BaseSet (version 0.9.0)

union: Join sets

Description

Given a TidySet merges several sets into the new one using the logic defined on FUN.

Usage

union(object, ...)
# S3 method for TidySet
union(
  object,
  sets,
  name = NULL,
  FUN = "max",
  keep = FALSE,
  keep_relations = keep,
  keep_elements = keep,
  keep_sets = keep,
  ...
)

Value

A TidySet object.

Arguments

object

A TidySet object.

...

Other named arguments passed to FUN.

sets

The name of the sets to be used.

name

The name of the new set. By defaults joins the sets with an ∩.

FUN

A function to be applied when performing the union. The standard union is the "max" function, but you can provide any other function that given a numeric vector returns a single number.

keep

A logical value if you want to keep.

keep_relations

A logical value if you wan to keep old relations.

keep_elements

A logical value if you wan to keep old elements.

keep_sets

A logical value if you wan to keep old sets.

Details

The default uses the max function following the standard fuzzy definition, but it can be changed. See examples below.

See Also

union_probability()

Other methods that create new sets: complement_element(), complement_set(), intersection(), subtract()

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(), set_size(), sets(), subtract()

Examples

# Classical set
rel <- data.frame(
    sets = c(rep("A", 5), "B", "B"),
    elements = c(letters[seq_len(6)], "a")
)
TS <- tidySet(rel)
union(TS, c("B", "A"))
# Fuzzy set
rel <- data.frame(
    sets = c(rep("A", 5), "B", "B"),
    elements = c(letters[seq_len(6)], "a"),
    fuzzy = runif(7)
)
TS2 <- tidySet(rel)
# Standard default logic
union(TS2, c("B", "A"), "C")
# Probability logic
union(TS2, c("B", "A"), "C", FUN = union_probability)