Remove unused functions

01_INVENTORY/INVENTORY_00_R_functions.R

@@ -61,27 +61,6 @@ get_target_list_for_observational_study <- function(x, n_target) {
 
 
 
-#' Calculate the expected sample size for a given group
-#'
-#' @param n_obs The number of observations in a group nested within a cluster.
-#' @param n_tot The total number of inhabitants in the corresponding cluster.
-#' @param n_target The total target sample size in the cluster.
-#' @return The number of participants to sample among the group of interest in the cluster population or, if there's too few, the total number of observations in that group.
-get_group_sample_size <- function(n_obs, n_tot, n_target) {
-  
-  if (n_tot <= n_target) {
-    return(n_obs)
-    
-    } else {
-    n_group = round((n_obs/n_tot)*n_target, 0)
-    
-    return(n_group)}
-}
-
-
-
-
-
 #' Randomly subset group to a given size
 #'
 #' @param x A data.frame containing the population inventory in a wide format. It should be the output of \code{INVENTORY_02_list_all_inventory_participants.R}.
@@ -101,57 +80,3 @@ get_group_subset <- function(x, country_f, clusterid_f, sex_f, agey_cat_f, n_tar
   
   return(as.data.frame(res))
 }
-
-
-
-
-
-#' Extract random subset from the population list
-#'
-#' @param x A data.frame containing the population inventory in a wide format. It should be the output of \code{INVENTORY_02_list_all_inventory_participants.R}.
-#' @param clusterid The cluster ID to restrict the data to.
-#' @param n_target The total target sample size in the cluster.
-#' @return Writes the subset list into a dedicated CSV file.
-get_population_subset_in_cluster <-  function(clusterid, n_target) {
-  df <- x %>% 
-    count(country, clusterid, sex, ageClass, name = "sexage_n") %>% 
-    left_join(
-      x %>% group_by(clusterid) %>% 
-        summarise(pop_cluster = n())) %>%
-    mutate(n_target = mapply(get_group_sample_size, 
-                             sexage_n, 
-                             pop_cluster, 
-                             n_target),
-           list = mapply(get_group_subset, 
-                         x, 
-                         clusterid, 
-                         sex,
-                         ageClass,
-                         n_target,
-                         SIMPLIFY = FALSE)) %>% 
-    filter(clusterid == clusterid) 
-  sample_list <- bind_rows(df$list)
-  file_name <- paste0("outputs/sample_cluster_",
-                      clusterid,"_", 
-                      strftime(Sys.time(), 
-                               format = "%Y%m%d_%H%M%S"),".csv")
-  
-  return(write.csv2(sample_list, file_name))
-}
-
-
-
-
-
-#' Loop subset functions over multiple clusters
-#'
-#' @param clusterids The cluster IDs over which the subset routine should be iterated.
-#' @param n_targets The total target sample sizes for each cluster in \code{clusterids}.
-#' @return Writes the subset lists resulting from calls to \code{\link{get_population_subset_in_cluster}} into dedicated CSV file.
-get_population_subset <- function(clusterids, n_targets) {
-  index <- 1
-  for (index in 1:length(clusterids)) {
-    get_population_subset_in_cluster(clusterids[index], n_targets[index])
-    index <- index + 1
-  }
-}