migraph (version 0.12.1)

generate: Make networks with a stochastic element

Description

These functions are similar to the create_* functions, but include some element of randomisation. They are particularly useful for creating a distribution of networks for exploring or testing network properties.

Usage

generate_random(n, p = 0.5, directed = FALSE, with_attr = TRUE)
generate_smallworld(n, p = 0.05, width = 2, directed = FALSE)
generate_scalefree(n, p = 1, directed = FALSE)
generate_permutation(object, with_attr = TRUE)

Value

By default an igraph object is returned, but this can be coerced into other types of objects using as_matrix(), as_tidygraph(), or as_network().

Arguments

n

Given:

• A single integer, e.g. n = 10, a one-mode network will be created.

• A vector of two integers, e.g. n = c(5,10), a two-mode network will be created.

• A migraph-compatible object, a network of the same dimensions will be created.

p

Proportion of possible ties in the network that are realised or, if integer greater than 1, the number of ties in the network.

directed

Whether to generate network as directed. By default FALSE.

with_attr

Logical whether any attributes of the object should be retained. By default TRUE.

width

Integer specifying the width or breadth of the ring or branches.

object

An object of a migraph-consistent class:

• matrix (adjacency or incidence) from {base} R

• edgelist, a data frame from {base} R or tibble from {tibble}

• igraph, from the {igraph} package

• network, from the {network} package

• tbl_graph, from the {tidygraph} package

Functions

• generate_random(): Generates a random network with a particular probability.

• generate_smallworld(): Generates a small-world structure following the lattice rewiring model.

• generate_scalefree(): Generates a scale-free structure following the preferential attachment model.

• generate_permutation(): Generates a permutation of the original network using a Fisher-Yates shuffle on both the rows and columns (for a one-mode network) or on each of the rows and columns (for a two-mode network).

References

Erdős, Paul, and Alfréd Rényi. (1959). "On Random Graphs I" Publicationes Mathematicae. 6: 290–297.

Watts, Duncan J., and Steven H. Strogatz. 1998. “Collective Dynamics of ‘Small-World’ Networks.” Nature 393(6684):440–42. tools:::Rd_expr_doi("10.1038/30918").

Barabási, Albert-László, and Réka Albert. 1999. “Emergence of Scaling in Random Networks.” Science 286(5439):509–12. tools:::Rd_expr_doi("10.1126/science.286.5439.509").

See Also

as

Other makes: create, read

Examples

autographr(generate_random(12, 0.4)) +
autographr(generate_random(c(6, 6), 0.4))
autographr(generate_smallworld(12, 0.025)) +
autographr(generate_smallworld(12, 0.25)) +
autographr(generate_smallworld(c(6,6), 0.025))
autographr(generate_scalefree(12, 0.25)) +
autographr(generate_scalefree(12, 1.25))
autographr(generate_scalefree(c(12,6), 0.25)) /
autographr(generate_scalefree(c(12,6), 1.25))
autographr(mpn_elite_usa_advice) +
autographr(generate_permutation(mpn_elite_usa_advice))