Revision style as Cata suggested

Author: AliceBeckmann

DESCRIPTION

@@ -4,7 +4,8 @@ Version: 0.0.0.9000
 Authors@R: c(
     person("Catalin", "Covaci", , "catalin.covaci@csic.es", role = c("aut", "cre"), comment = c(ORCID = "0009-0005-2186-5972")),
     person("Eduardo", "Aguilera", , "eduardo.aguilera@csic.es", role = c("aut"), comment = c(ORCID = "0000-0003-4382-124X")),
-    person("João", "Serra", , "jserra@agro.au.dk", role = c("ctb"), comment = c(ORCID = "0000-0002-3561-5350"))
+    person("João", "Serra", , "jserra@agro.au.dk", role = c("ctb"), comment = c(ORCID = "0000-0002-3561-5350")),
+    person("Alice", "Beckmann", , "alice.beckmann@cchs.csic.es", role = c("aut"), comment = c(ORCID = "0009-0009-6840-0258"))
   )
 Description: Gather historical agricultural and trade data from 1850.
 License: MIT + file LICENSE

NAMESPACE

@@ -1,6 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
-export(.create_prod_and_destiny_grafs)
+export(create_prod_and_destiny_grafs)
 export(add_area_code)
 export(add_area_name)
 export(add_item_cbs_code)

R/Typologies_Julia.R

@@ -15,12 +15,13 @@
 #'
 #' @export
 create_typologies_grafs_spain <- function(
-    make_map = TRUE,
-    shapefile_path = paste0(
-      "C:/PhD/GRAFS/Production Boxes/",
-      "Final Files/Inputs/ne_10m_admin_1_states_provinces.shp"
-    ),
-    map_year = 1980) {
+  make_map = TRUE,
+  shapefile_path = paste0(
+    "C:/PhD/GRAFS/Production Boxes/",
+    "Final Files/Inputs/ne_10m_admin_1_states_provinces.shp"
+  ),
+  map_year = 1980
+) {
   inputs_dir <- "C:/PhD/GRAFS/Production Boxes/Final Files/Inputs"
 
   # Load datasets
@@ -131,6 +132,7 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Load input datasets ---------------------------------------------------------
+#'
 #' @param shapefile_path The local path where the input data are located.
 #' @param inputs_dir Path to the input data directory.
 #'
@@ -180,6 +182,7 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Prepare LU coefficients with Livestock_cat mapping --------------------------
+#'
 #' @param codes_coefs_df An excel file including coefficients.
 #' @keywords internal
 .prepare_lu_coefs <- function(codes_coefs_df) {
@@ -192,8 +195,8 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Calculate LU_total per row --------------------------------------------------
-#' @param livestock_df A data frame containing livestock data.
 #'
+#' @param livestock_df A data frame containing livestock data.
 #' @param lu_coefs_df A data frame with livestock unit coefficients.
 #'
 #' @return A tibble with columns 'Year', 'Province_name', 'Livestock_cat',
@@ -250,8 +253,8 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Calculate livestock density -------------------------------------------------
-#' @param lu_totals_df A data frame containing livestock total data.
 #'
+#' @param lu_totals_df A data frame containing livestock total data.
 #' @param area_df A data frame containing area information.
 #'
 #' @return A tibble with columns 'Year', 'Province_name', 'LU_total', 'Area_ha',
@@ -266,6 +269,7 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Aggregate Productivity for Cropland -----------------------------------------
+#'
 #' @param npp_df A data frame containing columns `Year`, `Province_name`,
 #' `LandUse`,`Prod_MgN`, and `Area_ygpit_ha`.
 #'
@@ -309,6 +313,7 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Aggregate Feed from Cropland -----------------------------------------------
+#'
 #' @param df A data frame containing columns `Year`, `Province_name`,
 #' `Box`, `Destiny`, and `MgN`.
 #'
@@ -371,9 +376,9 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Calculate feed domestic supply ---------------------------------------------
+#'
 #' @param grafs_df A data frame containing GRAFS data with the columns Destiny',
 #' 'Year', 'Province_name', and 'MgN'.
-#'
 #' @param lu_df A data frame with land use data.
 #'
 #' @return A tibble with columns 'Year', 'Province_name', and
@@ -388,7 +393,7 @@ create_typologies_grafs_spain <- function(
       na.rm = TRUE
     ), .groups = "drop")
 
-  #' Add LU_total for use in further steps
+  # Add LU_total for use in further steps
   domestic_feed |>
     dplyr::left_join(
       lu_df |> dplyr::select(Year, Province_name, LU_total),
@@ -397,8 +402,8 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Calculate feed import per province -----------------------------------------
-#' @param feed_df A data frame containing feed data.
 #'
+#' @param feed_df A data frame containing feed data.
 #' @param lu_df A data frame with land use information.
 #'
 #' @return A tibble with columns 'Year', 'Province_name', 'LU_total',
@@ -434,13 +439,16 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Calculate feed share of imported/consumed feed -----------------------------
+#'
 #' @param feed_import_by_province A data frame containing imported feed data.
 #' @param domestic_feed_by_province A data frame containing domestic feed data.
 #'
 #' @return A data frame with the imported feed share.
 #' @keywords internal
-.calculate_imported_feed_share <- function(feed_import_by_province,
-                                           domestic_feed_by_province) {
+.calculate_imported_feed_share <- function(
+  feed_import_by_province,
+  domestic_feed_by_province
+) {
   feed_import_by_province |>
     dplyr::left_join(
       domestic_feed_by_province,
@@ -465,6 +473,7 @@ create_typologies_grafs_spain <- function(
 }
 
 #' Assign Typologies and optionally plot map
+#'
 #' @param livestock_density A data frame with livestock density values.
 #' @param productivity A data frame with productivity (kgN/ha) values.
 #' @param semi_nat_share A data frame with semi-natural agroecosystem share.
@@ -476,8 +485,9 @@ create_typologies_grafs_spain <- function(
 #' typology for the specified year.
 #' @keywords internal
 .assign_decision_tree <- function(
-    livestock_density, productivity, semi_nat_share, imported_feed_share,
-    sf_provinces, year) {
+  livestock_density, productivity, semi_nat_share, imported_feed_share,
+  sf_provinces, year
+) {
   typologies <- livestock_density |>
     dplyr::inner_join(productivity, by = c("Year", "Province_name")) |>
     dplyr::inner_join(semi_nat_share, by = c("Year", "Province_name")) |>
@@ -555,3 +565,43 @@ create_typologies_grafs_spain <- function(
     Typologies_all_years = typologies_all_years
   )
 }
+
+
+# Create bar plots for N inputs per typology and year
+.create_bar_plots_typologies <- function(n_inputs_data,
+                                         typologies, output_dir = NULL) {
+  # Merging n_inputs_data with typologies (per Year and Province_name)
+  typologies <- n_inputs_data %>%
+    inner_join(typologies, by = c("Year", "Province_name"))
+
+  bar_plot_data <- typologies %>%
+    group_by(Typology, Year) %>%
+    summarise(
+      MgN_dep = sum(MgN_dep, na.rm = TRUE),
+      MgN_fix = sum(MgN_fix, na.rm = TRUE),
+      MgN_syn = sum(MgN_syn, na.rm = TRUE),
+      .groups = "drop"
+    ) %>%
+    pivot_longer(
+      cols = c(MgN_dep, MgN_fix, MgN_syn),
+      names_to = "n_input",
+      values_to = "MgN_amount"
+    )
+
+  # Stacked Bar Plot erstellen
+  p <- ggplot(bar_plot_data, aes(x = factor(Year), y = MgN_amount, fill = n_input)) +
+    geom_bar(stat = "identity") +
+    facet_wrap(~Typology) +
+    labs(
+      title = "Stacked Barplots of N_Inputs per Typology",
+      x = "Year",
+      y = "MgN",
+      fill = "Input"
+    ) +
+    theme_minimal() +
+    theme(axis.text.x = element_text(angle = 45, hjust = 1))
+
+  print(p)
+
+  return(p)
+}

R/GRAFS_N_Inputs_git.R R/grafs_n_inputs.RR/GRAFS_N_Inputs_git.R renamed to R/grafs_n_inputs.R

@@ -1,11 +1,10 @@
-#' @title Create N Inputs and NUE Dataset for GRAFS Spain
+#' @title N Inputs and NUE for GRAFS Spain
 #'
 #' @description
 #' N Inputs, Production and NUE in Spain:
 #' This code is creating a dataset with nitrogen (N) inputs (deposition,
-#' fixation, synthetic, urban, manure)
-#' and N production in Spain between 1860 and 2020 for the GRAFS model on a
-#' provincial level
+#' fixation, synthetic, urban, manure) and N production in Spain between
+#' 1860 and 2020 for the GRAFS model on a provincial level
 #'
 #' @return
 #' A named list with two elements:
@@ -46,27 +45,31 @@ create_n_inputs_grafs_spain <- function() {
   )
 }
 
-# N Inputs --------------------------------------------------------------------
-# load data -------------------------------------------------------------------
-# @keywords internal
+#' @title N Inputs -------------------------------------------------------------
+#' @description Loading all required data sets.
+#' @return A named list including four datasets.
+#' @keywords internal
+#' @noRd
 .load_inputs_n_inputs <- function() {
   result <-
     list(
       n_Excretion_ygs = readRDS(get_file_path("n_excretion_ygs")),
       # TODO: Excretion need to be added to dataset as an input of Livestock
       n_balance_ygpit_all = readRDS(get_file_path("n_balance_ygpit_all")),
-      grafs_prod_destiny = readr::read_csv(get_file_path(
-        "GRAFS_prod_destiny_git"
-      )),
+      grafs_prod_destiny = readr::read_csv(
+        get_file_path("GRAFS_prod_destiny_git")
+      ),
       codes_coefs = readxl::read_excel(get_file_path("codes_coefs"),
         sheet = "Names_biomass_CB"
       )
     )
   result
 }
 
-# Assign some special items to Boxes ------------------------------------------
-# @keywords internal
+#' @title Assign some special items to Boxes -----------------------------------
+#' @return A named list with assigned items.
+#' @keywords internal
+#' @noRd
 .assign_items <- function() {
   list(
     semi_natural_agroecosystems = c(
@@ -81,9 +84,21 @@ create_n_inputs_grafs_spain <- function() {
   )
 }
 
-# Calculate n Inputs ----------------------------------------------------------
-# @keywords internal
-.calculate_n_inputs <- function(n_balance_ygpit_all, codes_coefs) {
+#' @title Calculate N Inputs ---------------------------------------------------
+#' @description Merges N balance data with items and aggregates deposition,
+#' fixation, synthetic, urban, and manure inputs for each combination of year,
+#' province, item, and box.
+#'
+#' @param n_balance_ygpit_all A data frame containing nitrogen balance data.
+#' @param codes_coefs A data frame merging biomass names to item names.
+#'
+#' @return A list with two tibbles: 'n_inputs_summary' and 'manure_summary'.
+#' @keywords internal
+#' @noRd
+.calculate_n_inputs <- function(
+  n_balance_ygpit_all,
+  codes_coefs
+) {
   categories <- .assign_items()
   firewood_biomass <- categories$Firewood_biomass
   semi_natural_agroecosystems <- categories$semi_natural_agroecosystems
@@ -145,9 +160,18 @@ create_n_inputs_grafs_spain <- function() {
   )
 }
 
-# Combine all Inputs ----------------------------------------------------------
-# @keywords internal
-.summarise_inputs <- function(n_inputs_prepared) {
+#' @title Combine all Inputs ---------------------------------------------------
+#' @description Combines different N input sources and calculates total values
+#' per year, province, item, and box.
+#'
+#' @param n_inputs_prepared A list with 'n_inputs_summary' and 'manure_summary'
+#'
+#' @return A tibble summarising nitrogen input components by item and region.
+#' @keywords internal
+#' @noRd
+.summarise_inputs <- function(
+  n_inputs_prepared
+) {
   n_inputs <- dplyr::full_join(
     n_inputs_prepared$n_inputs_summary,
     n_inputs_prepared$manure_summary,
@@ -168,11 +192,20 @@ create_n_inputs_grafs_spain <- function() {
   n_inputs_sum
 }
 
-# GRAFS_Prod_Destiny ---------------------------------------------------------
-# Summarize and calculate new columns: Prod_MgN
-# Spread Destiny column to separate columns for Food, Feed, Other_uses, Export
-# @keywords internal
-.summarise_production <- function(grafs_prod_destiny, n_inputs_sum) {
+#' @title GRAFS_Prod_Destiny ---------------------------------------------------
+#' @description Summarize and calculate new columns: Prod_MgN
+#' Spread Destiny column to separate columns for Food, Feed, Other_uses, Export
+#'
+#' @param grafs_prod_destiny Data containing production values by destiny.
+#' @param n_inputs_sum A tibble of summarized N inputs.
+#'
+#' @return A tibble with combined N input and production data.
+#' @keywords internal
+#' @noRd
+.summarise_production <- function(
+  grafs_prod_destiny,
+  n_inputs_sum
+) {
   grafs_prod_destiny_summary <- grafs_prod_destiny |>
     tidyr::pivot_wider(
       names_from = Destiny, values_from = MgN, values_fn = sum,
@@ -194,18 +227,28 @@ create_n_inputs_grafs_spain <- function() {
     dplyr::select(Year, Province_name, Item, Box, Import_MgN, Prod_MgN)
 
   # Combine with n_inputs dataset
-  n_inputs_combined <- dplyr::full_join(n_inputs_sum,
-    grafs_prod_destiny_summary,
+  n_inputs_combined <- dplyr::full_join(
+    n_inputs_sum, grafs_prod_destiny_summary,
     by = c("Year", "Province_name", "Item", "Box")
   ) |>
     dplyr::filter(!is.na(Box))
 
   n_inputs_combined
 }
 
-# NUE for Cropland and Semi-natural agroecosystems ----------------------------
-# @keywords internal
-.calculate_nue <- function(n_inputs_combined) {
+#' @title NUE for Cropland and Semi-natural agroecosystems ---------------------
+#' @description Calculates NUE for cropland and semi-natural agroecosystems as
+#' the ratio of production to total N input.
+#'
+#' @param n_inputs_combined A data frame combining N inputs and production.
+#'
+#' @return A tibble with calculated NUE values for cropland and semi-natural
+#' agroecosystems.
+#' @keywords internal
+#' @noRd
+.calculate_nue <- function(
+  n_inputs_combined
+) {
   nue <- n_inputs_combined |>
     dplyr::mutate(
       Inputs_MgN = MgN_dep + MgN_fix + MgN_syn + MgN_manure + MgN_urban