Functions to help to perform some action to just some type of data: elements,
sets or relations.
activate: To table the focus of future manipulations: elements, sets
or relations.
active: To check the focus on the TidySet.
deactivate: To remove the focus on a specific TidySet-
See also
Other methods:
TidySet-class,
add_column(),
add_relation(),
arrange.TidySet(),
cartesian(),
complement(),
complement_element(),
complement_set(),
element_size(),
elements(),
filter.TidySet(),
group(),
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
relations <- data.frame(
sets = c(rep("a", 5), "b", rep("a2", 5), "b2"),
elements = rep(letters[seq_len(6)], 2),
fuzzy = runif(12)
)
a <- tidySet(relations)
elements(a) <- cbind(elements(a),
type = c(rep("Gene", 4), rep("lncRNA", 2))
)
# Filter in the whole TidySet
filter(a, elements == "a")
#> elements sets fuzzy type
#> 1 a a 0.49777739 Gene
#> 2 a a2 0.03424133 Gene
filter(a, elements == "a", type == "Gene")
#> elements sets fuzzy type
#> 1 a a 0.49777739 Gene
#> 2 a a2 0.03424133 Gene
# Equivalent to filter_elements
filter_element(a, type == "Gene")
#> elements sets fuzzy type
#> 1 a a 0.49777739 Gene
#> 2 b a 0.28976724 Gene
#> 3 c a 0.73288199 Gene
#> 4 d a 0.77252151 Gene
#> 5 a a2 0.03424133 Gene
#> 6 b a2 0.32038573 Gene
#> 7 c a2 0.40232824 Gene
#> 8 d a2 0.19566983 Gene
a <- activate(a, "elements")
active(a)
#> [1] "elements"
filter(a, type == "Gene")
#> elements sets fuzzy type
#> 1 a a 0.49777739 Gene
#> 2 b a 0.28976724 Gene
#> 3 c a 0.73288199 Gene
#> 4 d a 0.77252151 Gene
#> 5 a a2 0.03424133 Gene
#> 6 b a2 0.32038573 Gene
#> 7 c a2 0.40232824 Gene
#> 8 d a2 0.19566983 Gene
a <- deactivate(a)
active(a)
#> NULL
filter(a, type == "Gene")
#> elements sets fuzzy type
#> 1 a a 0.49777739 Gene
#> 2 b a 0.28976724 Gene
#> 3 c a 0.73288199 Gene
#> 4 d a 0.77252151 Gene
#> 5 a a2 0.03424133 Gene
#> 6 b a2 0.32038573 Gene
#> 7 c a2 0.40232824 Gene
#> 8 d a2 0.19566983 Gene
