plot.topicCorr: Plot a topic correlation graph

Description

Uses a topic correlation graph estimated by topicCorr and the igraph package to plot a network where nodes are topics and edges indicate a positive correlation.

Usage

# S3 method for topicCorr
plot(
  x,
  topics = NULL,
  vlabels = NULL,
  layout = NULL,
  vertex.color = "green",
  vertex.label.cex = 0.75,
  vertex.label.color = "black",
  vertex.size = NULL,
  ...
)

Arguments

x: A topicCorr model object.
topics: A vector of topics to include in the plot, defaults to all.
vlabels: A character vector of labels for the vertices. Defaults to "Topic #"
layout: The layout algorithm passed to the igraph package. It will choose layout.fruchterman.reingold by default. Note that to pass an alternate algorithm you should load the igraph package first.
vertex.color: Color of the vertices.
vertex.label.cex: Controls the size of the labels.
vertex.label.color: Controls the color of the labels.
vertex.size: Controls the sizes of the vertices, either NULL, a scalar or a vector of the same length as number of topics.
...: Additional parameters passed to plot.graph.adjacency

Details

Essentially a thin wrapper around the plotting functionality in the igraph package. See package vignette for more details.

References

Csardi G, Nepusz T: The igraph software package for complex network research, InterJournal, Complex Systems 1695. 2006. http://igraph.sf.net

Examples

Run this code


# \donttest{

#This function becomes more useful with larger numbers of topics.
#it is demonstrated here with a small model simply to show how the syntax works.
cormat <- topicCorr(gadarianFit)
plot(cormat)
# }

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