Description Usage Arguments Value Author(s) References Examples
This function returns the number of edges node(s) contain in each community.
1 | numberEdgesIn(x, clusterids = 1:x$numbers[3], nodes)
|
x |
An object of class |
clusterids |
An integer vector of community IDs. Defaults to all communities. |
nodes |
A character vector specifying node(s) for which edge membership should be returned. |
A named list of named integer vectors specifying the number of edges in each community a node belongs in. Names of the integer vectors are community IDs, and names of the list are node names.
Alex T. Kalinka alex.t.kalinka@gmail.com
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.
1 2 3 4 5 6 | ## Generate graph and extract OCG communities.
g <- swiss[,3:4]
oc <- getOCG.clusters(g)
## Get edges from community 1.
numberEdgesIn(oc, nodes = 1)
|
Loading required package: igraph
Attaching package: 'igraph'
The following objects are masked from 'package:stats':
decompose, spectrum
The following object is masked from 'package:base':
union
Loading required package: RColorBrewer
Welcome to linkcomm version 1.0-11
For a step-by-step guide to using linkcomm functions:
> vignette(topic = "linkcomm", package = "linkcomm")
To run an interactive demo:
> demo(topic = "linkcomm", package = "linkcomm")
To cite, see:
> citation("linkcomm")
NOTE: To use linkcomm, you require read and write permissions in the current directory (see: help("getwd"), help("setwd"))
Calculating Initial class System....Done
Nb. of classes 21
Nb. of edges not within the classes 11
Number of initial classes 21
Running....
Remaining classes: 20 of 21
Remaining classes: 10 of 21
Remaining classes: None
Reading OCG data...
Extracting cluster sizes... 5%
Extracting cluster sizes... 11%
Extracting cluster sizes... 17%
Extracting cluster sizes... 23%
Extracting cluster sizes... 29%
Extracting cluster sizes... 35%
Extracting cluster sizes... 41%
Extracting cluster sizes... 47%
Extracting cluster sizes... 52%
Extracting cluster sizes... 58%
Extracting cluster sizes... 64%
Extracting cluster sizes... 70%
Extracting cluster sizes... 76%
Extracting cluster sizes... 82%
Extracting cluster sizes... 88%
Extracting cluster sizes... 94%
Extracting cluster sizes... 100%
Getting node community edge density...100%
$`1`
1
1
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