gmm_revise.R

#small sample for GMM
#install.packages('mclust') #installing Mclust package
args <- commandArgs(trailingOnly = T)
infile <- args[1]
outfile <- args[2]
time <- args[3]
library(mclust)
dat <- read.table(infile)
dat <- data.matrix(dat)
result.dat <- Mclust(dat)
if(result.dat$G == 2){
  if(result.dat$parameters$variance$modelName == "V"){
    wrtdat <- c(time,sum(result.dat$classification == 1),sum(result.dat$classification == 2),result.dat$n,result.dat$parameters$mean,result.dat$parameters$variance$sigmasq)
    wrtfile <- outfile
    write(t(wrtdat),outfile,append=T,ncolumns=8)
  }else if(result.dat$parameters$variance$modelName == "E" ){
    wrtdat <- c(time,sum(result.dat$classification == 1),sum(result.dat$classification == 2),result.dat$n,result.dat$parameters$mean,result.dat$parameters$variance$sigmasq,result.dat$parameters$variance$sigmasq)
    wrtfile <- outfile
    write(t(wrtdat),outfile,append=T,ncolumns=8)
  }
}