This function allows the user to extract link communities by cutting the dendrogram at a specified height.

newLinkCommsAt(x, cutat = 0.5)

Arguments

x

An object of class linkcomm.

cutat

A numerical value indicating the height at which to cut the dendrogram. Defaults to 0.5.

Details

Users may wish to explore the communities formed by cutting the dendrogram higher or lower than the maximum partition density height. After cutting at a new height, the pdmax value in the resulting object will be set to the cutat value used by the user, only to distinguish the new object from the one generated by the link communities algorithm (the global partition density maximum does not change).

Value

An object of class linkcomm, which is a list containing the following components:

numbers

An integer vector with the number of edges, nodes, and communities.

hclust

An object of class hclust, which contains information about the hierarchical clustering of links.

pdmax

A numerical value indicating the height of the dendrogram at which the partition density is maximised.

pdens

A numerical matrix with 2 columns; the first is the heights at which clusters appear and the second is the partition density.

nodeclusters

A data frame consisting of 2 columns; the first contains node names, and the second contains single community IDs for each node. All communities and their nodes are represented, but not necessarily all nodes.

clusters

A list of integer vectors containing the link IDs that belong to each community. Community IDs are the numerical position of the communities in the list.

edges

A data frame with 3 columns; the first two contain nodes that interact with each other, and the third is an integer vector of community IDs indicating community membership for each link.

numclusters

A named integer vector. Names are node names and integer values are the number of communities to which each node belongs.

clustsizes

A named integer vector. Names are community IDs and integer values indicate the number of nodes that belong in each community.

igraph

An object of class igraph. The network is represented here as an igraph object.

edgelist

A character matrix with 2 columns containing the nodes that interact with each other.

directed

Logical indicating whether the network is directed.

bipartite

Logical indicating whether the network is bipartite.

References

Kalinka, A.T. and Tomancak, P. (2011). linkcomm: an R package for the generation, visualization, and analysis of link communities in networks of arbitrary size and type. Bioinformatics 27, 2011-2012.

Author

Alex T. Kalinka alex.t.kalinka@gmail.com

Note

After cutting at a new height, the pdmax value in the resulting object will be set to the cutat value used by the user, only to distinguish the new object from the one generated by the link communities algorithm (the global partition density maximum does not change).

See also

Examples

## Generate graph and extract link communities. g <- swiss[,3:4] lc <- getLinkCommunities(g)
#> Checking for loops and duplicate edges... 0.000% Checking for loops and duplicate edges... 2.174% Checking for loops and duplicate edges... 4.348% Checking for loops and duplicate edges... 6.522% Checking for loops and duplicate edges... 8.696% Checking for loops and duplicate edges... 10.870% Checking for loops and duplicate edges... 13.043% Checking for loops and duplicate edges... 15.217% Checking for loops and duplicate edges... 17.391% Checking for loops and duplicate edges... 19.565% Checking for loops and duplicate edges... 21.739% Checking for loops and duplicate edges... 23.913% Checking for loops and duplicate edges... 26.087% Checking for loops and duplicate edges... 28.261% Checking for loops and duplicate edges... 30.435% Checking for loops and duplicate edges... 32.609% Checking for loops and duplicate edges... 34.783% Checking for loops and duplicate edges... 36.957% Checking for loops and duplicate edges... 39.130% Checking for loops and duplicate edges... 41.304% Checking for loops and duplicate edges... 43.478% Checking for loops and duplicate edges... 45.652% Checking for loops and duplicate edges... 47.826% Checking for loops and duplicate edges... 50.000% Checking for loops and duplicate edges... 52.174% Checking for loops and duplicate edges... 54.348% Checking for loops and duplicate edges... 56.522% Checking for loops and duplicate edges... 58.696% Checking for loops and duplicate edges... 60.870% Checking for loops and duplicate edges... 63.043% Checking for loops and duplicate edges... 65.217% Checking for loops and duplicate edges... 67.391% Checking for loops and duplicate edges... 69.565% Checking for loops and duplicate edges... 71.739% Checking for loops and duplicate edges... 73.913% Checking for loops and duplicate edges... 76.087% Checking for loops and duplicate edges... 78.261% Checking for loops and duplicate edges... 80.435% Checking for loops and duplicate edges... 82.609% Checking for loops and duplicate edges... 84.783% Checking for loops and duplicate edges... 86.957% Checking for loops and duplicate edges... 89.130% Checking for loops and duplicate edges... 91.304% Checking for loops and duplicate edges... 93.478% Checking for loops and duplicate edges... 95.652% Checking for loops and duplicate edges... 97.826% Checking for loops and duplicate edges... 100.000% #> Found and removed 4 loop(s) #> Found and removed 2 duplicate edge(s) #> Calculating edge similarities for 41 edges... 0.00% Calculating edge similarities for 41 edges... 2.56% Calculating edge similarities for 41 edges... 5.13% Calculating edge similarities for 41 edges... 7.69% Calculating edge similarities for 41 edges... 10.26% Calculating edge similarities for 41 edges... 12.82% Calculating edge similarities for 41 edges... 15.38% Calculating edge similarities for 41 edges... 17.95% Calculating edge similarities for 41 edges... 20.51% Calculating edge similarities for 41 edges... 23.08% Calculating edge similarities for 41 edges... 25.64% Calculating edge similarities for 41 edges... 28.21% Calculating edge similarities for 41 edges... 30.77% Calculating edge similarities for 41 edges... 33.33% Calculating edge similarities for 41 edges... 35.90% Calculating edge similarities for 41 edges... 38.46% Calculating edge similarities for 41 edges... 41.03% Calculating edge similarities for 41 edges... 43.59% Calculating edge similarities for 41 edges... 46.15% Calculating edge similarities for 41 edges... 48.72% Calculating edge similarities for 41 edges... 51.28% Calculating edge similarities for 41 edges... 53.85% Calculating edge similarities for 41 edges... 56.41% Calculating edge similarities for 41 edges... 58.97% Calculating edge similarities for 41 edges... 61.54% Calculating edge similarities for 41 edges... 64.10% Calculating edge similarities for 41 edges... 66.67% Calculating edge similarities for 41 edges... 69.23% Calculating edge similarities for 41 edges... 71.79% Calculating edge similarities for 41 edges... 74.36% Calculating edge similarities for 41 edges... 76.92% Calculating edge similarities for 41 edges... 79.49% Calculating edge similarities for 41 edges... 82.05% Calculating edge similarities for 41 edges... 84.62% Calculating edge similarities for 41 edges... 87.18% Calculating edge similarities for 41 edges... 89.74% Calculating edge similarities for 41 edges... 92.31% Calculating edge similarities for 41 edges... 94.87% Calculating edge similarities for 41 edges... 97.44% Calculating edge similarities for 41 edges... 100.00% #> Hierarchical clustering of edges... #> Calculating link densities... 0.00% Calculating link densities... 2.56% Calculating link densities... 5.13% Calculating link densities... 7.69% Calculating link densities... 10.26% Calculating link densities... 12.82% Calculating link densities... 15.38% Calculating link densities... 17.95% Calculating link densities... 20.51% Calculating link densities... 23.08% Calculating link densities... 25.64% Calculating link densities... 28.21% Calculating link densities... 30.77% Calculating link densities... 33.33% Calculating link densities... 35.90% Calculating link densities... 38.46% Calculating link densities... 41.03% Calculating link densities... 43.59% Calculating link densities... 46.15% Calculating link densities... 48.72% Calculating link densities... 51.28% Calculating link densities... 53.85% Calculating link densities... 56.41% Calculating link densities... 58.97% Calculating link densities... 61.54% Calculating link densities... 64.10% Calculating link densities... 66.67% Calculating link densities... 69.23% Calculating link densities... 71.79% Calculating link densities... 74.36% Calculating link densities... 76.92% Calculating link densities... 79.49% Calculating link densities... 82.05% Calculating link densities... 84.62% Calculating link densities... 87.18% Calculating link densities... 89.74% Calculating link densities... 92.31% Calculating link densities... 94.87% Calculating link densities... 97.44% Calculating link densities... 100.00% #> Maximum partition density = 0.2601626 #> Finishing up...1/4... 12% Finishing up...1/4... 25% Finishing up...1/4... 37% Finishing up...1/4... 50% Finishing up...1/4... 62% Finishing up...1/4... 75% Finishing up...1/4... 87% Finishing up...1/4... 100% Finishing up...2/4... 12% Finishing up...2/4... 25% Finishing up...2/4... 37% Finishing up...2/4... 50% Finishing up...2/4... 62% Finishing up...2/4... 75% Finishing up...2/4... 87% Finishing up...2/4... 100% Finishing up...3/4... 12% Finishing up...3/4... 25% Finishing up...3/4... 37% Finishing up...3/4... 50% Finishing up...3/4... 62% Finishing up...3/4... 75% Finishing up...3/4... 87% Finishing up...3/4... 100% Finishing up...4/4... 0.00% Finishing up...4/4... 4.76% Finishing up...4/4... 9.52% Finishing up...4/4... 14.29% Finishing up...4/4... 19.05% Finishing up...4/4... 23.81% Finishing up...4/4... 28.57% Finishing up...4/4... 33.33% Finishing up...4/4... 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## User defined communities. lc2 <- newLinkCommsAt(lc, cutat = 0.8)
#> Extracting clusters... 0.00% Extracting clusters... 5.26% Extracting clusters... 10.53% Extracting clusters... 15.79% Extracting clusters... 21.05% Extracting clusters... 26.32% Extracting clusters... 31.58% Extracting clusters... 36.84% Extracting clusters... 42.11% Extracting clusters... 47.37% Extracting clusters... 52.63% Extracting clusters... 57.89% Extracting clusters... 63.16% Extracting clusters... 68.42% Extracting clusters... 73.68% Extracting clusters... 78.95% Extracting clusters... 84.21% Extracting clusters... 89.47% Extracting clusters... 94.74% Extracting clusters... 100.00% #> Finishing up...1/3... 10% Finishing up...1/3... 20% Finishing up...1/3... 30% Finishing up...1/3... 40% Finishing up...1/3... 50% Finishing up...1/3... 60% Finishing up...1/3... 70% Finishing up...1/3... 80% Finishing up...1/3... 90% Finishing up...1/3... 100% Finishing up...2/3... 10% Finishing up...2/3... 20% Finishing up...2/3... 30% Finishing up...2/3... 40% Finishing up...2/3... 50% Finishing up...2/3... 60% Finishing up...2/3... 70% Finishing up...2/3... 80% Finishing up...2/3... 90% Finishing up...2/3... 100% Finishing up...3/3... 4% Finishing up...3/3... 9% Finishing up...3/3... 13% Finishing up...3/3... 18% Finishing up...3/3... 22% Finishing up...3/3... 27% Finishing up...3/3... 31% Finishing up...3/3... 36% Finishing up...3/3... 40% Finishing up...3/3... 45% Finishing up...3/3... 50% Finishing up...3/3... 54% Finishing up...3/3... 59% Finishing up...3/3... 63% Finishing up...3/3... 68% Finishing up...3/3... 72% Finishing up...3/3... 77% Finishing up...3/3... 81% Finishing up...3/3... 86% Finishing up...3/3... 90% Finishing up...3/3... 95% Finishing up...3/3... 100%