examples/keppler/1cpuRGM/JA1new.r

# ssh -X -Y -l aliaksah abel.uio.no
# scp -r  /usit/abel/u1/aliaksah/simulations/scenario1  aliaksah@pittheus.uio.no://mn/sarpanitu/ansatte-u2/aliaksah/Desktop/package/simulations
# cat slurm-16078690.out
# squeue -u aliaksah
#

source("https://raw.githubusercontent.com/aliaksah/EMJMCMC2016/master/R/the_mode_jumping_package4.r")


library(inline)
includes <- '#include <sys/wait.h>'
code <- 'int wstat; while (waitpid(-1, &wstat, WNOHANG) > 0) {};'
wait <- cfunction(body=code, includes=includes, convention='.C')


estimate.gamma.cpen <- function(formula, data,r = 1.0/223.0,logn=log(223.0),relat=c("to23","expi","logi","to35","sini","troot","sigmoid"))
{
  fparam<-NULL
  fmla.proc<-as.character(formula)[2:3]
  fobserved <- fmla.proc[1]
  fmla.proc[2]<-stri_replace_all(str = fmla.proc[2],fixed = " ",replacement = "")
  fmla.proc[2]<-stri_replace_all(str = fmla.proc[2],fixed = "\n",replacement = "")
  fparam <-stri_split_fixed(str = fmla.proc[2],pattern = "+I",omit_empty = F)[[1]]
  sj<-(stri_count_fixed(str = fparam, pattern = "*"))
  sj<-sj+(stri_count_fixed(str = fparam, pattern = "+"))
  for(rel in relat)
    sj<-sj+(stri_count_fixed(str = fparam, pattern = rel))
  sj<-sj+1
  tryCatch(capture.output({
    out <- glm(formula = formula,data = data, family = gaussian)
    # 1 for aic, 2 bic prior, else g.prior

    mlik = (-(out$deviance -2*log(r)*sum(sj)))/2
    waic = -(out$deviance + 2*out$rank)
    dic =  -(out$deviance + logn*out$rank)
    summary.fixed =list(mean = coefficients(out))

  }, error = function(err) {
    print(err)
    mlik = -10000
    waic = -10000
    dic =  -10000
    summary.fixed =list(mean = array(0,dim=length(fparam)))
  }))
  return(list(mlik = mlik,waic = waic , dic = dic,summary.fixed =summary.fixed))

}


parall.gmj <<- mclapply



simplifyposteriors<-function(X,posteriors,th=0.0001,thf=0.2)
{
  posteriors<-posteriors[-which(posteriors[,2]<th),]
  rhash<-hash()
  for(i in 1:length(posteriors[,1]))
  {
    expr<-posteriors[i,1]
    print(expr)
    res<-model.matrix(data=X,object = as.formula(paste0("RadiusJpt~",expr)))
    ress<-c(stri_flatten(round(res[,2],digits = 4),collapse = ""),stri_flatten(res[,2],collapse = ""),posteriors[i,2],expr)
    if(!((ress[1] %in% values(rhash))))
      rhash[[ress[1]]]<-ress
    else
    {
      if(ress[1] %in% keys(rhash))
      {
        rhash[[ress[1]]][3]<- (as.numeric(rhash[[ress[1]]][3]) + as.numeric(ress[3]))
        if(stri_length(rhash[[ress[1]]][4])>stri_length(expr))
          rhash[[ress[1]]][4]<-expr
      }
    }

  }
  res<-as.data.frame(t(values(rhash)[c(3,4),]))
  res$V1<-as.numeric(as.character(res$V1))
  res<-res[which(res$V1>thf),]
  res<-res[order(res$V1, decreasing = T),]
  clear(rhash)
  rm(rhash)
  res[which(res[,1]>1),1]<-1
  colnames(res)<-c("posterior","tree")
  return(res)
}

#"to23","expi","logi","to35","sini","troot"
sini<-function(x)sin(x/180*pi)
expi<-function(x)exp(-abs(x))
logi <-function(x)log(abs(x)+1)
troot<-function(x)abs(x)^(1/3)
to23<-function(x)abs(x)^(2.3)
to35<-function(x)abs(x)^(3.5)

MM = 1
M = 1
NM= 1000
compmax = 16
th<-(10)^(-5)
thf<-0.05

paral<-function(X,FUN)
{
  return(mclapply(X = X,FUN = FUN,mc.preschedule = F, mc.cores = 32))
}

runpar<-function(vect)
{

  set.seed(as.integer(vect[22]))
  do.call(runemjmcmc, vect[1:21])
  vals<-values(hashStat)
  fparam<-mySearch$fparam
  cterm<-max(vals[1,],na.rm = T)
  ppp<-mySearch$post_proceed_results_hash(hashStat = hashStat)
  post.populi<-sum(exp(values(hashStat)[1,][1:NM]-cterm),na.rm = T)
  clear(hashStat)
  rm(hashStat)
  rm(vals)
  gc()
  return(list(post.populi = post.populi, p.post =  ppp$p.post, cterm = cterm, fparam = fparam))
}


for(j in 1:100)
{
  tryCatch({

    set.seed(j)

    X<-read.csv("exa1.csv")

    formula1 = as.formula(paste(colnames(X)[5],"~ 1 +",paste0(colnames(X)[-5],collapse = "+")))
    data.example = as.data.frame(X)

    print(formula1)

    #wait()

    vect<-list(formula = formula1,data = data.example,estimator = estimate.gamma.cpen,estimator.args =  list(data = data.example),recalc_margin = 249, save.beta = F,interact = T,outgraphs=F,relations=c("to23","expi","logi","to35","sini","troot","sigmoid"),relations.prob =c(0.1,0.1,0.1,0.1,0.1,0.1,0.1),interact.param=list(allow_offsprings=4,mutation_rate = 250,last.mutation=10000, max.tree.size = 5, Nvars.max =15,p.allow.replace=0.9,p.allow.tree=0.01,p.nor=0.9,p.and = 0.9),n.models = 10000,unique =T,max.cpu = 4,max.cpu.glob = 4,create.table = F,create.hash = T,pseudo.paral = T,burn.in = 100,print.freq = 1000,advanced.param = list(
      max.N.glob=as.integer(10),
      min.N.glob=as.integer(5),
      max.N=as.integer(3),
      min.N=as.integer(1),
      printable = F))

    params <- list(vect)[rep(1,M)]

    for(i in 1:M)
    {
      params[[i]]$cpu<-i*j
      params[[i]]$simul<-"scenario_JM_"
      params[[i]]$simid<-j
    }
    gc()
    print(paste0("begin simulation ",j))
    results<-parall.gmj(X = params,FUN = runpar,mc.preschedule = F, mc.cores = M)
    print(results)

    wait()

    resa<-array(data = 0,dim = c(compmax,M*3))
    post.popul <- array(0,M)
    max.popul <- array(0,M)
    nulls<-NULL

    not.null<-1
    for(k in 1:M)
    {
      if(is.character(results[[k]]))
      {
        nulls<-c(nulls,k)
        next
      }
      if(length(results[[k]])==0)
      {
        nulls<-c(nulls,k)
        next
      }
      else
      {
        not.null <- k
      }

    }


    for(k in 1:M)
    {
      if(k %in% nulls)
      {
        results[[k]]<-results[[not.null]]
      }
      max.popul[k]<-results[[k]]$cterm
      post.popul[k]<-results[[k]]$post.populi
      if(length(resa[,k*3-2])==(length(results[[k]]$fparam)+1))
      {
        resa[,k*3-2]<-c(results[[k]]$fparam,"Post.Gen.Max")
        resa[,k*3-1]<-c(results[[k]]$p.post,results[[k]]$cterm)
        resa[,k*3]<-rep(post.popul[k],length(results[[k]]$p.post)+1)
      }else
      {
        resa[,k*3-2]<-rep(results[[k]]$fparam[1],length(resa[,k*3-2]))
        resa[,k*3-1]<-rep(0,length(resa[,k*3-1]))
        resa[,k*3]<-rep(-10^9,length(resa[,k*3]))
      }

    }


    gc()
    rm(results)
    ml.max<-max(max.popul)
    post.popul<-post.popul*exp(-ml.max+max.popul)
    p.gen.post<-post.popul/sum(post.popul)
    hfinal<-hash()
    for(ii in 1:M)
    {
      resa[,ii*3]<-p.gen.post[ii]*as.numeric(resa[,ii*3-1])
      resa[length(resa[,ii*3]),ii*3]<-p.gen.post[ii]
      if(p.gen.post[ii]>0)
      {
        for(jj in 1:(length(resa[,ii*3])-1))
        {
          if(resa[jj,ii*3]>0)
          {
            #print(paste0(ii,"  and ",jj))
            if(as.integer(has.key(hash = hfinal,key =resa[jj,ii*3-2]))==0)
              hfinal[[resa[jj,ii*3-2]]]<-as.numeric(resa[jj,ii*3])
            else
              hfinal[[resa[jj,ii*3-2]]]<-hfinal[[resa[jj,ii*3-2]]]+as.numeric(resa[jj,ii*3])
          }

        }
      }
    }

    posteriors<-values(hfinal)

    print(posteriors)
    clear(hfinal)
    rm(hfinal)
    rm(resa)
    rm(post.popul)
    rm(max.popul)
    posteriors<-as.data.frame(posteriors)
    posteriors<-data.frame(X=row.names(posteriors),x=posteriors$posteriors)
    posteriors$X<-as.character(posteriors$X)
    tryCatch({
      res1<-simplifyposteriors(X = X,posteriors = posteriors, th,thf)
      row.names(res1)<-1:dim(res1)[1]
      write.csv(x =res1,row.names = F,file = paste0("postJA1_",j,".csv"))
    },error = function(err){
      print("error")
      write.csv(x =posteriors,row.names = F,file = paste0("posteriorsJA1_",j,".csv"))
    },finally = {

      print(paste0("end simulation ",j))

    })
    rm(X)
    rm(data.example)
    rm(vect)
    rm(params)
    gc()
    print(paste0("end simulation ",j))
  },error = function(err){
    print("error")
    j=j-1
    print(paste0("repeat  simulation ",j))
  },finally = {

    print(paste0("end simulation ",j))
    rm(X)
    rm(data.example)
    rm(vect)
    rm(params)
    gc()
  })

}
aliaksah/EMJMCMC2016 documentation built on July 27, 2023, 5:48 a.m.