An S3 class
packs_info to represent information about packs in exposure.
It is a tibble with the following structure:
is_packs_info(.x, .skip_class = FALSE) get_packs_info(.object)
Object to test.
Whether to skip checking inheritance from
Object to get
packs_info attribute of
object if it
is exposure and of its 'exposure' attribute otherwise.
To avoid possible confusion it is preferred (but not required) that
fun doesn't have names. Names of packs are stored in
column. During exposure
fun is always created without names.
my_row_packs <- row_packs( row_mean_props = . %>% dplyr::transmute(row_mean = rowMeans(.)) %>% dplyr::transmute( row_mean_low = row_mean > 20, row_mean_high = row_mean < 60 ), row_outlier = . %>% dplyr::transmute(row_sum = rowSums(.)) %>% dplyr::transmute( not_row_outlier = abs(row_sum - mean(row_sum)) / sd(row_sum) < 1.5 ) ) my_data_packs <- data_packs( data_dims = . %>% dplyr::summarise(nrow = nrow(.) == 32, ncol = ncol(.) == 5) ) mtcars_exposed <- mtcars %>% expose(my_data_packs, .remove_obeyers = FALSE) %>% expose(my_row_packs) mtcars_exposed %>% get_packs_info()#> Packs info: #> # A tibble: 3 x 4 #> name type fun remove_obeyers #> <chr> <chr> <list> <lgl> #> 1 data_dims data_pack <data_pck> FALSE #> 2 row_mean_props row_pack <row_pack> TRUE #> 3 row_outlier row_pack <row_pack> TRUEmtcars_exposed %>% get_packs_info() %>% is_packs_info()#>  TRUE