build_motif_adjacency_matrix: Build a motif adjacency matrix

In motifcluster: Motif-Based Spectral Clustering of Weighted Directed Networks

Build a motif adjacency matrix

Description

Build a motif adjacency matrix from an adjacency matrix.

Usage

build_motif_adjacency_matrix(
  adj_mat,
  motif_name,
  motif_type = c("struc", "func"),
  mam_weight_type = c("unweighted", "mean", "poisson"),
  mam_method = c("sparse", "dense")
)

Arguments

adj_mat	Adjacency matrix from which to build the motif adjacency matrix.
motif_name	Motif used for the motif adjacency matrix.
motif_type	Type of motif adjacency matrix to build. One of "func" or "struc".
mam_weight_type	The weighting scheme to use. One of "unweighted", "mean" or "product".
mam_method	Which formulation to use. One of "dense" or "sparse". The sparse formulation avoids generating large dense matrices so tends to be faster for large sparse graphs.

Details

Entry (i, j) of a motif adjacency matrix is the sum of the weights of all motifs containing both nodes i and j. The motif is specified by name and the type of motif instance can be one of:

• Functional: motifs should appear as subgraphs.

• Structural: motifs should appear as induced subgraphs.

The weighting scheme can be one of:

• Unweighted: the weight of any motif instance is one.

• Mean: the weight of any motif instance is the mean of its edge weights.

• Product: the weight of any motif instance is the product of its edge weights.

Value

A motif adjacency matrix.

Examples

adj_mat <- matrix(c(1:9), nrow = 3)
build_motif_adjacency_matrix(adj_mat, "M1", "func", "mean")

motifcluster documentation built on Nov. 18, 2022, 9:06 a.m.