It allows to create a new set given some condition. If no element meet the condition an empty set is created.
See also
Other methods:
TidySet-class,
activate(),
add_column(),
add_relation(),
arrange.TidySet(),
cartesian(),
complement(),
complement_element(),
complement_set(),
element_size(),
elements(),
filter.TidySet(),
group_by.TidySet(),
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
x <- list("A" = c("a" = 0.1, "b" = 0.5), "B" = c("a" = 0.2, "b" = 1))
TS <- tidySet(x)
TS1 <- group(TS, "C", fuzzy < 0.5)
TS1
#> elements sets fuzzy
#> 1 a A 0.1
#> 2 b A 0.5
#> 3 a B 0.2
#> 4 b B 1.0
#> 5 a C 1.0
sets(TS1)
#> sets
#> 1 A
#> 2 B
#> 3 C
TS2 <- group(TS, "D", fuzzy < 0)
sets(TS2)
#> sets
#> 1 A
#> 2 B
#> 3 D
r <- data.frame(
sets = c(rep("A", 5), "B", rep("A2", 5), "B2"),
elements = rep(letters[seq_len(6)], 2),
fuzzy = runif(12),
type = c(rep("Gene", 2), rep("Protein", 2), rep("lncRNA", 2))
)
TS3 <- tidySet(r)
group(TS3, "D", sets %in% c("A", "A2"))
#> elements sets fuzzy type
#> 1 a A 0.02795603 Gene
#> 2 b A 0.46938430 Gene
#> 3 c A 0.80568003 Protein
#> 4 d A 0.81405131 Protein
#> 5 e A 0.40391100 lncRNA
#> 6 f B 0.21843101 lncRNA
#> 7 a A2 0.41836140 Gene
#> 8 b A2 0.66887075 Gene
#> 9 c A2 0.50765028 Protein
#> 10 d A2 0.66035931 Protein
#> 11 e A2 0.51179131 lncRNA
#> 12 f B2 0.83555244 lncRNA
#> 13 a D 1.00000000 <NA>
#> 14 b D 1.00000000 <NA>
#> 15 c D 1.00000000 <NA>
#> 16 d D 1.00000000 <NA>
#> 17 e D 1.00000000 <NA>