Access location metadata

This accessor extracts variables from the locations data frame in an epiflow object. get_vars is a generic with a method defined for epiflows objects.

get_vars(x, ...)

# S3 method for epiflows
get_vars(x, what = NULL, id = TRUE,
  vector = FALSE, ...)

set_vars(x, ...)

set_vars(x, name) <- value

# S3 method for epiflows
set_vars(x, ...)

# S3 method for epiflows
set_vars(x, name) <- value

Arguments

x	An epiflows object.
...	For set_vars(), any number of variables defined in global_vars() that can be used for mapping or modelling. This is unused in get_vars()
what	a valid character string specifying the variable desired. If `NULL` (default), the names of the available vars will be returned.
id	a logical. If `TRUE` (default), the `id` column of the locations will be the first column of the data frame. if `FALSE`, the variable will be returned with identifiers as row names.
vector	if `TRUE` the result will be coerced into a vector (or a matrix in the case of coordinates)
name	the name of the variable in global_vars() to assign
value	the name of the column in the locations data

Value

A data frame with the variables requested

See also

global_vars(); make_epiflows(); get_pop_size(); get_id()

Examples

data("Brazil_epiflows")
get_vars(Brazil_epiflows) # defined global variables pointint to column names
#> $pop_size
#> [1] "location_population"
#> 
#> $duration_stay
#> [1] "length_of_stay"
#> 
#> $num_cases
#> [1] "num_cases_time_window"
#> 
#> $first_date
#> [1] "first_date_cases"
#> 
#> $last_date
#> [1] "last_date_cases"
#> 
get_vars(Brazil_epiflows, "duration_stay")
#>                          id length_of_stay
#> 1            Espirito Santo             NA
#> 2              Minas Gerais             NA
#> 3            Rio de Janeiro             NA
#> 4                 Sao Paulo             NA
#> 5          Southeast Brazil             NA
#> 6                 Argentina           10.9
#> 7                     Chile           10.3
#> 8                   Germany           22.3
#> 9                     Italy           30.1
#> 10                 Paraguay            7.3
#> 11                 Portugal           27.2
#> 12                    Spain           27.2
#> 13           United Kingdom           19.5
#> 14 United States of America           18.5
#> 15                  Uruguay            8.0
get_vars(Brazil_epiflows, "duration_stay", vector = TRUE)
#>           Espirito Santo             Minas Gerais           Rio de Janeiro 
#>                       NA                       NA                       NA 
#>                Sao Paulo         Southeast Brazil                Argentina 
#>                       NA                       NA                     10.9 
#>                    Chile                  Germany                    Italy 
#>                     10.3                     22.3                     30.1 
#>                 Paraguay                 Portugal                    Spain 
#>                      7.3                     27.2                     27.2 
#>           United Kingdom United States of America                  Uruguay 
#>                     19.5                     18.5                      8.0