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[talweg.git] / pkg / R / getForecast.R
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1#' @title get Forecast
2#'
3#' @description Predict time-series curves for the selected days indices (lines in data).
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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)
e030a6e3 7#' @param forecaster Name of the main forcaster
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8#' \itemize{
9#' \item Persistence : use values of last (similar, next) day
e030a6e3 10#' \item Neighbors : use values from the k closest neighbors' tomorrows
3d69ff21 11#' \item Average : global average of all the (similar) "tomorrow of past"
e030a6e3 12#' \item Zero : just output 0 (benchmarking purpose)
3d69ff21 13#' }
e030a6e3 14#' @param pjump How to predict the jump at the interface between two days ?
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15#' \itemize{
16#' \item Persistence : use last (similar) day values
e030a6e3 17#' \item Neighbors: re-use the weights optimized in corresponding forecaster
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18#' \item Zero: just output 0 (no adjustment)
19#' }
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20#' @param memory Data depth (in days) to be used for prediction
21#' @param horizon Number of time steps to predict
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22#' @param ... Additional parameters for the forecasting models
23#'
24#' @return An object of class Forecast
25#'
26#' @examples
613a986f 27#' data = getData(ts_data="pm10_mesures_H_loc.csv", exo_data="meteo_extra_noNAs.csv",
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28#' input_tz = "Europe/Paris", working_tz="Europe/Paris", predict_at=7)
29#' pred = getForecast(data, 2200:2230, "Persistence", "Persistence", 500, 12)
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30#' \dontrun{#Sketch for real-time mode:
31#' data = new("Data", ...)
e030a6e3 32#' forecaster = new(..., data=data)
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33#' repeat {
34#' data$append(some_new_data)
e030a6e3 35#' pred = forecaster$predict(data$getSize(), ...)
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36#' #do_something_with_pred
37#' }}
38#' @export
e5aa669a 39getForecast = function(data, indices, forecaster, pjump=NULL,
e030a6e3 40 memory=Inf, horizon=data$getStdHorizon(), ...)
3d69ff21 41{
e030a6e3 42 # (basic) Arguments sanity checks
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43 horizon = as.integer(horizon)[1]
44 if (horizon<=0 || horizon>length(data$getCenteredSerie(2)))
45 stop("Horizon too short or too long")
09cf9c19 46 indices = sapply( seq_along(indices), function(i) dateIndexToInteger(indices[i], data) )
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47 if (any(indices<=0 | indices>data$getSize()))
48 stop("Indices out of range")
49 indices = sapply(indices, dateIndexToInteger, data)
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50 if (!is.character(forecaster))
51 stop("forecaster (name) should be of class character") #pjump could be NULL
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52
53 pred = list()
e030a6e3 54 forecaster = new(paste(forecaster,"Forecaster",sep=""), data=data,
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55 pjump =
56 if (is.null(pjump))
57 function() {}
58 else
59 getFromNamespace(paste("get",pjump,"JumpPredict",sep=""), "talweg"))
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60 for (today in indices)
61 {
1e20780e 62 #pred$append(...) is slow; TODO: use R6 class
3d69ff21 63 pred[[length(pred)+1]] = list(
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64 "serie" = forecaster$predict(today, memory, horizon, ...),
65 "params" = forecaster$getParameters(),
66 "index" = today
67 )
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68 }
69 new("Forecast",pred=pred)
70}