R/calcCoolingSharesAll.R

In pik-piam/moinput: Model Operations Input Data Library

#' Calculate Cooling Type Shares
#' 
#' This function merges the output of two other functions that calculate REMIND
#' input data for the shares of cooling types per electricity technology and
#' REMIND region, using as initial information the Davies (2013) data per
#' electricity technology and GCAM region. The two other functions separately
#' calculate data for the base year and for future time steps. The source data
#' provide most required information but some assumptions on missing data are
#' also made.
#' 
#' 
#' @return MAgPIE object on cooling type shares per elecricity technology and
#' REMIND region
#' @author Ioanna Mouratiadou
#' @seealso \code{\link{calcOutput}}, \code{\link{readDaviesCooling}},
#' \code{\link{convertDaviesCooling}},
#' \code{\link{calcCoolingSharesBase}},\code{\link{calcCoolingSharesFuture}}
#' @examples
#' 
#' \dontrun{ 
#' 
#' a <- calcOutput("CoolingSharesAll")
#' 
#' }
#' 
calcCoolingSharesAll <- function() {

  cooloutputBase   <- calcOutput("CoolingSharesBase", aggregate=FALSE)
  cooloutputFuture <- calcOutput("CoolingSharesFuture",aggregate=FALSE)
  
  # merge two datasets
  outputAll <- mbind(cooloutputBase,cooloutputFuture)
  
  #assign aggregation weight
  weight     <- dimSums(calcOutput("IO",subtype="output",aggregate=FALSE)[,2010,c("feelb","feeli")],dim=3) 
  
  #set weights to zero for countries that were not contained in the GCAM2ISO mapping
  weight["ALA",,] <- 0
  weight["ATA",,] <- 0
  weight["BES",,] <- 0
  weight["BLM",,] <- 0
  weight["CUW",,] <- 0
  weight["GGY",,] <- 0
  weight["IMN",,] <- 0
  weight["JEY",,] <- 0
  weight["MAF",,] <- 0
  weight["PSE",,] <- 0
  weight["SSD",,] <- 0
  weight["SXM",,] <- 0

  return(list(x=outputAll, weight=weight,
              unit="% of cooling type technologies", 
              description="Cooling shares for different cooling technologies based on Davies et al. (2013) publication and using electricity use weights (aggregated based on IEA World Energy Balances, 2014) for regional mapping"              
  ))
}