R/getData_raw.R

In pik-piam/validation: MAgPIE validation library

getData_raw<-function(collections,level="glo",historical=NULL,datasources=NULL, query=NULL){
  ###############################################################
  #Check if data for the specified collection sis available
  ###############################################################
  tmp<-collections
  for(i in 1:length(collections)){
    if(!collections[i] %in% names(valdata$data)){
      tmp[i]<-NA
    }                                                        
  }
  tmp<-tmp[which(!is.na(tmp))]
  if(length(tmp)==0) stop("No data for any of the collections ",paste(collections)," found.")
  collections<-tmp
  ###############################################################
  #Determine what data_levels can be used for the level specified in the add_data call
  ###############################################################
  levels<-c("cell","country","reg","glo")
  data_levels<-levels[1:grep(level,levels)]
  if(length(data_levels)==0) stop("No appropriate data for level=",level,"found.")
  #Rename func_level for groupAggregate
  if(level=="country") level<-"iso"
  
  ###############################################################
  #Check if historical data, projections or both are requested
  ###############################################################
  if(is.null(historical)){
    types<-c("historical","projection")
  } else if(historical==TRUE){
    types<-"historical"
  } else if(historical==FALSE){
    types<-"projection"
  } else {
    stop("'historical argument must be either TRUE, FALSE or NULL.")
  }

  #Create an output object
  out<-list()
  
  ###############################################################
  #Get the requested data, aggregate it to the desired level and save it in the out list
  ###############################################################
  for(collection in collections){
    out[[collection]]<-list()
    out[[collection]][["unit"]]<-valdata$data[[collection]][["unit"]]
    out[[collection]][["data"]]<-list()
    for(data_level in data_levels){
      if(!is.null(valdata$data[[collection]][["data"]][[data_level]][["data"]])){
        for(type in types){
          if(!is.null(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]])){
            if(is.null(out[[collection]][["data"]][[type]])) out[[collection]][["data"]][[type]]<-list()
            if(is.null(datasources)) {
              sources<-names(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]])
            } else {
              sources<-datasources
            }
            for(sourc in sources){
              if(!is.null(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]])){
                message(sourc," DATA for ",collection," found")
                comment<-attr(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]][["data"]],"comment")
                if(data_level=="cell" & !is.null(query)){
                  #convert query (if provided) from country2reg to cell2reg
                  cell <- valdata$other$iso_cell
                  a <- merge(query,cell,by.x="iso",by.y="country")
                  a <- a[order(a$magpiecell),]
                  a$iso <- paste(a$iso,a$magpiecell,sep=".")
                  a$magpiecell <- NULL
                  query_final <- a
                  getCells(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]][["data"]]) <- query_final$iso
                } else {
                  query_final <- query
                }
                #Define all the arguments for groupAggregate in a list
                args<-list(data=clean_magpie(valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]][["data"]]),
                           vectorfunction=valdata$aggr_types[[valdata$data[[collection]][["aggr_type"]]]][["func"]],
                           dim=1,
                           from=NULL,
                           to=level,
                           query=query_final)
                for(i in valdata$aggr_types[[valdata$data[[collection]][["aggr_type"]]]][["add_args"]]){
                  args[[i]]<-valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]][[i]]
                  if(is.magpie(args[[i]])) args[[i]] <- clean_magpie(args[[i]])
                }
                if(level!="cell") {
                  tmp<-do.call(groupAggregate,args)
                } else {
                  tmp<-valdata$data[[collection]][["data"]][[data_level]][["data"]][[type]][[sourc]][["data"]]
                }
                tmp<-tmp[which(!getCells(tmp)%in%c("XXX.11","XXX")),,]
                if(!is.null(out[[collection]][[type]][[sourc]])){
                  warning("More than one dataset is present for the combination: ",type," ",sourc,". Only last one will be returned.")
                }
                attr(tmp,"comment")<-comment
                out[[collection]][["data"]][[type]][[sourc]]<-as.magpie(tmp)
              }
            }
          }
        }
      }
    }
    if(is.null(out[[collection]][["data"]])) out[[collection]]<-NULL
  }
  
  if(length(out)==0) {
    out<-NULL
    warning("No Data found. NULL returned")
  }
    
  return(out)
}