R/readDaviesCooling.R

In pik-piam/mrremind: MadRat REMIND Input Data Package

#' Read Davies Cooling
#' 
#' Read in Davies (2013) data on shares of cooling types per electricity
#' technology and GCAM region
#' 
#' 
#' @param subtype Type of Davies data that should be read. Available types are:
#' \itemize{ \item \code{dataBase}: The Davies source data for the base year
#' \item \code{dataFuture}: The Daves source data for the future }
#' @return MAgPIE object of the Davies (2013) data
#' @author Lavinia Baumstark, Ioanna Mouratiadou
#' @seealso \code{\link{readSource}}
#' @examples
#' 
#' \dontrun{ a <- readSource(type="DaviesCooling")
#' }
#' 
readDaviesCooling <- function(subtype) {
      
  sheets <- c(dataBase=1, dataFuture=2)
  sheet <- toolSubtypeSelect(subtype,sheets)
  
  cool <- as.data.frame(read_excel("DaviesCooling.xlsx", sheet = sheet))
  cool <- cool[!is.na(cool$`Davies Source`),]
      
  row.names(cool) <- paste(cool$'Davies Source',cool$'Davies Cooling',sep=".")
  cool$'Davies Source'  <- NULL
  cool$'Davies Cooling' <- NULL
      
  regions <- c("USA"="USA","Canada"="CAN", "Western Europe"="WEU", "Japan"="JPN", "Australia & NZ"="ANZ", "Former Soviet Union"="FSU", "China"="CHN", "Middle East"="MEA", "Africa"="AFR", "Latin America"="LAM", "Southeast Asia"="SEA", "Eastern Europe"="EEU" , "Korea"="KOR" , "India"="IND")
  names(cool) <- regions #three-letter code"
      
  cool <- as.magpie(cool)
  getYears(cool) <- NULL
      
  return(cool)
}