X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2FR%2FgetForecast.R;fp=pkg%2FR%2FgetForecast.R;h=0000000000000000000000000000000000000000;hb=99f83c9af27492f6fb9b10f51fb8704ed588f5c1;hp=8efcff8da70a7c8b13f40958dc8cced50fada203;hpb=defcae035f2e26fd8568cedb27040b173811b246;p=talweg.git diff --git a/pkg/R/getForecast.R b/pkg/R/getForecast.R deleted file mode 100644 index 8efcff8..0000000 --- a/pkg/R/getForecast.R +++ /dev/null @@ -1,72 +0,0 @@ -#' @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 -#' 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) -#' 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) -}