makeGraph.Rd
Creates an igraph object from a square input correlation matrix - only positive correlations are used. Based on the graph.adjacency function of igraph. gplot is helpful for visualization.
makeGraph( mat, graphdensity = 1, communityMethod = NA, getEfficiency = FALSE, inverseValuesAsWeights = FALSE )
mat | input matrix |
---|---|
graphdensity | fraction of edges to keep |
communityMethod | see igraph's community detection |
getEfficiency | boolean, this is slow to compute |
inverseValuesAsWeights | if TRUE, high correlations produce small
edge weights. This detail is important when using igraph algorithms as
different methods use weights in different ways. See igraph for its
|
a named list is output including the graph object, adjacency matrix and several graph metrics
#> [1] "Need igraph package"mat <- matrix( c( 1, 0.5, 0.2, -0.1, 1, 0.3, -0.2, 0.6, 1 ) , ncol= 3 ) gobj<-makeGraph( mat , 0.5 )#> [1] "Need igraph package"# gplot( gobj$adjacencyMatrix ) # need sna library for this