (!is.character(forecaster) || !is.character(pjump)) |
64 | stop("forecaster (name) and pjump (function) should be of class character") | |
3d69ff21 | 65 | |
98e958ca | 66 | pred = Forecast$new( sapply(indices, function(i) integerIndexToDate(i,data)) ) |
72b9c501 BA |
67 | forecaster_class_name = getFromNamespace( |
68 | paste(forecaster,"Forecaster",sep=""), "talweg") | |
98e958ca BA |
69 | forecaster = forecaster_class_name$new( #.pjump = |
70 | getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg")) | |
5e838b3e | 71 | |
ee8b1b4e | 72 | if (ncores > 1 && requireNamespace("parallel",quietly=TRUE)) |
a866acb3 | 73 | { |
ee8b1b4e | 74 | p <- parallel::mclapply(seq_along(integer_indices), function(i) { |
a866acb3 | 75 | list( |
72b9c501 BA |
76 | "forecast" = forecaster$predictSerie( |
77 | data, integer_indices[i], memory, horizon, ...), | |
a866acb3 BA |
78 | "params"= forecaster$getParameters(), |
79 | "index" = integer_indices[i] ) | |
ee8b1b4e | 80 | }, mc.cores=ncores) |
a866acb3 BA |
81 | } |
82 | else | |
83 | { | |
ee8b1b4e | 84 | p <- lapply(seq_along(integer_indices), function(i) { |
a866acb3 | 85 | list( |
72b9c501 BA |
86 | "forecast" = forecaster$predictSerie( |
87 | data, integer_indices[i], memory, horizon, ...), | |
a866acb3 BA |
88 | "params"= forecaster$getParameters(), |
89 | "index" = integer_indices[i] ) | |
90 | }) | |
91 | } | |
5e838b3e | 92 | |
ee8b1b4e BA |
93 | # TODO: find a way to fill pred in //... |
94 | for (i in seq_along(integer_indices)) | |
95 | { | |
96 | pred$append( | |
72b9c501 BA |
97 | forecast = p[[i]]$forecast, |
98 | params = p[[i]]$params, | |
99 | index_in_data = p[[i]]$index | |
ee8b1b4e BA |
100 | ) |
101 | } | |
25b75559 | 102 | pred |
3d69ff21 | 103 | } |