new function as_popim_vacc_activities()

NAMESPACE

@@ -2,6 +2,7 @@
 
 export(apply_vacc)
 export(as_popim_pop)
+export(as_vacc_activities)
 export(calc_pop_immunity)
 export(complete_vacc_activities)
 export(plot_immunity)

R/popim_population.R

@@ -138,9 +138,9 @@ read_popim_pop <- function(file) {
 ##' columns and data ranges), and if so converts it to a
 ##' `popim_population` object and returns this.
 ##'
-##' The input dataframe has to have at least the columns region, age,
-##' and year. The output popim_population object is generated via
-##' expand.grid to have consecutive year and age ranges that are
+##' The input dataframe has to have at least the columns `region`,
+##' `age`, and `year`. The output popim_population object is generated
+##' via expand.grid to have consecutive year and age ranges that are
 ##' identical for all regions.
 ##'
 ##' If the input dataframe contains a column `pop_size`, this must be
@@ -151,9 +151,11 @@ read_popim_pop <- function(file) {
 ##' numeric, with values between 0 and 1. If it is missing, this
 ##' column is generated and initialised to 0.
 ##'
-##' Any further colunms are simply carried over into the popim_population object.
+##' Any further colunms are simply carried over into the
+##' popim_population object.
 ##'
-##' @param df a dataframe with at least columns region, age, year and pop_size.
+##' @param df a dataframe with at least columns region, age, year and
+##'     pop_size.
 ##' @return an object of class `popim_population`
 ##' @author Tini Garske
 ##' @export

R/popim_vacc_activities.R

@@ -173,10 +173,31 @@ read_vacc_activities <- function(file) {
         stop(sprintf("%s does not exist", file), call. = FALSE)
 
     df <- utils::read.csv(file, stringsAsFactors = FALSE)
-    class(df) <- c("popim_vacc_activities", "data.frame")
+    df <- as_vacc_activities(df)
+    df
+}
 
-    validate_vacc_activities(df)
+##' Generate a `popim_vacc_activites object from a dataframe
+##'
+##' Checks if the dataframe is suitable (i.e., contains appropriate
+##' columns and data ranges), and if so converts it to a
+##' `popim_vacc_activities` object and returns this.
+##'
+##' The input dataframe has to have at least teh columns `region`,
+##' `year`, `age_first`, `age_last`, `coverage`, `doses` and
+##' `targeting`. Any further columns are simply carried over into the
+##' `popim_vacc_activities` object.
+##'
+##' @param df dataframe to be converted to class
+##'     `popim_vacc_activities`
+##' @return an object of class `popim_vacc_activities`
+##' @author Tini Garske
+##' @seealso [popim_vacc_activities()] for details of the S3 class.
+##' @export
+as_vacc_activities <- function(df) {
 
+    class(df) <- c("popim_vacc_activities", "data.frame")
+    validate_vacc_activities(df)
     df
 }