crane.bipartite: Pertrubs the bipartite network with fixed node strength

In PadiLab/CRANE: Randomly perturbing networks with fixed strength

Description

Pertrubs the bipartite network with fixed node strength

Usage

crane.bipartite(df, alpha = 0.1, beta = 0, getAdj = F, randomStart = F)

Arguments

df	Adjacency Matrix or Edge list
alpha	alpha paramter perturbs each edge weights
beta	beta parameter perturbs the strength of each node. Set this to 0 if you want nodes to have node strength identical to the orignal network.
getAdj	TRUE = this will return adjacency matrix instead of edge list
randomStart	FALSE = initialize the first row with completely random edge weights.

Value

edge list

Examples

## Not run: 

# Using Edge list as input
elist=crane.bipartite(nonAng)
elist=crane.bipartite(nonAng,alpha=0.3)

# Using Edge list as input and Adjcency Matrix as output
adjMatrix=crane.bipartite(nonAng,alpha=0.1,getAdj=T)

# Using Edge list as input and Adjcency Matrix as output
A=elistToAdjMat(nonAng)
elist=crane.bipartite(A)


## End(Not run)

PadiLab/CRANE documentation built on Sept. 19, 2020, 8:28 a.m.