A loop edge is an edge from a vertex to itself. An edge is a multiple edge if it has exactly the same head and tail vertices as another edge. A graph without multiple and loop edges is called a simple graph.
Value
any_loop() and any_multiple() return a logical scalar.
which_loop() and which_multiple() return a logical vector.
count_loops() returns a numeric scalar with the total number of loop edges.
count_multiple() returns a numeric vector.
Details
any_loop() decides whether the graph has any loop edges.
which_loop() decides whether the edges of the graph are loop edges.
count_loops() counts the total number of loop edges in the graph.
any_multiple() decides whether the graph has any multiple edges.
which_multiple() decides whether the edges of the graph are multiple
edges.
count_multiple() counts the multiplicity of each edge of a graph.
Note that the semantics for which_multiple() and count_multiple() is
different. which_multiple() gives TRUE for all occurrences of a
multiple edge except for one. I.e. if there are three i-j edges in the
graph then which_multiple() returns TRUE for only two of them while
count_multiple() returns ‘3’ for all three.
See the examples for getting rid of multiple edges while keeping their original multiplicity as an edge attribute.
See also
simplify() to eliminate loop and multiple edges.
Other structural.properties:
bfs(),
component_distribution(),
connect(),
constraint(),
coreness(),
degree(),
dfs(),
distance_table(),
edge_density(),
feedback_arc_set(),
feedback_vertex_set(),
girth(),
is_acyclic(),
is_dag(),
is_matching(),
k_shortest_paths(),
knn(),
reciprocity(),
subcomponent(),
subgraph(),
topo_sort(),
transitivity(),
unfold_tree(),
which_mutual()
Author
Gabor Csardi csardi.gabor@gmail.com
Related documentation in the C library
is_multiple(), has_multiple(), count_multiple(), is_loop(), has_loop(), count_loops().
Examples
# Loops
g <- make_graph(c(1, 1, 2, 2, 3, 3, 4, 5))
any_loop(g)
#> [1] TRUE
which_loop(g)
#> [1] TRUE TRUE TRUE FALSE
count_loops(g)
#> [1] 3
# Multiple edges
g <- sample_pa(10, m = 3, algorithm = "bag")
any_multiple(g)
#> [1] TRUE
which_multiple(g)
#> [1] FALSE TRUE TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE FALSE
#> [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE
#> [25] FALSE FALSE TRUE
count_multiple(g)
#> [1] 3 3 3 1 2 2 3 3 3 2 2 1 1 1 1 1 1 1 2 1 2 1 1 1 2 1 2
which_multiple(simplify(g))
#> [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE
all(count_multiple(simplify(g)) == 1)
#> [1] TRUE
# Direction of the edge is important
which_multiple(make_graph(c(1, 2, 2, 1)))
#> [1] FALSE FALSE
which_multiple(make_graph(c(1, 2, 2, 1), dir = FALSE))
#> [1] FALSE TRUE
# Remove multiple edges but keep multiplicity
g <- sample_pa(10, m = 3, algorithm = "bag")
E(g)$weight <- count_multiple(g)
g <- simplify(g, edge.attr.comb = list(weight = "min"))
any(which_multiple(g))
#> [1] FALSE
E(g)$weight
#> [1] 3 2 1 2 1 1 1 1 2 1 1 1 1 1 1 1 3 1 1 1