update hosp weekly to have ci bars

NAMESPACE

@@ -17,6 +17,7 @@ export(departures.FUN)
 export(format_sims)
 export(get_ci)
 export(get_prev.FUN)
+export(get_weekly_local)
 export(infection.FUN)
 export(init_seiqhrf)
 export(init_status.icm)

R/get_weekly_local.R

-#' Extract information of local and weekly estimates from simulation 
-#'
-#'
-#' @param sim An \code{seiqhrf} object returned by \link{simulate_seiqhrf}. 
-#' @param market.share between 0 and 1, percentage of local hospital beds in 
-#'        the simulated unit (e.g. state)
-#' @param icu_percent between 0 and 1, percentage of patients that should go to 
-#'        ICU among the ones that need hospitalization
-#' @param start_date Epidemic start date. Default is 'na', if not provided will 
-#'        plot week numbers, if provided will plot the first day (Sunday) of the
-#'        week.
-#' @param time_limit Number of days to include. Default = 90.
-#' @param total_population True population size, needed only if simulation size 
-#'        is smaller than the true population size due to computational cost 
-#'        etc.
-#' 
-#' @return 
-#' \itemize{
-#' \item \code{plot:} A \code{ggplot} object, bar charts of count of patients 
-#'              requiring hospitalization and ICU respectively
-#' \item \code{result:} A dataframe
-#'    \itemize{\item \code{week:}  week number from input \code{sim},
-#'             \item \code{hosp:} the number of patients that require hospitalization locally,
-#'             \item \code{icu:} the number of patients that require ICU locally. }
-#
-#' }
-#' 
-#' @importFrom tidyr pivot_wider
-#' 
-get_weekly_local <- function(sim, 
-                             market.share = .04,
-                             icu_percent = .1, 
-                             start_date = 'na',
-                             time_limit = 90,
-                             total_population = NULL){
-  
-  sim_mean <- as.data.frame(sim, out = "mean")
-  
-  hosp <- sim_mean$h.num
-  
-  if(!is.null(total_population)){
-    if(total_population < max(sim_mean$s.num)) 
-      stop("total Population should be larger than simulated size")
-    cat("Scalling w.r.t total population")
-    hosp <- hosp*total_population/max(sim_mean$s.num)
-  } 
-  
-  if(market.share < 0 || market.share > 1) stop("Market share has to be between 
-                                                0 and 1")
-  if(icu_percent < 0 || icu_percent > 1) stop("ICU percentage has to be between
-                                              0 and 1")
-  
-  hosp[is.na(hosp)] <- 0
-  hosp <- hosp[1: time_limit]
-  
-  hosp_week <- split(hosp, ceiling(seq_along(hosp)/7))
-  hosp_sum_week <- unlist(lapply(hosp_week, sum))
-  t_sz <- length(hosp_sum_week)
-  
-  hosp_wk_df <- data.frame(wk = rep(seq_along(hosp_sum_week), 2), 
-                           group = rep(c("general", "icu"), 
-                                       each = t_sz),
-                           hosp_icu = c(hosp_sum_week - 
-                                           (hosp_sum_week*icu_percent), 
-                                         hosp_sum_week*icu_percent))
-  
-  if(class(start_date) == 'Date'){
-    
-    hosp_wk_df <- data.frame(append(hosp_wk_df,
-                                    list(Date=start_date + 
-                                           (7 * (hosp_wk_df$wk - 1))),
-                                    after=match("wk", names(hosp_wk_df))))
-    
-    gg <- ggplot(data=hosp_wk_df, aes(x = Date, y = hosp_icu, fill = group)) +
-      geom_bar(stat="identity") + theme_bw() +
-      scale_x_date(date_breaks = "1 week", date_labels = "%m-%d") + 
-      labs(y="Weekly Hospital Load (sum over week)", x = "Week")
-    
-  }else{
-
-    gg <- ggplot(data=hosp_wk_df, aes(x = wk, y = hosp_icu, fill = group)) +
-      geom_bar(stat="identity") + theme_bw() +
-      labs(y="Weekly Hospital Load (sum over week)", x = "Week") + 
-      scale_x_continuous(breaks = seq(0,t_sz,5), labels= seq(0,t_sz,5))
-  }
-  
-  res <- hosp_wk_df %>% tidyr::pivot_wider(names_from = group, values_from = hosp_icu)
-                    
-  return(list("plot" = gg, "result" = res))
- 
-}
-