R/h5_utils.R

In antaresViz: Antares Visualizations

# .convertH5Filtering <- function(h5requestFiltering, x)
# {
#   if (length(h5requestFiltering) > 0)
#   {
#     if (!is.list(h5requestFiltering[[1]])){
#       if (!any(c("simOptions", "antaresDataTable") %in% class(x)))
#       {
#         h5requestFiltering <- rep(list(h5requestFiltering), length(x))
#       }else{
#         h5requestFiltering <- list(h5requestFiltering)
#       }
#     }else{
#       if (inherits(x, "list")){
#         if (length(h5requestFiltering) != length(x)){
#           h5requestFiltering <- h5requestFiltering[1:length(x) %% length(h5requestFiltering) + 1]
#         }
#       }
#     }
#   }else{
#     if (!any(c("simOptions", "antaresDataTable") %in% class(x)))
#     {
#       h5requestFiltering <- replicate(length(x), list())
#     }else{
#       h5requestFiltering <- replicate(1, list())
#     }
#   }
#   h5requestFiltering
# }



# .getTableInH5 <- function(fid, timeStep){
#   dataExist <- NULL
#   if (rhdf5::H5Lexists(fid, paste0(timeStep, "/areas")))
#   {
#     dataExist <- c(dataExist, "areas")
#   }
#   if (rhdf5::H5Lexists(fid, paste0(timeStep, "/links")))
#   {
#     dataExist <- c(dataExist, "links")
#   }
#   if (rhdf5::H5Lexists(fid, paste0(timeStep, "/clusters")))
#   {
#     dataExist <- c(dataExist, "clusters")
#   }
#   if (rhdf5::H5Lexists(fid, paste0(timeStep, "/districts")))
#   {
#     dataExist <- c(dataExist, "districts")
#   }
#   dataExist
# }

# .getVariablesH5 <- function(fid, timeStep, tables){
#   sapply(tables, function(X){
#     struct <- .getstructure(fid, paste0(timeStep, "/", X, "/mcInd/", "/structure"))$variable
#     if ("timeId" %in% struct){
#       struct <- struct[struct != "timeId"]
#     }
#     struct
#   }, simplify = FALSE)
# }

# .getClustersNames <- function(fid, timeStep){
#   unique(unlist(lapply(strsplit(.getstructure(fid, paste0(timeStep, "/clusters/mcInd/structure"))$cluster, "/"), function(X)X[1])))
# }

# .getElements <- function(opts, tables, fid, timeStep){
#   elements <- list()
#   if ("areas" %in% tables) elements$areas <- opts$areaList
#   if ("links" %in% tables) elements$links <- opts$linkList
#   if ("districts" %in% tables) elements$districts <- opts$districtList
#   if ("clusters" %in% tables){
#     elements$clusters  <- .getClustersNames(fid, timeStep)
#   }
#   elements
# }
# 
# .getDateRange <- function(opts, timeStep){
#   tim <- .timeIdToDate(sort(
#     unique(
#       antaresRead::.h5ReadAntares(opts$h5path, timeStep = timeStep, select = "timeId", 
#                                  areas = opts$areaList[1], mcYears = opts$mcYears[1], perf = FALSE)$timeId)
#   ), timeStep = timeStep, opts = opts)
#   dt <- as.Date(range(tim))
#   dt
# }
# 
# 
# .getGraphFunction <- function(type){
#   switch(type,
#          "ts" = .plotTS,
#          "barplot" = .barplot,
#          "monotone" = .plotMonotone,
#          "density" = .density,
#          "cdf" = .cdf,
#          "heatmap" = .heatmap,
#          stop("Invalid type")
#   )
# }

# .getTimeStep <- function(fid){
#   timeSteps <- sapply(c("hourly", "daily", "weekly", "monthly", "annual"), function(X){
#     rhdf5::H5Lexists(fid, X)
#   })
#   names(timeSteps[which(timeSteps == TRUE)])
# }

.compareOperation <- function(a, opType){
  if (length(a) == 1) return(unlist(unique(a)))
  if (opType == "union") return(Reduce(union, a))
  if (opType == "intersect") return(Reduce(intersect, a))
}