Use this if you are using igraph from R
igraph community detection functions return their results as an object from
communities class. This manual page describes the operations of
membership(communities) ## S3 method for class 'communities' print(x, ...) ## S3 method for class 'communities' modularity(x, ...) ## S3 method for class 'communities' length(x) sizes(communities) algorithm(communities) merges(communities) crossing(communities, graph) code_len(communities) is_hierarchical(communities) ## S3 method for class 'communities' as.dendrogram(object, hang = -1, use.modularity = FALSE, ...) ## S3 method for class 'communities' as.hclust(x, hang = -1, use.modularity = FALSE, ...) as_phylo(x, ...) ## S3 method for class 'communities' as_phylo(x, use.modularity = FALSE, ...) cut_at(communities, no, steps) show_trace(communities) ## S3 method for class 'communities' plot( x, y, col = membership(x), mark.groups = communities(x), edge.color = c("black", "red")[crossing(x, y) + 1], ... )
An igraph graph object, corresponding to
Numeric scalar indicating how the height of leaves should be
computed from the heights of their parents; see
Logical scalar, whether to use the modularity values to define the height of the branches.
Integer scalar, the desired number of communities. If too low or
two high, then an error message is given. Exactly one of
The number of merge operations to perform to produce the
communities. Exactly one of
An igraph graph object, corresponding to the communities in
A vector of colors, in any format that is accepted by the regular R plotting methods. This vector gives the colors of the vertices explicitly.
A list of numeric vectors. The communities can be
highlighted using colored polygons. The groups for which the polygons are
drawn are given here. The default is to use the groups given by the
The colors of the edges. By default the edges within communities are colored green and other edges are red.
Numeric vector, one value for each vertex, the membership
vector of the community structure. Might also be
Numeric scalar or vector, the modularity value of the
community structure. It can also be
Community structure detection algorithms try to find dense subgraphs in directed or undirected graphs, by optimizing some criteria, and usually using heuristics.
igraph implements a number of community detection methods (see them below),
all of which return an object of the class
communities. Because the
community structure detection algorithms are different,
objects do not always have the same structure. Nevertheless, they have some
common operations, these are documented here.
prints a short summary.
length generic function call be called on
returns the number of communities.
sizes function returns the community sizes, in the order of their
membership gives the division of the vertices, into communities. It
returns a numeric vector, one value for each vertex, the id of its
community. Community ids start from one. Note that some algorithms calculate
the complete (or incomplete) hierarchical structure of the communities, and
not just a single partitioning. For these algorithms typically the
membership for the highest modularity value is returned, but see also the
manual pages of the individual algorithms.
communities is also the name of a function, that returns a list of
communities, each identified by their vertices. The vertices will have
symbolic names if the
add.vertex.names igraph option is set, and the
graph itself was named. Otherwise numeric vertex ids are used.
modularity gives the modularity score of the partitioning. (See
modularity.igraph for details. For algorithms that do not
result a single partitioning, the highest modularity value is returned.
algorithm gives the name of the algorithm that was used to calculate
the community structure.
crossing returns a logical vector, with one value for each edge,
ordered according to the edge ids. The value is
TRUE iff the edge
connects two different communities, according to the (best) membership
vector, as returned by
is_hierarchical checks whether a hierarchical algorithm was used to
find the community structure. Some functions only make sense for
hierarchical methods (e.g.
merges returns the merge matrix for hierarchical methods. An error
message is given, if a non-hierarchical method was used to find the
community structure. You can check this by calling
cut_at cuts the merge tree of a hierarchical community finding method,
at the desired place and returns a membership vector. The desired place can
be expressed as the desired number of communities or as the number of merge
steps to make. The function gives an error message, if called with a
as.dendrogram converts a hierarchical community structure to a
dendrogram object. It only works for hierarchical methods, and gives
an error message to others. See
dendrogram for details.
as.hclust is similar to
as.dendrogram, but converts a
hierarchical community structure to a
as_phylo converts a hierarchical community structure to a
object, you will need the
ape package for this.
show_trace works (currently) only for communities found by the leading
eigenvector method (
returns a character vector that gives the steps performed by the algorithm
while finding the communities.
code_len is defined for the InfoMAP method
cluster_infomap and returns the code length of the
It is possibly to call the
plot function on
objects. This will plot the graph (and uses
internally), with the communities shown. By default it colores the vertices
according to their communities, and also marks the vertex groups
corresponding to the communities. It passes additional arguments to
plot.igraph, please see that and also
igraph.plotting on how to change the plot.
communities object itself,
length returns an integer scalar.
sizes returns a numeric vector.
membership returns a numeric vector, one number for each vertex in
the graph that was the input of the community detection.
modularity returns a numeric scalar.
algorithm returns a character scalar.
crossing returns a logical vector.
is_hierarchical returns a logical scalar.
merges returns a two-column numeric matrix.
cut_at returns a numeric vector, the membership vector of the
as.dendrogram returns a
show_trace returns a character vector.
code_len returns a numeric scalar for communities found with the
InfoMAP method and
NULL for other methods.
communities objects returns
#' @author Gabor Csardi firstname.lastname@example.org
plot_dendrogram for plotting community structure
compare for comparing two community structures
on the same graph.
The different methods for finding communities, they all return a
karate <- make_graph("Zachary") wc <- cluster_walktrap(karate) modularity(wc) membership(wc) plot(wc, karate)