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#Copyright © 2016 RTE Réseau de transport d’électricité
#' Read Input thermal time series
#'
#' @description
#' \code{readInputThermal} is a function that reads thermal time series from an antares
#' project. But contrary to \code{\link{readAntares}}, it only reads time series
#' stored in the input folder, so it can work in "input" mode.
#'
#' @param clusters vector of clusters names for which thermal time series must be read.
#' @param thermalModulation if TRUE, return thermalModulation data
#' @param thermalData if TRUE, return thermalData from prepro
#' @inheritParams readAntares
#'
#' @return
#' If thermalModulation or thermalData is TRUE, an object of class "antaresDataList" is returned. It is a list of
#' data.tables for selected input
#'
#' Else the result is a data.table with class "antaresDataTable".
#'
#' @note
#' the clusters parameter can also accept the special value "all".
#' It indicates the function to read the desired time series for all clusters.
#'
#' @seealso
#' \code{\link{setSimulationPath}}, \code{\link{readAntares}},
#' \code{\link{getAreas}}, \code{\link{getLinks}}
#'
#' @export
readInputThermal <- function(clusters = NULL, thermalModulation = FALSE, thermalData = FALSE,
opts = simOptions(),
timeStep = c("hourly", "daily", "weekly", "monthly", "annual"),
simplify = TRUE, parallel = FALSE,
showProgress = TRUE) {
timeStep <- match.arg(timeStep)
# Can the importation be parallelized ?
if (parallel) {
if(!requireNamespace("foreach")) stop("Parallelized importation impossible. Please install the 'foreach' package and a parallel backend provider like 'doParallel'.")
if (!foreach::getDoParRegistered()) stop("Parallelized importation impossible. Please register a parallel backend, for instance with function 'registerDoParallel'")
}
allAreasClusters <- readClusterDesc(opts = opts)[area %in% opts$areasWithClusters, c("area", "cluster")]
allClusters <- unique(allAreasClusters$cluster)
# Manage special value "all"
if(identical(clusters, "all")) clusters <- allClusters
if (length(setdiff(tolower(clusters), tolower(allClusters))) > 0){
cat(c("the following clusters are not available : ",setdiff(tolower(clusters), tolower(allClusters))))
stop("Some clusters are not available in the areas specified")
}
ind_cluster <- which(tolower(allClusters) %in% tolower(clusters))
clusters <- unique(allClusters[ind_cluster])
res <- list() # Object the function will return
thermalTS <- as.data.table(ldply(clusters, function(cl) {
area <- unique(allAreasClusters[cluster == cl]$area)
if (length(area) > 1) warning(cl," is in more than one area")
resCl <- ldply(area, function(x){
filePattern <- sprintf("%s/%s/%%s/series.txt", "thermal/series", x)
mid <- .importInputTS(cl, timeStep, opts, filePattern, "ThermalAvailabilities",
inputTimeStep = "hourly", type = "matrix")
if (is.null(mid)) return (data.table())
mid$area <- x
mid$cluster <- cl
mid
})
resCl <- dcast(as.data.table(resCl), area + cluster + timeId ~ tsId, value.var = "ThermalAvailabilities")
}))
tsCols <- setdiff(colnames(thermalTS), c("area", "cluster", "timeId"))
setnames(thermalTS, tsCols, paste0("ts",tsCols))
setcolorder(thermalTS, c("area", "cluster", "timeId", setdiff(names(thermalTS), c("area", "cluster", "timeId"))))
if (nrow(thermalTS) > 0) res$thermalAvailabilities <- thermalTS
# thermalModulation processing
if (thermalModulation){
areas <- unique(allAreasClusters[cluster %in% clusters]$area)
thermalMod <- as.data.table(ldply(areas, .importThermalModulation, opts = opts, timeStep = timeStep))
thermalMod <- thermalMod[cluster %in% clusters]
setcolorder(thermalMod, c("area", "cluster", "timeId", setdiff(names(thermalMod), c("area", "cluster", "timeId"))))
if (nrow(thermalMod) > 0) res$thermalModulation <- thermalMod
}
# thermalData processing
if (thermalData){
areas <- unique(allAreasClusters[cluster %in% clusters]$area)
thermalDat <- as.data.table(ldply(areas, .importThermalData, opts = opts, timeStep = timeStep))
thermalDat <- thermalDat[cluster %in% clusters]
setcolorder(thermalDat, c("area", "cluster", "timeId", setdiff(names(thermalDat), c("area", "cluster", "timeId"))))
if (nrow(thermalDat) > 0) res$thermalData <- thermalDat
}
if (length(res) == 0) stop("At least one argument of readInputTS has to be defined.")
# Class and attributes
res <- .addClassAndAttributes(res, NULL, timeStep, opts, simplify)
addDateTimeColumns(res)
}
#' Read Input RES time series
#'
#' @description
#' \code{readInputRes} is a function that reads renewable time series from an antares
#' project. But contrary to \code{\link{readAntares}}, it only reads time series
#' stored in the input folder, so it can work in "input" mode.
#'
#' @param clusters vector of RES clusters names for which renewable time series must be read.
#' @inheritParams readAntares
#'
#' @return
#' data.table with class "antaresDataTable".
#'
#' @seealso
#' \code{\link{setSimulationPath}}, \code{\link{readAntares}},
#' \code{\link{getAreas}}, \code{\link{getLinks}}
#'
#' @export
readInputRES <- function(clusters = NULL, opts = simOptions(),
timeStep = c("hourly", "daily", "weekly", "monthly", "annual"),
simplify = TRUE, parallel = FALSE,
showProgress = TRUE) {
timeStep <- match.arg(timeStep)
# Can the importation be parallelized ?
if (parallel) {
if(!requireNamespace("foreach")) stop("Parallelized importation impossible. Please install the 'foreach' package and a parallel backend provider like 'doParallel'.")
if (!foreach::getDoParRegistered()) stop("Parallelized importation impossible. Please register a parallel backend, for instance with function 'registerDoParallel'")
}
allAreasClusters <- readClusterResDesc(opts = opts)[area %in% opts$areasWithResClusters, c("area", "cluster")]
allClusters <- unique(allAreasClusters$cluster)
# Manage special value "all"
if(identical(clusters, "all")) clusters <- allClusters
if (length(setdiff(tolower(clusters), tolower(allClusters))) > 0){
cat(c("the following clusters are not available : ",setdiff(tolower(clusters), tolower(allClusters))))
stop("Some clusters are not available in the areas specified")
}
ind_cluster <- which(tolower(allClusters) %in% tolower(clusters))
clusters <- unique(allClusters[ind_cluster])
res <- list() # Object the function will return
ResTS <- as.data.table(ldply(clusters, function(cl) {
area <- unique(allAreasClusters[cluster == cl]$area)
if (length(area) > 1) warning(cl," is in more than one area")
resCl <- ldply(area, function(x){
filePattern <- sprintf("%s/%s/%%s/series.txt", "renewables/series", x)
mid <- .importInputTS(cl, timeStep, opts, filePattern, "production",
inputTimeStep = "hourly", type = "matrix")
if (is.null(mid)) return (data.table())
mid$area <- x
mid$cluster <- cl
mid
})
resCl <- dcast(as.data.table(resCl), area + cluster + timeId ~ tsId, value.var = "production")
}))
tsCols <- setdiff(colnames(ResTS), c("area", "cluster", "timeId"))
setnames(ResTS, tsCols, paste0("ts",tsCols))
setcolorder(ResTS, c("area", "cluster", "timeId", setdiff(names(ResTS), c("area", "cluster", "timeId"))))
if (nrow(ResTS) > 0) res$ResProduction <- ResTS
if (length(res) == 0) stop("At least one argument of readInputRes has to be defined.")
# Class and attributes
res <- .addClassAndAttributes(res, NULL, timeStep, opts, simplify)
addDateTimeColumns(res)
}
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