MultiplexNetwork_principle.R
In sbm: Stochastic Blockmodels

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup, message=FALSE, warning=FALSE--------------------------------------
library(sbm)

## ----param all----------------------------------------------------------------
nbLayers <- 2

## ----Independant Poisson bernoulli--------------------------------------------
Nnodes <- 40
blockProp <- c(.4,.6)
set.seed(1)
connectParam <- list(list(mean=matrix(rbeta(4,.5,.5),2,2)),list(mean=matrix(rexp(4,.5),2,2)))
model <- c("bernoulli","poisson")
type <- "directed"
mySampleMultiplexSBM_PB <-
   sampleMultiplexSBM(
   nbNodes = Nnodes,
    blockProp = blockProp,
   nbLayers = nbLayers,
   connectParam = connectParam,
   model=model,
   dimLabels = c('Individuals'), # generic name of the nodes
   type=type,
   seed = 1)
listSBM_PB <- mySampleMultiplexSBM_PB$listSBM
names(listSBM_PB) <- c("Bernoulli","Poisson")  
plotMyMultiplexMatrix(listSBM_PB)

## -----------------------------------------------------------------------------
listSBM_PB

## -----------------------------------------------------------------------------
blockProp <- list(c(0.3, 0.3, 0.4), c(0.5, 0.5))
Q <- sapply(blockProp, function(p) length(p))
nbNodes <- c(80, 30)
connectParam <- list()
connectParam$mu <- vector("list", nbLayers)
connectParam$mu[[1]] <- matrix(0.1, Q[1], Q[2]) + matrix(c(1, 1, 1, 0,
    1, 0), Q[1], Q[2])
connectParam$mu[[2]] <- matrix(-2, Q[1], Q[2]) + matrix(c(1, 3, 2, 1, 2,
    3), Q[1], Q[2])
connectParam$Sigma <- matrix(c(2, 1, 0.1, 4), nbLayers, nbLayers)
model <- rep("gaussian", 2)
mySampleMultiplexSBM_GG <-
  sampleMultiplexSBM(
     nbNodes = nbNodes,
     blockProp = blockProp,
     nbLayers = nbLayers,
     connectParam = connectParam,
     model = model,
     type = "bipartite",
     dependent = TRUE,
     dimLabels = c('row', 'col'),
     seed = 1)
listSBM_GG <- mySampleMultiplexSBM_GG$listSBM
plotMyMultiplexMatrix(listSBM_GG)

## -----------------------------------------------------------------------------
## MultiplexSBM Bernoulli with dependence
Q <- 2
set.seed(94)
P00 <- matrix(runif(Q * Q), Q, Q)
P10 <- matrix(runif(Q * Q), Q, Q)
P01 <- matrix(runif(Q * Q), Q, Q)
P11 <- matrix(runif(Q * Q), Q, Q)
SumP <- P00 + P10 + P01 + P11
P00 <- P00/SumP
P01 <- P01/SumP
P10 <- P10/SumP
P11 <- P11/SumP
connectParam <- list()
connectParam$prob00 <- P00
connectParam$prob01 <- P01
connectParam$prob10 <- P10
connectParam$prob11 <- P11
model <- rep("bernoulli", 2)
type <- "directed"
nbLayers <- 2
Nnodes <- 40
blockProp <- c(0.6, 0.4)
mySampleMultiplexSBM <-
   sampleMultiplexSBM(
     nbNodes = Nnodes,
     blockProp = blockProp,
     nbLayers = nbLayers,
     connectParam = connectParam,
     model = model,
     type = type,
     dependent = TRUE,
     seed = 1)
listSBM_BB <- mySampleMultiplexSBM$listSBM
plotMyMultiplexMatrix(listSBM_BB)

## ---- echo = FALSE, eval = TRUE-----------------------------------------------
load(file = 'resVignetteSimuMultiplex.rda')

## ---- echo = TRUE, eval = FALSE-----------------------------------------------
#  res_PB <- estimateMultiplexSBM(listSBM_PB)
#  res_PB$storedModels

## ---- echo = FALSE, eval = TRUE-----------------------------------------------
res_PB$storedModels

## ---- echo = TRUE, eval = TRUE------------------------------------------------
plot(res_PB)

## ---- echo = TRUE, eval = TRUE------------------------------------------------
plot(res_PB, type = 'expected')

## -----------------------------------------------------------------------------
All <- plotAlluvial(list(simulated  = mySampleMultiplexSBM_PB$memberships$Individuals, estim = res_PB$memberships$Individuals))
All

## ---- echo = TRUE, eval = FALSE-----------------------------------------------
#  res_GG <- estimateMultiplexSBM(listSBM_GG, dependent = TRUE, estimOptions = list(plot = FALSE, verbosity = 0 ))
#  res_GG$storedModels

## ---- echo = FALSE, eval = TRUE-----------------------------------------------
res_GG$storedModels

## ---- echo = TRUE, eval = TRUE------------------------------------------------
plot(res_GG)

## ---- echo = TRUE, eval = FALSE-----------------------------------------------
#  res_BB <- estimateMultiplexSBM(listSBM_BB,dependent =  TRUE, estimOptions = list(plot = FALSE, verbosity = 0 ))
#  res_BB$storedModels

## ---- echo = FALSE, eval = TRUE-----------------------------------------------
res_BB$storedModels