From b0e4bce915fccfca8a3c401cd7c7be9988959c12 Mon Sep 17 00:00:00 2001
From: cazodi <cazodi@svi.edu.au>
Date: Fri, 17 Apr 2020 09:41:10 +1000
Subject: [PATCH] update hosp weekly to have ci bars
---
NAMESPACE | 1 +
R/get_weekly_local.R | 92 --------------------------------------------
2 files changed, 1 insertion(+), 92 deletions(-)
delete mode 100644 R/get_weekly_local.R
diff --git a/NAMESPACE b/NAMESPACE
index fb6c891..5d5645c 100644
--- a/NAMESPACE
+++ b/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)
diff --git a/R/get_weekly_local.R b/R/get_weekly_local.R
deleted file mode 100644
index 92d7182..0000000
--- a/R/get_weekly_local.R
+++ /dev/null
@@ -1,92 +0,0 @@
-#' 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))
-
-}
-
--
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