Improve function documentation and add forestry, land, and fertilizer…

… data processing

.gitignore

@@ -33,4 +33,6 @@ IEA_EnergyBalances_2019.csv.gz
 
 
 # FAOSTATA raw zip
-inst/extdata/aglu/FAO/FAOSTAT/*.zip
+inst/extdata/aglu/FAO/FAOSTAT/*.zip
+inst/extdata/aglu/FAO/temp
+paper

DESCRIPTION

@@ -36,5 +36,5 @@ Suggests:
     rmarkdown
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
 VignetteBuilder: knitr

NAMESPACE

@@ -67,7 +67,6 @@ importFrom(dplyr,summarize)
 importFrom(dplyr,transmute)
 importFrom(dplyr,ungroup)
 importFrom(dplyr,vars)
-importFrom(gcamdata,gather_years)
 importFrom(ggplot2,aes)
 importFrom(ggplot2,facet_wrap)
 importFrom(ggplot2,geom_line)

R/xfaostat_L201_Forestry.R

@@ -167,6 +167,7 @@ module_xfaostat_L201_Forestry <- function(command, ...) {
     rm(FO_area, UnitMap, FO1, F01_Prod, FO1_Import_Q_V)
 
 
+    ## Produce output and export CSV ----
     GCAMDATA_FAOSTAT_ForProdTrade_215Regs_Roundwood_1973to2020 <-
       For_Balance %>% filter(element != "Demand") %>%
       spread(year, value)
@@ -175,7 +176,6 @@ module_xfaostat_L201_Forestry <- function(command, ...) {
       FO1_Export_Q_V %>% spread(year, value)
 
 
-
     GCAMDATA_FAOSTAT_ForProdTrade_215Regs_Roundwood_1973to2020 %>%
       add_title("FAO forestry production, export, and import (roundwood total) by country_year") %>%
       add_units("m3 ") %>%
@@ -189,8 +189,6 @@ module_xfaostat_L201_Forestry <- function(command, ...) {
       GCAMDATA_FAOSTAT_ForExportPrice_214Regs_Roundwood_1973to2020
 
 
-    ## Export CSV ----
-
     if (OUTPUT_Export_CSV == T) {
       output_csv_data(
         "GCAMDATA_FAOSTAT_ForProdTrade_215Regs_Roundwood_1973to2020",

R/xfaostat_L301_LandCover.R

@@ -44,7 +44,7 @@ module_xfaostat_L301_LandCover <- function(command, ...) {
     FAOSTAT_load_raw_data(DATASETCODE = "RL", DATA_FOLDER = DIR_RAW_DATA_FAOSTAT)
 
     ## Proprocess and quick clean ----
-    FF_summary("RL")
+    #FF_summary("RL")
     RL %>% distinct(element, element_code, unit)
     RL %>% distinct(area, area_code)
     RL %>% distinct(item, item_code)

R/xfaostat_L401_Fertilizer.R

@@ -42,7 +42,7 @@ module_xfaostatL401_Fertilizer <- function(command, ...) {
     FAOSTAT_load_raw_data(DATASETCODE = "RFN", DATA_FOLDER = DIR_RAW_DATA_FAOSTAT)
 
     ## Proprocess and quick clean ----
-    FF_summary("RFN")
+    #FF_summary("RFN")
     RFN %>% distinct(element, element_code, unit)
     RFN %>% distinct(area, area_code)
     RFN %>% distinct(item, item_code)

R/xfaostat_helper_funcs.R

@@ -219,7 +219,6 @@ FAO_AREA_RM_NONEXIST <- function(.DF,
 #' @param COL_CNTY Country column name
 #' @param COL_ITEM Item column name
 #' @importFrom dplyr summarize
-#' @importFrom gcamdata gather_years
 #' @importFrom  magrittr %>%
 #'
 #' @return A data frame with summary information,
@@ -228,7 +227,8 @@ FAO_AREA_RM_NONEXIST <- function(.DF,
 FF_summary <- function(DF, COL_CNTY = "area", COL_ITEM = "item"){
   assert_that(is.character(DF))
 
-  get(DF) %>% gcamdata::gather_years() -> .tbl1
+  get(DF) %>%
+    gather_years() -> .tbl1
   list_out<- list(
     dataset_code = DF,
     ncountry = length(unique(.tbl1[COL_CNTY])%>% pull()),
@@ -271,7 +271,8 @@ FF_FILL_NUMERATOR_DENOMINATOR <- function(.DF, NUMERATOR_c, DENOMINATOR_c,
     # setting NUMERATOR to NA if both prod and area are 0; it improves NUMERATOR interpolation
     mutate(NUMERATOR = if_else(NUMERATOR == 0 & DENOMINATOR == 0, NA_real_, NUMERATOR)) %>%
     # linearly interpolate NUMERATOR and fill in yield down-up
-    mutate(NUMERATOR = gcamdata::approx_fun(year, NUMERATOR)) %>%
+    mutate(NUMERATOR = approx_fun(year, NUMERATOR)) %>%
+    #mutate(NUMERATOR = gcamdata::approx_fun(year, NUMERATOR)) %>%
     tidyr::fill(NUMERATOR, .direction = NUMERATOR_FILL_DIRECTION) %>%
     tidyr::fill(Yield, .direction = "downup") %>%
     ungroup() %>%
@@ -479,7 +480,6 @@ FAOSTAT_check_count_plot <- function(.DF, .ELEMENT = c()){
 #' @param out_dir output directory
 #' @param GZIP IF TRUE
 #'
-#' @return
 #' @export
 
 output_csv_data <- function(gcam_dataset, col_type_nonyear,