#' Read in GDX and import different parameters used in convGDX2MIF.R for intermediate calculations in
#' the reporting
#'
#'
#' @param gdx a GDX object as created by readGDX, or the path to a gdx
#' @return MAgPIE object - contains the capacity variables
#' @author Sebastian Osorio, Renato Rodrigues
#' @seealso \code{\link{convGDX2MIF}}
#' @examples
#'
#' \dontrun{importParameters(gdx)}
#'
#' @importFrom gdx readGDX
#' @importFrom magclass mbind setNames dimSums getSets getSets<- as.magpie
#'
importParameters <- function(gdx) {
# read parameters
p_taulength <- readGDX(gdx,name=c("p_taulength","pm_taulength"),field="l",format="first_found")
p_exdemand <- readGDX(gdx,name="p_exdemand",field="l",format="first_found")
c_demandscale <- readGDX(gdx,name="c_demandscale",field="l",format="first_found")
s_c2co2 <- readGDX(gdx,name="s_c2co2",field="l",format="first_found")
p_nuren <- readGDX(gdx,name="p_nuren",field="l",format="first_found")
p_datafuelcost <- readGDX(gdx,name="p_datafuelcost",field="l",format="first_found")
p_tedata <- readGDX(gdx,name="p_tedata",field="l",format="first_found")
p_incoall <- readGDX(gdx,name="p_incoall",field="l",format="first_found")
# create MagPie object of demand with iso3 regions
p_exdemand <- limesMapping(p_exdemand)
p_nuren <- limesMapping(p_nuren)
p_datafuelcost <- limesMapping(p_datafuelcost)
p_tedata <- limesMapping(p_tedata)
p_incoall <- limesMapping(p_incoall)
#Distinguish electricity demand ("seel")
p_eldemand <- p_exdemand[,,"seel"]
#
#p_nuren_best <- p_nuren[,,"1"]
# parReturn <- mbind(p_taulength,p_exdemand,c_demandscale,p_eldemand)
returnList <- list("p_taulength" = p_taulength ,
"c_demandscale" = c_demandscale,
"p_eldemand" = p_eldemand,
"s_c2co2" = s_c2co2,
"p_nuren" = p_nuren,
"p_datafuelcost" = p_datafuelcost,
"p_tedata" = p_tedata,
"p_incoall" = p_incoall)
return(returnList)
}
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