This set of graph creation algorithms simulate the topology by, in some way, connecting subgraphs. The nature of their algorithm is described in detail at the linked igraph documentation.

play_blocks(n, size_blocks, p_between, directed = TRUE, loops = FALSE)

play_blocks_hierarchy(n, size_blocks, rho, p_within, p_between)

play_islands(n_islands, size_islands, p_within, m_between)

play_smallworld(
n_dim,
dim_size,
order,
p_rewire,
loops = FALSE,
multiple = FALSE
)

## Arguments

n

The number of nodes in the graph.

size_blocks

The number of vertices in each block

p_between, p_within

The probability of edges within and between groups/blocks

directed

Should the resulting graph be directed

loops

Are loop edges allowed

rho

The fraction of vertices per cluster

n_islands

The number of densely connected islands

size_islands

The number of nodes in each island

m_between

The number of edges between groups/islands

n_dim, dim_size

The dimension and size of the starting lattice

order

The neighborhood size to create connections from

p_rewire

The rewiring probability of edges

multiple

Are multiple edges allowed

## Value

A tbl_graph object

## Functions

• play_blocks(): Create graphs by sampling from stochastic block model. See igraph::sample_sbm()

• play_blocks_hierarchy(): Create graphs by sampling from the hierarchical stochastic block model. See igraph::sample_hierarchical_sbm()

• play_islands(): Create graphs with fixed size and edge probability of subgraphs as well as fixed edge count between subgraphs. See igraph::sample_islands()

• play_smallworld(): Create graphs based on the Watts-Strogatz small- world model. See igraph::sample_smallworld()

Other graph games: evolution_games, sampling_games, type_games
plot(play_islands(4, 10, 0.7, 3))