Description Usage Arguments Value Author(s) See Also Examples
Simulate a multi-layer weighted network with each layer sharing the same set of nodes but different nodes scores
1 | multilayernetworkSimulation(n, k, theta, L)
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n |
number of nodes in each layer of the network |
k |
number of nodes in the conserved module |
theta |
module node score follow the uniform distribution in range [theta,1] |
L |
number of layers |
a list containing all the layers, each as result object of networkSimulation
Dong Li, dxl466@cs.bham.ac.uk
1 2 3 4 5 6 | n = 100
k = 20
theta = 0.5
L = 5
cpl <- multilayernetworkSimulation(n,k,theta,L)
## No proper way to visualize it yet
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