R/reportGrasslandSoilCarbon.R

In pik-piam/magpie4: MAgPIE outputs R package for MAgPIE version 4.x

#' @title reportGraslandSoilCarbon
#' @description reports cattle related numbers
#'
#' @export
#'
#' @param gdx GDX file
#' @return Cattle values as magpie objetc
#' @author Marcos Alves
#' @examples
#' \dontrun{
#' x <- reportGraslandSoilCarbon(gdx)
#' }
#' @importFrom madrat toolGetMapping getConfig toolCountryFill

reportGraslandSoilCarbon <- function(gdx) {

# dir <- dirname(gdx)
# 
# map <- toolGetMapping(type = "regional", name = "clustermapping.csv")
# 
# grass_areas <- NULL
# sc_range <- NULL
# sc_pastr <- NULL
# sc_grassland <- NULL
# sc_net <- NULL
# x <- NULL
# 
# try(
#   {
#     grass_areas <- collapseNames(readGDX(gdx, "ov31_grass_area")[, , "rainfed.level"])
#   },
#   silent = T)
# try(
#   {
#     sc_range <- read.magpie(file.path(dir, "soil_range_future.mz"))
#     sc_pastr <- read.magpie(file.path(dir, "soil_pastr_future.mz"))
#     sc_grassland <- read.magpie(file.path(dir, "grassland_soil_carbon.mz"))
#     sc_net <- read.magpie(file.path(dir, "net_management_change_range.mz"))
#     sc_net0 <- read.magpie(file.path(dir, "net_management_change_range0.mz"))
#   },
#   silent = T)
# 
# if (!is.null(grass_areas)) {
#   if (!is.null(sc_range)) {
#     grass_areas <- gdxAggregate(gdx, grass_areas, to = "regglo", absolute = T)
#     
#     sc_range_reg <- toolAggregate(sc_range, map, from = "cell", to = "region")
#     sc_range_reg <- mbind(sc_range_reg, setCells(dimSums(sc_range_reg, dim = 1), "GLO"))
#     sc_range_reg <- setNames(sc_range_reg, "range")
#     
#     sc_pastr_reg <- toolAggregate(sc_pastr, map, from = "cell", to = "region")
#     sc_pastr_reg <- mbind(sc_pastr_reg, setCells(dimSums(sc_pastr_reg, dim = 1), "GLO"))
#     
#     sc_total <- setNames(mbind(sc_pastr_reg, sc_range_reg), c("pastr", "range"))
#     
#     sc_total_avg <- sc_total / grass_areas[, getYears(sc_total), c("pastr", "range")]
#     sc_total_avg[is.infinite(sc_total_avg) | is.nan(sc_total_avg)] <- 0
#     sc_total_avg_t <- dimSums(sc_total, dim = 3) / dimSums(grass_areas[, getYears(sc_total), c("pastr", "range")], dim = 3)
#     sc_total_avg_t[is.infinite(sc_total_avg_t) | is.nan(sc_total_avg_t)] <- 0
#     
#     sc_net_reg <- toolAggregate(sc_net, map, from = "cell", to = "region")
#     sc_net_reg <- mbind(sc_net_reg, setCells(dimSums(sc_net_reg, dim = 1), "GLO"))
#     
#     sc_net0_reg <- toolAggregate(sc_net0, map, from = "cell", to = "region")
#     sc_net0_reg <- mbind(sc_net0_reg, setCells(dimSums(sc_net0_reg, dim = 1), "GLO"))
#     
#     x <- NULL
#     x <- mbind(x, setNames(sc_total_avg, paste0("Resources|Soil Carbon|Grassland|+|", reportingnames(getNames(sc_total_avg, dim = 1)), "|Density (tC per ha)")))
#     x <- mbind(x, setNames(dimSums(sc_total_avg_t, dim = 3), paste0("Resources|Soil Carbon|Grassland|Density (tC per ha)")))
#     x <- mbind(x, setNames(sc_total, paste0("Resources|Soil Carbon|Grassland|+|", reportingnames(getNames(sc_total, dim = 1)), "|Total (MtC)")))
#     x <- mbind(x, setNames(dimSums(sc_total, dim = 3), paste0("Resources|Soil Carbon|Grassland|Total (MtC)")))
#     x <- mbind(x, setNames(dimSums(sc_net_reg, dim = 3), paste0("Resources|Soil Carbon Change|Rangelands|Management related (MtC)")))
#     x <- mbind(x, setNames(dimSums(sc_net0_reg, dim = 3), paste0("Resources|Soil Carbon Change|Rangelands|Management related 0 Baseline (MtC)")))
#    } else {
#      x <- "Disabled (dissagregation must be run first)"
#    }
#  } else {
#    x <- "Disabled (no managed pastures) "
#  }
  gdx <- NULL
  x <- "Disabled (under development)"
}