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.
Arguments
- graph
The input graph.
- eids
The edges to which the query is restricted. By default this is all edges in the graph.
Value
any_loop() and any_multiple() return a logical scalar.
which_loop() and which_multiple() return a logical vector.
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.
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(),
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
# Multiple edges
g <- sample_pa(10, m = 3, algorithm = "bag")
any_multiple(g)
#> [1] TRUE
which_multiple(g)
#> [1] FALSE TRUE TRUE FALSE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE
#> [13] FALSE TRUE TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE
#> [25] FALSE TRUE TRUE
count_multiple(g)
#> [1] 3 3 3 2 2 1 3 3 3 3 3 3 3 3 3 2 1 2 3 3 3 1 1 1 3 3 3
which_multiple(simplify(g))
#> [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> [13] 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 3 2 1 3 1 1 1 2 1 1 1 1 2 1 2 1