R/calcLivestock_kcal_structure.R

In pik-piam/mrvalidation: madrat data preparation for validation purposes

#' @importFrom magclass setNames convergence


calcLivestock_kcal_structure <- function(reduce_ruminants = 0.5) { # nolint
  kap <- findset("kap")
  years <- findset("time")
  massbalance <- calcOutput("FAOmassbalance", aggregate = FALSE)
  out <- collapseNames(massbalance[, , "households"][, , "ge"][, , kap], collapsedim = c(2, 3))
  lastyear <- paste0("y", max(getYears(massbalance, as.integer = TRUE)))
  missingyears <- setdiff(years, getYears(massbalance))
  out <- add_columns(x = out, addnm = missingyears, dim = 2.1)
  out[, missingyears, ] <- setYears(out[, lastyear, ], NULL)
  aim <- out
  aim[, , "livst_chick"] <- out[, , "livst_chick"] + setNames(out[, , "livst_rum"], NULL) * (1 - reduce_ruminants)
  aim[, , "livst_rum"] <- setNames(out[, , "livst_rum"], NULL) * (reduce_ruminants)
  out <- convergence(origin = out, aim = aim, start_year = "y2010", end_year = "y2050", type = "s")
  weight <- out
  weight[, , ] <- setNames(dimSums(out, dim = 3), NULL)
  out <- out / dimSums(out, dim = 3)

  a <- unique(dimnames(which(is.na(out), arr.ind = TRUE))[[1]])
  vcat(verbosity = 2, paste0("no values for ", paste(a, collapse = " "), ". Set to zero."))
  out[is.nan(out)] <- 0
  return(list(x = out, weight = weight, unit = "Share",
              description = "Composition of livestock demand. Fixed after historical period to latest year."))
}