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.
Related documentation in the C library
is_multiple, edges, get_eids, vcount, ecount, has_multiple, count_multiple, is_loop, has_loop, count_loops
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
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