hypergraph_from_incidence_matrix: Hypergraph construction.

In HyperG: Hypergraphs in R

Description

Construct a hypergraph from a collection of hyper-edges.

Usage

hypergraph_from_incidence_matrix(incidence_matrix)
hypergraph_from_edgelist(x,v)
hypergraph_from_membership(x)
hypergraph_from_fuzzy_clustering(z,threshold)
hypergraph_from_spectral_clustering(g,m,fuzzy=FALSE,threshold,...)

Arguments

incidence_matrix	an sxn binary matrix corresponding to the s hyper-edges on n vertices.
x	a list of hyper-edges, or a vector corresponding to which hyper-edge each node is in.
z	a matrix of probabilities that is nxc where c is the number of clusters.
v	optional vector of node names.
g	a graph. Only used if m is missing.
m	a communities object. See communities in the igraph package.
fuzzy	logical.
threshold	threshold on the probabilities if fuzzy is true. If not given, it defaults to the inverse of the number of communities.
...	arguments passed to cluster_spectral if g is given and m is given.

Details

An edgelist is a list of hyper-edges. An incidence matrix is a binary matrix that is hsize(g)xhorder(h). A membership vector is the vector of node membership returned from a community detection or clustering algorithm. A hypergraph constructed from a membership vector has a disconnected component for each hyper-edge.

Value

a hypergraph.

Author(s)

David J. Marchette [e-mail]

See Also

cluster_spectral, communities.

Examples

   h <- hypergraph_from_edgelist(list(1:4,3:6))

HyperG documentation built on March 4, 2021, 5:06 p.m.