k_dist: Maximum difference between cumulative degree distribution

In memnet: Network Tools for Memory Research

Description

Determines the maximum difference between the cumulative degree distributions of two graphs

Usage

k_dist(adj_1, adj_2, weights_1 = NULL, weights_2 = NULL,
  mode_1 = "undirected", mode_2 = "undirected")

Arguments

adj_1	numeric matrix representing the adjacency matrix of graph 1.
adj_2	numeric matrix representing the adjacency matrix of graph 2.
weights_1, weights_2	numeric vector of edge weights for network 1 and 2, respectively. Optional.
mode_1, mode_2	character, either "directed" or "undirected", specifying whether network 1 and 2 should be interepeted as directed or undirected, respectively. Defaults to "undirected".

Value

Distance between cumulative degree distributions.

Examples

# get fluency data
data(animal_fluency)

# edge lists of fluency graphs
edge_list_1 = threshold_graph(animal_fluency[1:100])
edge_list_2 = threshold_graph(animal_fluency[101:200])

# get adjacency matrices
adj_1 = edg_to_adj(edge_list_1)
adj_2 = edg_to_adj(edge_list_2)

# get max degree distance
k_dist(adj_1, adj_2)

memnet documentation built on May 2, 2019, 9:35 a.m.