\name{clusterGraph-class} \docType{class} \alias{clusterGraph-class} \alias{clusterGraph-class} \alias{adj,clusterGraph,ANY-method} \alias{coerce,clusterGraph,matrix-method} \alias{connComp,clusterGraph-method} \alias{edges,clusterGraph,missing-method} \alias{edges,clusterGraph,character-method} \alias{edgeL,clusterGraph-method} \alias{edgeWeights,clusterGraph-method} \alias{edgeWeights,clusterGraph,ANY-method} \alias{nodes,clusterGraph-method} \alias{nodes<-,clusterGraph,character-method} \alias{numNodes,clusterGraph-method} \alias{show,clusterGraph-method} \title{Class "clusterGraph" } \description{ A cluster graph is a special sort of graph for clustered data. Each cluster forms a completely connected subgraph. Three are no edges between clusters.} \section{Objects from the Class}{ Objects can be created by calls of the form \code{new("clusterGraph", ...)}. } \section{Slots}{ \describe{ \item{\code{clusters}:}{Object of class \code{"list"} a list of the labels of the elements, one element of the list for each cluster. } } } \section{Extends}{ Class \code{"graph"}, directly. } \section{Methods}{ \describe{ \item{connComp}{\code{signature(object = "clusterGraph")}: find the connected components; simply the clusters in this case. } \item{acc}{\code{signature(object = "clusterGraph")}: find the accessible nodes from the supplied node. } \item{adj}{\code{signature(object = "clusterGraph")}: find the adjacent nodes to the supplied node. } \item{nodes}{\code{signature(object = "clusterGraph")}: return the nodes. } \item{nodes<-}{\code{signature(object="clusterGraph", value="character")}: replace the node names with the new labels given in \code{value}.} \item{numNodes}{\code{signature(object = "clusterGraph")}: return the number of nodes. } \item{edgeWeights}{Return a list of edge weights in a list format similar to the \code{edges} method.} \item{edgeL}{\code{signature(graph = "clusterGraph")}: A method for obtaining the edge list.} \item{coerce}{\code{signature(from = "clusterGraph", to = "matrix")}: Convert the \code{clusterGraph} to an adjacency matrix. Currently, weights are ignored. The conversion assumes no self-loops.} } } \author{R. Gentleman} \seealso{ \code{\link{graph-class}}, \code{\link{distGraph-class}} } \examples{ cG1 <- new("clusterGraph", clusters=list(a=c(1,2,3), b=c(4,5,6))) cG1 acc(cG1, c("1", "2")) } \keyword{classes}