Sparsify.matrix-methods: Sparsifying the graph

In NetPreProc: Network Pre-Processing and Normalization

Sparsifying the graph

Description

Methods to sparsify a network matrix. By this method a general threshold is et such that you a minimum of k edges is guranteed for each node

Usage

Sparsify.matrix(W, k=1)

Arguments

W	an object representing the graph to be sparsified
k	the number of guaranteed edges for each node (def.=1)

Value

The sparsified adjacency matrix of the network

Methods

signature(W = "graph")

an object of the virtual class graph (hence including objects of class graphAM and graphNEL from the package graph)

signature(W = "matrix")

a matrix representing the adjacency matrix of the graph

Examples

library(bionetdata);
data(FIN.data);
W <- Laplacian.norm(as.matrix(FIN.data));
# sparsification by maintaining at least one neighbour per node 
W1 <- Sparsify.matrix(W);
# sparsification by maintaining at least 20 neighbours per node (if any)
W20 <- Sparsify.matrix(W, k=20);

NetPreProc documentation built on Sept. 19, 2022, 5:06 p.m.