Nothing
### This file gives a prob extend initialization.
initial.em.gbd.prob.extend <- function(PARAM){
N.all <- PARAM$N.all
N.gbd <- PARAM$N.gbd
K <- PARAM$K
p.X <- PARAM$p.X
### For the 1st cluster.
gcenter.X <- rep(0, p.X)
gcenter.PV <- 0
### For the rests.
id.PV.gbd <- which(.MixfMRIEnv$PV.gbd < PARAM$max.PV)
if(length_gbd(id.PV.gbd) < PARAM$min.N.CLASS * (K - 1)){
### Avoid too tiny subset or too large K.
stop("K may be too large.")
}
tmp.X.gbd <- .MixfMRIEnv$qnorm.X.gbd[id.PV.gbd,]
tmp.PV.gbd <- .MixfMRIEnv$qnorm.PV.gbd[id.PV.gbd]
### Get comm size and rank if MPI is loaded.
if(.MixfMRIEnv$MPI.gbd){
COMM.SIZE <- pbdMPI::spmd.comm.size()
COMM.RANK <- pbdMPI::spmd.comm.rank()
### Stupid but work.
all.tmp.X.gbd <- pbdMPI::gather(tmp.X.gbd)
all.tmp.PV.gbd <- pbdMPI::gather(tmp.PV.gbd)
if(COMM.RANK == 0){
all.tmp.X.gbd <- do.call("rbind", all.tmp.X.gbd)
all.tmp.PV.gbd <- do.call("c", all.tmp.PV.gbd)
prob.center <- all.tmp.PV.gbd^2
prob.center <- prob.center / sum(prob.center)
}
} else{
prob.center <- tmp.PV.gbd^2
prob.center <- prob.center / sum(prob.center)
}
### Random centering K - 1 points.
iter <- 0
repeat{
if(.MixfMRIEnv$MPI.gbd){
if(COMM.RANK == 0){
id.center <- sample(1:length(prob.center), K - 1, prob = prob.center)
center.X <- matrix(all.tmp.X.gbd[id.center,], ncol = p.X)
center.X <- pbdMPI::spmd.bcast.double(center.X)
center.PV <- all.tmp.PV.gbd[id.center]
center.PV <- pbdMPI::spmd.bcast.double(center.PV)
} else{
center.X <- pbdMPI::spmd.bcast.double(rep(0.0, (K - 1) * p.X))
center.X <- matrix(center.X, ncol = p.X)
center.PV <- pbdMPI::spmd.bcast.double(rep(0.0, K - 1))
}
### Gather all centers and pv's.
center.X <- matrix(rbind(gcenter.X, center.X), ncol = p.X)
center.PV <- c(gcenter.PV, center.PV)
} else{
id.center <- sample(1:length(prob.center), K - 1, prob = prob.center)
center.X <- matrix(rbind(gcenter.X, tmp.X.gbd[id.center,]), ncol = p.X)
center.PV <- c(gcenter.PV, tmp.PV.gbd[id.center])
}
### Classifying to the closest center.
CLASS.gbd <- rep(1, N.gbd)
tmp.dist <- NULL
for(i.k in 1:K){
if(PARAM$p.X > 0){
tmp <- rowMeans(W.plus.y(tmp.X.gbd, -center.X[i.k,],
length(id.PV.gbd), p.X)^2)
} else{
tmp <- 0
}
tmp <- tmp + (tmp.PV.gbd - center.PV[i.k])^2
tmp.dist <- cbind(tmp.dist, tmp)
}
CLASS.gbd[id.PV.gbd] <- apply(tmp.dist, 1, which.min)
check <- all(tabulate.gbd(CLASS.gbd, nbins = K) > PARAM$min.N.CLASS)
if(.MixfMRIEnv$CONTROL$debug > 2){
tmp <- tabulate.gbd(CLASS.gbd, nbins = K)
.MixfMRIEnv$cat("n.class: ",
paste(tmp, collapse = " "),
"\n", sep = "", quiet = TRUE)
}
if(check){
break
} else{
iter <- iter + 1
}
if(iter > .FC.CT$INIT$max.try.iter){
.MixfMRIEnv$cat("max.try.iter reached.\n")
break
}
}
initial.em.gbd.update(PARAM, CLASS.gbd, K)
} # End of initial.em.gbd.prob.extend().
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