R/calcFoodSupplyPast.R

In pik-piam/mrcommons: MadRat commons Input Data Library

#' @title calcFoodSupplyPast
#' @description Calculates the food supply (as defined by FAO, including intake and household waste) for the past.
#'
#' @param per_capita if true, calculates per capita demand per day, otherwhise total demand per year
#' @param products a set with the products that shall be provided, e.g. kall. If NULL, the products are provided
#' that are in the primary data
#' @param product_aggr if TRUE, all products are summed up, if "maingroups" products
#' are summed over livestock products, staples and vegfruits.
#' @param populationweight datasource of populationweight: FAO can be selected in order
#' to better meet exact values. Normal datasource is PopulationPast
#' @param attributes attributes of different products,i.e., kcal,protein,wm
#' @return List of magpie objects with results on country level, weight on country level, unit and description.
#' @author Benjamin Leon Bodirsky, Xiaoxi Wang
#' @seealso
#' [calcFAOharmonized()]
#' @examples
#' \dontrun{
#' calcOutput("FoodSupplyPast")
#' }
#'
#' @importFrom magclass getSets

calcFoodSupplyPast <- function(
    per_capita = TRUE, # nolint: object_name_linter.
    products = NULL,
    product_aggr = FALSE, # nolint: object_name_linter.
    populationweight = "PopulationPast",
    attributes = c("kcal", "protein", "wm")) {
  kfo <- findset("kfo")
  kcal <- calcOutput("FAOmassbalance", aggregate = FALSE)
  kcal <- kcal[, , "households"][, , kfo][, , c("ge", "nr", "wm")]
  kcal <- collapseNames(kcal)

  # translate back to calories and proteins
  kcal[, , "ge"] <- kcal[, , "ge"] / 4.184
  kcal[, , "nr"] <- kcal[, , "nr"] * 6.25
  # make sure order is correct
  kcal <- kcal[, , c("ge", "nr", "wm")]
  getNames(kcal, dim = 2) <- c("kcal", "protein", "wm")

  if (!is.null(products)) {
    products <- findset(products)
    kall <- findset("kall")
    missing <- kall[which(!kall %in% getNames(kcal, dim = 1))]
    if (length(missing > 0)) {
      vcat(verbosity = 2, paste0("The following products were not included in FAO Food supply ",
                                 "and were added with value 0:", paste(missing, collapse = " ")))
      kcal <- add_columns(kcal, addnm = missing, dim = 3.1)
      kcal[, , missing] <- 0
    }
    kcal <- kcal[, , products]
  }
  if (product_aggr) {
    kcal <- dimSums(kcal, dim = 3.1)
  } else if (product_aggr == "maingroups") {
    kap <- findset("kap")
    kst <- findset("kst")
    staples <- add_dimension(dimSums(kcal[, , kst], dim = 3.1), dim = 3.1, add = "products", nm = "kst")
    animals <- add_dimension(dimSums(kcal[, , kap], dim = 3.1), dim = 3.1, add = "products", nm = "kap")
    vegfruit <- add_dimension(dimSums(kcal[, , "others"], dim = 3.1), dim = 3.1, add = "products", nm = "vegfruit")
    kcal <- mbind(staples, animals, vegfruit)
  } else if (product_aggr != FALSE) {
    stop("unknown product_aggr")
  }

  if (per_capita) {
    if (populationweight == "PopulationPast") {
      weight <- collapseNames(calcOutput("PopulationPast", aggregate = FALSE))
    } else if (populationweight == "FAO") {
      faoOnline <- readSource(type = "FAO_online", subtype = "Pop", convert = TRUE)
      weight <- collapseNames(faoOnline[, getYears(kcal), "Total_Population_Both_sexes_(persons)"]) / 1000000
    }
    weight <- weight[, getYears(kcal), ]
    out <- kcal / weight / 365 * 1000000

    if (any(is.nan(out))) {
      out[is.nan(out)] <- 0
    }
    if (any(out == Inf)) {
      out[out == Inf] <- 0
    }

    unit <- "kcal per capita per day, g protein or fat per capita per day, kg food wet matter per capita per day"
    min <- 0
    max <- 5000
  } else if (per_capita == FALSE) {
    out <- kcal
    out[, , c("wm")] <- out[, , c("wm")] / 1000
    out[, , c("kcal")] <- out[, , c("kcal")]
    out[, , c("protein")] <- out[, , c("protein")] / 10^6

    weight <- NULL
    unit <- "Mio Kcal, Mt protein, Mt WM per year"
    min <- 0
    max <- 2e+10
  } else {
    stop("per_capita has to be binary")
  }

  out <- collapseNames(out[, , attributes])

  return(list(x = out,
              weight = weight,
              unit = unit,
              description = "FAO food supply (including household waste)",
              min = min,
              max = max))
}