Generate a Sequence of Shuffled Networks and Track SVD/Modularity Evolution

This function generates a sequence of shuffled networks from an original graph by applying incremental shuffling steps. It tracks modularity and SVD entropy throughout the process, and stops when the change in these metrics falls below a specified tolerance threshold.

Usage

generate_shuffled_seq_tol(
  input_graph,
  delta = 10,
  max_iterations = 100,
  tolerance = 0.001,
  directed = TRUE,
  weighted = TRUE,
  modularity_func = cluster_infomap,
  shuffle_func = shuffle_network_deg
)

Arguments

input_graph

An igraph object or adjacency matrix (directed or undirected, weighted or unweighted).

delta

Integer. Number of link swaps per iteration (default: 10).

max_iterations

Integer. Maximum number of iterations until network metrics stabilize (default: 100).

tolerance

Numeric. Tolerance for metric stability - minimum change in modularity or SVD entropy (default: 1e-3).

directed

Logical. Whether the network is directed (default: TRUE).

weighted

Logical. Whether the network is weighted (default: TRUE).

modularity_func

Function. Function to calculate modularity (default: cluster_infomap).

shuffle_func

Function. Function to perform network shuffling (default: shuffle_network_deg).

Value

A list containing:

New_A

Shuffled adjacency matrix

Metrics

Data frame tracking metric evolution across iterations, including the original network