Assuming that the fuzzy values are probabilities, calculates the probability of being of different sizes for a given set.

## Usage

``````set_size(object, sets = NULL)

# S4 method for TidySet
set_size(object, sets = NULL)``````

## Arguments

object

A TidySet object.

sets

The sets from which the length is calculated.

## Value

A list with the size of the set or the probability of having that size.

## Methods (by class)

• `set_size(TidySet)`: Calculates the size of a set using `length_set()`

cardinality

Other sizes: `element_size()`

Other methods: `TidySet-class`, `activate()`, `add_column()`, `add_relation()`, `arrange.TidySet()`, `cartesian()`, `complement_element()`, `complement_set()`, `complement()`, `element_size()`, `elements()`, `filter.TidySet()`, `group_by.TidySet()`, `group()`, `incidence()`, `intersection()`, `is.fuzzy()`, `is_nested()`, `move_to()`, `mutate.TidySet()`, `nElements()`, `nRelations()`, `nSets()`, `name_elements<-()`, `name_sets<-()`, `name_sets()`, `power_set()`, `pull.TidySet()`, `relations()`, `remove_column()`, `remove_element()`, `remove_relation()`, `remove_set()`, `rename_elements()`, `rename_set()`, `select.TidySet()`, `sets()`, `subtract()`, `union()`

## Examples

``````relations <- data.frame(
sets = c(rep("A", 5), "B", "C"),
elements = c(letters[seq_len(6)], letters[6]),
fuzzy = runif(7)
)
a <- tidySet(relations)
set_size(a)
#>    sets size  probability
#> 1     A    0 0.0003426333
#> 2     A    1 0.0209556642
#> 3     A    2 0.2353804439
#> 4     A    3 0.5097888990
#> 5     A    4 0.2297076037
#> 6     A    5 0.0038247559
#> 7     B    0 0.3220219053
#> 8     B    1 0.6779780947
#> 9     C    0 0.3348475387
#> 10    C    1 0.6651524613
``````