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

## Usage

``````element_size(object, elements = NULL)

# S4 method for TidySet
element_size(object, elements = NULL)``````

## Arguments

object

A TidySet object.

elements

The element from which the length is calculated.

## Value

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

## Methods (by class)

• `element_size(TidySet)`: Calculates the number of sets an element appears with `length_set()`

cardinality

Other sizes: `set_size()`

Other methods: `TidySet-class`, `activate()`, `add_column()`, `add_relation()`, `arrange.TidySet()`, `cartesian()`, `complement_element()`, `complement_set()`, `complement()`, `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()`, `set_size()`, `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)
element_size(a)
#>    elements size probability
#> 1         a    0   0.4400872
#> 2         a    1   0.5599128
#> 3         b    0   0.1429164
#> 4         b    1   0.8570836
#> 5         c    0   0.6151903
#> 6         c    1   0.3848097
#> 7         d    0   0.4720830
#> 8         d    1   0.5279170
#> 9         e    0   0.3993625
#> 10        e    1   0.6006375
#> 11        f    0   0.5243893
#> 12        f    1   0.3997999
#> 13        f    2   0.0758108
``````