R/make-excluded-df.R

In lifecycle-project/ds-helper: Helper Functions for Use with 'DataSHIELD'

#' Given df-A & df-B, creates a new df which is the rows in A but not in B
#'
#' When writing a paper often we need to exclude various participants for 
#' various reasons. Then we will need a df with all of these excluded 
#' participants. This is one way to do it.
#'
#' @param original_df Dataframe containing the full sample
#' @param final_df Dataframe containing the included sample
#' @param type Specifies type of dataframe in `original_df`. Either 'long' or
#' 'wide'. NOTE NOT CURRENTLY FUNCTIONAL - ONLY WORKS FOR WIDE.
#' @template new_obj
#' @template conns
#' 
#' @return Creates a serverside dataframe containing the rows from `original_df`
#' that are not contained in `final_df`   
#' 
#' @importFrom utils head
#'
#' @export
dt.makeExcludedDf <- function(original_df, final_df, id_var = "child_id", new_obj,
                              type = "wide", conns = NULL){
  
  if (is.null(conns)) {
    conns <- datashield.connections_find()
  }
  
  dims <- ds.dim(final_df)
  
  length.ref <- tibble(
    cohort = names(conns), 
    length = dims %>% map(~.x[[1]]) %>% unlist() %>% head(-1) %>% as.character)
  
  length.ref %>%
    pmap(function(cohort, length){
      ds.rep(
        x1 = 1,
        times = length,
        source.x1 = "clientside",
        source.times = "c",
        newobj = "final_ones", 
        datasources = conns[cohort])
    })
  
  ds.dataFrame(
    x = c(paste0(final_df, "$", id_var), "final_ones"),
    newobj = "final_tmp")
  
## ---- Now merge this vector with baseline_df ---------------------------------

if(type == "wide"){
  
  ds.merge(
  x.name = original_df,
  y.name = "final_tmp",
  by.x.names = id_var,
  by.y.names = id_var,
  all.x = TRUE,
  all.y = FALSE, 
  newobj = "orig_w_vec")
  
} else if(type == "long"){
  
  ds.merge(
    x.name = original_df,
    y.name = "final_tmp",
    by.x.names = c(id_var, "age"),
    by.y.names = c(id_var, "age"),
    all.x = TRUE,
    all.y = FALSE, 
    newobj = "orig_w_vec")
  
}

## ---- Transform case_def to binary vector ------------------------------------
ds.Boole(
  V1 = paste0("orig_w_vec$final_ones"), 
  V2 = 1, 
  Boolean.operator = "==", 
  na.assign = "0", 
  newobj = "exc_vec")
  
## ---- Create excluded subset based on this vector ----------------------------
ds.dataFrameSubset(
  df.name = original_df, 
  V1.name = "exc_vec", 
  V2.name = "0", 
  Boolean.operator = "==", 
  keep.NAs = FALSE, 
  newobj = new_obj)

}