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.

## Usage

``````which_multiple(graph, eids = E(graph))

any_multiple(graph)

count_multiple(graph, eids = E(graph))

which_loop(graph, eids = E(graph))

any_loop(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.

`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

``````