condorCluster | R Documentation |
This function performs community structure clustering using
the bipartite modularity described in
condorModularityMax
. This function uses a standard
(non-bipartite) community structure clustering of the uni-partite,
weighted projection of the original bipartite graph as an initial
guess for the bipartite modularity.
condorCluster(
condor.object,
cs.method = "LCS",
project = TRUE,
low.memory = FALSE,
deltaQmin = "default"
)
condor.object |
Output of make.condor.object. This function uses
|
cs.method |
is a string to specify which unipartite community
structure algorithm should be used for the seed clustering.
Options are |
project |
Provides options for initial seeding of the bipartite
modularity maximization.
If TRUE, the nodes in the first column of |
low.memory |
If TRUE, uses |
deltaQmin |
convergence parameter determining the minimum required increase
in the modularity for each iteration. Default is min(10^-4,1/(number of edges)),
with number of edges determined by |
condor.object
with condorModularityMax
output
included.
r = c(1,1,1,2,2,2,3,3,3,4,4);
b = c(1,2,3,1,2,4,2,3,4,3,4);
reds <- c("Alice","Sue","Janine","Mary")
blues <- c("Bob","John","Ed","Hank")
elist <- data.frame(red=reds[r],blue=blues[b])
condor.object <- createCondorObject(elist)
condor.object <- condorCluster(condor.object)
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