The girth of a graph is the length of the shortest circle in it.
Value
A named list with two components:
- girth
Integer constant, the girth of the graph, or 0 if the graph is acyclic.
- circle
Numeric vector with the vertex ids in the shortest circle.
Details
The current implementation works for undirected graphs only, directed graphs
are treated as undirected graphs. Loop edges and multiple edges are ignored.
If the graph is a forest (i.e. acyclic), then Inf is returned.
This implementation is based on Alon Itai and Michael Rodeh: Finding a minimum circuit in a graph Proceedings of the ninth annual ACM symposium on Theory of computing, 1-10, 1977. The first implementation of this function was done by Keith Briggs, thanks Keith.
References
Alon Itai and Michael Rodeh: Finding a minimum circuit in a graph Proceedings of the ninth annual ACM symposium on Theory of computing, 1-10, 1977
See also
Other structural.properties:
bfs(),
component_distribution(),
connect(),
constraint(),
coreness(),
degree(),
dfs(),
distance_table(),
edge_density(),
feedback_arc_set(),
feedback_vertex_set(),
is_acyclic(),
is_dag(),
is_matching(),
k_shortest_paths(),
knn(),
reciprocity(),
subcomponent(),
subgraph(),
topo_sort(),
transitivity(),
unfold_tree(),
which_multiple(),
which_mutual()
Graph cycles
feedback_arc_set(),
feedback_vertex_set(),
find_cycle(),
has_eulerian_path(),
is_acyclic(),
is_dag()
Author
Gabor Csardi csardi.gabor@gmail.com
Examples
# No circle in a tree
g <- make_tree(1000, 3)
girth(g)
#> $girth
#> [1] Inf
#>
#> $circle
#> + 0/1000 vertices, from 98dcd9b:
#>
# The worst case running time is for a ring
g <- make_ring(100)
girth(g)
#> $girth
#> [1] 100
#>
#> $circle
#> + 100/100 vertices, from 476cbdd:
#> [1] 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
#> [19] 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86
#> [37] 87 88 89 90 91 92 93 94 95 96 97 98 99 100 1 2 3 4
#> [55] 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
#> [73] 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
#> [91] 41 42 43 44 45 46 47 48 49 50
#>
# What about a random graph?
g <- sample_gnp(1000, 1 / 1000)
girth(g)
#> $girth
#> [1] 10
#>
#> $circle
#> + 10/1000 vertices, from 7a873db:
#> [1] 819 813 578 477 824 199 53 759 280 787
#>