R/plotMyMultiplexMatrix.R

In GrossSBM/sbm: Stochastic Blockmodels

#' Plot the matrices corresponding to a Multiplex Network
#'
#' @param listSBM  : a list of objects representing the multiplex network (see)
#' @param memberships : a list of length equal to the number of Functional Groups providing the clusterings inside each group.
#' @param plotOptions : a list containing the options. See details.
#' @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
#'
#' @return a ggplot object corresponding to the plot
#' @export
#'
#' @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))
#'
#'
#'

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

  #########################
  myMSBMObject <- MultiplexSBM_fit$new(listSBM)
  ### TODO: better handle of membership!!! we should use an instance of MultipartiteSBM_sampler when ready
  if (!is.null(memberships)) myMSBMObject$probMemberships <- lapply(memberships, as_indicator)
  ordered <- ifelse(is.null(memberships), FALSE, TRUE)
  g <- myMSBMObject$plot(type='data', ordered = ordered, plotOptions)
  g
}