more examples

R/calc_new_immunity.R

@@ -66,6 +66,21 @@ assert_valid_targeting <- function(x, name = deparse(substitute(x))) {
 ##' @return A dataframe containing the `popim_population` aggregated by age.
 ##' @author Tini Garske
 ##' @export
+##' @examples
+##' ## set up population and vaccination activities:
+##' pop <- popim_population(region = "UK", year_min = 2000, year_max = 2005,
+##'                         age_min = 0, age_max = 10)
+##' vacc <- popim_vacc_activities(region = "UK", year = c(2001, 2002),
+##'                               age_first = 0, age_last = 0,
+##'                               coverage = 0.8, doses = NA,
+##'                               targeting = "random")
+##'
+##' ## update the population immunity based on the vaccination activities:
+##' pop <- apply_vacc(pop, vacc)
+##'
+##' ## calculate the population immunity aggregated across ages:
+##' pop_aggregated <- calc_pop_immunity(pop)
+##'
 calc_pop_immunity <- function(pop) {
 
     assert_population(pop)

R/plotting.R

@@ -24,6 +24,24 @@ NULL
 ##' @rdname plotting
 ##' @export
 ##' @author Tini Garske
+##' @examples
+##' ## set up population and vaccination activities:
+##' pop <- popim_population(region = "UK", year_min = 2000, year_max = 2005,
+##'                         age_min = 0, age_max = 10)
+##' vacc <- popim_vacc_activities(region = "UK", year = c(2001, 2002),
+##'                               age_first = 0, age_last = 0,
+##'                               coverage = 0.8, doses = NA,
+##'                               targeting = "random")
+##'
+##' ## update the population immunity based on the vaccination activities:
+##' pop <- apply_vacc(pop, vacc)
+##'
+##' ## plot the population size by age and time:
+##' plot_pop_size(pop)
+##'
+##' ## plot the population immunity by age and time:
+##' plot_immunity(pop)
+##'
 plot_immunity <- function(pop) {
 
     assert_population(pop)

R/popim_vacc_activities.R

@@ -226,6 +226,21 @@ as_vacc_activities <- function(df) {
 ##'     updated to have both `doses` and `coverage` information.
 ##' @author Tini Garske
 ##' @export
+##' @examples
+##' ## set up some vaccination activities:
+##' vacc <- popim_vacc_activities(region = "UK", year = 2001:2003,
+##'                               age_first = 0, age_last = 0,
+##'                               coverage = c(0.8, 0.8, NA),
+##'                               doses = c(NA, NA, 60),
+##'                               targeting = "random")
+##' ## set up a population to which these activities shall apply:
+##' pop <- popim_population(region = "UK", year_min = 2000, year_max = 2005,
+##'                         age_min = 0, age_max = 10)
+##' pop$pop_size <- 100 ## cohort size of 100 for all cohorts
+##'
+##' ## fill in missing coverage/doses information based on population size:
+##' vacc <- complete_vacc_activities(vacc, pop)
+##'
 complete_vacc_activities <- function(vacc, pop) {
     validate_vacc_activities(vacc)
     stopifnot(is_population(pop))