# extraction total production of animals ----------------------------------

fadn.tp.animals <- function(fadn.countries ) {

  fadn.raw.rds.avail <- get.available.fadn.raw.rds()[COUNTRY %in% fadn.countries] 

  if(nrow(fadn.raw.rds.avail)==0){
    cat("Raw data does not exist, converting raw data ...\n")
    convert.raw(countries = fadn.countries)}

  # fadn countries
  # if (fadn.countries == "all") {
    fadn.countries.sel = c(
      "NED",
      "BEL",
      "BGR",
      "CYP",
      "CZE",
      "DAN",
      "DEU",
      "ELL",
      "ESP",
      "EST",
      "FRA",
      "HUN",
      "IRE",
      "ITA",
      "LTU",
      "LUX",
      "LVA",
      "MLT",
      "OST",
      "POL",
      "POR",
      "ROU",
      "SUO",
      "SVE",
      "SVK",
      "SVN",
      "UKI",
      "HRV"
    )

  # fadn years
  fadn.years.sel = c(2004:2018)
  # fadn info
  fadn.info.sel = c(
    "ID",
    "YEAR",
    "COUNTRY",
    "REGION",
    "NUTS0",
    "NUTS1",
    "NUTS2",
    "NUTS3",
    "SYS02",
    "TF14",
    "TF8",
    "SIZ6",
    "ORGANIC"
  )
  # extraction variables for animal product

  fadn.tp.sel <-
    c(
      "LBOV_CV",
      "LBOV_FUV",
      "LBOV_NO",
      "LBOV_OV",
      "LBOV_PV",
      "LBOV_SV",
      "PMLKGOAT_PRQ",
      "PMLKSHEP_PRQ",
      "PMLKBUF_TO",
      "PMLKCOW_TO",
      "PMLKCOWBUF_PRQ_X",
      "PMLKBUF_PRQ",
      "PMLKCOW_PRQ",
      "PEGGHENS_PRQ_X",
      "PEGGC_PRQ",
      "PEGGH_PRQ",
      "PEGGH_TO",
      "PEGGC_TO"
    )


  # fadn.str.data <- load.fadn.str.rds("alex",,"all")

  # after2014 <- readRDS(paste0(rds.dir, "/alex/fadn.str.after2014.all.rds"))
  # before2013 <- readRDS(paste0(rds.dir, "/alex/fadn.str.before2013.all.rds"))
  # fadn.str.crops <- bind_rows(before2013$crops,after2014$crops)

  # load
  cols.to.load.anim_prod = c(fadn.info.sel, fadn.tp.sel)

  # load raw fadn data using fadnutils package

  cat ("loading animal product variables from raw data\n")

  tmp.LOAD.raw = fadnUtils::load.fadn.raw.rds(years = fadn.years.sel,

                                              countries = fadn.countries,

                                              col.filter = cols.to.load.anim_prod)

  #
  tmp.LOAD.raw <- tmp.LOAD.raw %>% select(-c(load.COUNTRY, load.YEAR))




  tmp.LOAD <- tmp.LOAD.raw %>% mutate(
    COMI_GROF = ifelse (
      YEAR %in% c(2004:2013),
      PMLKCOWBUF_PRQ_X,
      (PMLKBUF_PRQ + PMLKCOW_PRQ)
    ),
    COMI_EAAP = PMLKBUF_TO + PMLKCOW_TO,
    EGGS_GROF = ifelse (
      YEAR %in% c(2004:2013),
      PEGGHENS_PRQ_X,
      as.numeric (PEGGC_PRQ  + PEGGH_PRQ)
    ) ,
    EGGS_EAAP = PEGGH_TO + PEGGC_TO,
    SGMI_GROF = PMLKGOAT_PRQ + PMLKSHEP_PRQ,
    PCAT_EAAP = LBOV_CV + LBOV_FUV - LBOV_OV + LBOV_NO + LBOV_PV,
    PCAT_EALP = LBOV_NO
  )

  tmp.LOAD.raw.long = melt(tmp.LOAD %>% select(-fadn.tp.sel),
                           id.vars = fadn.info.sel)

  tmp.LOAD.raw.long[grep("_", variable),
                    ":="(
                      PRODUCT = gsub("^(.+?)_(.+?)(_.*)?$", "\\1", variable),
                      VAR = gsub("^(.+?)_(.+?)(_.*)?$", "\\2", variable)
                    )]

  # rename and set the type of objects
  ANIMALS.production.all <- tmp.LOAD.raw.long %>%
    select(-c("NUTS0")) %>%
    mutate_if(is.character, as.factor) %>%
    mutate_at(c("COUNTRY", "REGION", "NUTS3", "NUTS2"), as.character) %>%
    mutate(ORGANIC =
             paste0('org-', ORGANIC)) %>%
    select(-variable)%>%
    rename(WEIGHT = SYS02, variable = VAR, ANIM = PRODUCT )

  return(ANIMALS.production.all)

}