generate_random_chordal_graph {graphicalExtremes} | R Documentation |
Generate random graphs
Description
Generate random graphs with different structures. These do not follow well-defined distributions and are mostly meant for quickly generating test models.
Usage
generate_random_chordal_graph(
d,
cMin = 2,
cMax = 6,
sMin = 1,
sMax = 4,
block_graph = FALSE,
...
)
generate_random_connected_graph(
d,
m = NULL,
p = 2/(d + 1),
maxTries = 1000,
...
)
generate_random_tree(d)
generate_random_cactus(d, cMin = 2, cMax = 6)
Arguments
d |
Number of vertices in the graph |
cMin |
Minimal size of cliques/blocks (last one might be smaller if necessary) |
cMax |
Maximal size of cliques/blocks |
sMin |
Minimal size of separators |
sMax |
Maximal size of separators |
block_graph |
Force |
... |
Ignored, only allowed for compatibility |
m |
Number of edges in the graph (specify this or |
p |
Probability of each edge being in the graph (specify this or |
maxTries |
Maximum number of tries to produce a connected Erdoes-Renyi graph |
Details
generate_random_chordal_graph
generates a random chordal graph by starting with a (small) complete graph
and then adding new cliques until the specified size is reached.
The sizes of cliques and separators can be specified.
generate_random_connected_graph
first tries to generate an Erdoes-Renyi graph, if that fails, falls back
to producing a tree and adding random edges to that tree.
generate_random_cactus
generates a random cactus graph (mostly useful for benchmarking).
Value
An [igraph::graph
] object
See Also
Other example generation functions:
generate_random_Gamma()
,
generate_random_graphical_Gamma()
,
generate_random_integer_Gamma()
,
generate_random_model()
,
generate_random_spd_matrix()