plotMyMultiplexMatrix function

Plot the matrices corresponding to a Multiplex Network

plotMyMultiplexMatrix(listSBM, memberships = NULL, plotOptions = list())

Arguments

• listSBM: : a list of objects representing the multiplex network (see)
• memberships: : a list of length equal to the number of Functional Groups providing the clusterings inside each group.
• plotOptions: : a list containing the options. See details.

Returns

a ggplot object corresponding to the plot

Details

plotOptions is a list containing the following items

• "normalized": Boolean. TRUE if the various matrices are presented in the same scale (between O and 1). FALSE otherwise. Default value FALSE
• "compact": Boolean. Default value is TRUE if you ask for the matrices to be transposed to have a more compact view
• "legend": Boolean. Set TRUE if you want to see the legend. Default value is FALSE
• "legend.title": Boolean. Set TRUE if you want to print the title of the legend. Default value is FALSE
• "legend.position": Position of the legend. Possible values are 'bottom', 'top','left,'right'. Default value is 'bottom'
• "nodeNames": Set true if the node Names must be plotted. Default value is FALSE
• "line.color": The color of the lines to separate groups. Default value is red
• "line.width": Width of the lines to separate groups. Default value is NULL, automatically chosen
• "title": Title of the plot. Default value is NULL

Examples

Nnodes <- c(40,30)
blockProp <- list(c(.4,.6),c(0.5,0.5))
nbLayers <- 2
connectParam <- list(list(mean=matrix(rbeta(4,.5,.5),2,2)),list(mean=matrix(rexp(4,.5),2,2)))
names(connectParam) <- c('Read','Score')
model <- c("bernoulli","poisson")
type <- "bipartite"
mySampleMultiplexSBM <-
 sampleMultiplexSBM(
   nbNodes = Nnodes,
   blockProp = blockProp,
   nbLayers = nbLayers,
   connectParam = connectParam,
   model=model,
   dimLabels =  c('readers','books'),
   type=type)
listNet <- mySampleMultiplexSBM$listSBM
names(listNet) <- c("Read","Affinity")
plotMyMultiplexMatrix(listNet,plotOptions=list(legend = TRUE))