#source("/home/zgong001/Documents/Alarm/D50C9v/RCode/CombineOrders.R")
getRelation = 
  function(st = "[6][8][5][7|6:8:5][1|7][3|7:1][4|1][2|4][0|2]"){
    re = c()
    temstr = substr(st, 2, nchar(st)-1)
    stlist = strsplit(chartr(old = "][", new = "##", temstr), "##")
    for(i in 1:length(stlist[[1]])){
      temc = chartr(old = "|", new = "g", stlist[[1]][i])
      
      if (grepl("g", temc)){
        temc2 = strsplit(temc, "g")
        
        X = temc2[[1]][1]
        TY = strsplit(temc2[[1]][2], ":")
        for(j in 1:length(TY[[1]])){
          Y = TY[[1]][j]
          
          cc= paste(Y,"->", X, sep = "")
          re = append(re, cc)
        }
      }
    }
    return(re)
  }

creatDataframe = 
  function(v = c("0", "1","2","3","4","5","6","7","8"), r = 246){
    cn = c()
    co= combn(v,2)
    for(i in 1:ncol(co)){
      X = co[1,i]
      Y = co[2,i]
      c1 = paste(X, "->", Y, sep = "")
      cn = append(cn,c1)
      c2 = paste(Y, "->", X, sep = "")
      cn = append(cn,c2)
      c3 = paste(X, " NA ", Y, sep = "")
      cn = append(cn,c3)
    }
    
    b= ncol(co)
    
    re = data.frame(matrix(0, nrow=r, ncol=b*3))
    colnames(re) = cn
    
    return(re)
  }


sumTable = 
  function (pathname = "/home/zgong001/Documents/Alarm/D1KC9v/D1KC9v BestOrders/Strus_D1KC9v.txt", 
            v = c("0", "1","2","3","4","5","6","7","8"), 
            exfilename = "/home/zgong001/Documents/Alarm/D1KC9v/D1KC9v BestOrders/Strus_D1KC9v.xlsx",
            xlsxfile = "/home/zgong001/Documents/Alarm/D50S9v2/D50S9vRS.xlsx"){
    library(bnlearn)
    library(xlsx)
    library(dplyr)
    suminput = read.table(pathname, header = FALSE)
    sumResu = data.frame()
    sumAnce = data.frame()
    suminput$ord = paste(suminput$V1,suminput$V2,suminput$V3,suminput$V4,suminput$V5,suminput$V6,suminput$V7,suminput$V8,suminput$V9, sep = " ")
    suminput = suminput[-c(1,2,3,4,5,6,7,8,9,13)]
    colnames(suminput)[1] <- "OrderScores"
    colnames(suminput)[2] <- "Structures"
    colnames(suminput)[3] <- "StructScores"
    
    orders= aggregate( OrderScores ~ord, data=suminput, FUN = mean)
    orders = orders[order(-orders[,2]), ]
    for(i in 1:nrow(orders)){
      orders$Opercentage[i] = exp(-log(sum(exp(orders$OrderScores-orders$OrderScores[i]))))
    }
    
    orders$Ocumper = cumsum(orders$Opercentage)
    
    for(i in 1:nrow(orders)){
      tem = suminput[which(suminput$ord== orders[i,1]), ]
      
      tem$Opercentage = orders[i,3]
      tem$Ocumper = orders[i,4]
      
      for(j in 1:nrow(tem)){
        tem$Spercentage[j] = exp(-log(sum(exp(tem$StructScores-tem$StructScores[j]))))
      }
      tem$Scumper = cumsum(tem$Spercentage)
      tem = tem[c("ord", "OrderScores", "Opercentage","Ocumper", "Structures", "StructScores","Spercentage","Scumper")]
      sumResu = rbind(sumResu, tem)
    }
    
    rs = nrow(sumResu)
    
    rl = creatDataframe(v,rs)
    sumResu= cbind(sumResu, rl)
    
    sumAnce = sumResu
    
    co= combn(v,2)
    
    for(i in 1:nrow(sumResu)){
      s = as.character(sumResu [i,5])
      rel = getRelation(st = s)
      
      for(j in 1:ncol(co)){
        X = co[1,j]
        Y = co[2,j]
        c1 = paste(X, "->", Y, sep = "")
        c2 = paste(Y, "->", X, sep = "")
        c3 = paste(X, " NA ", Y, sep = "")
        
        if (c1 %in% rel){
          sumResu[i,c1] = sumResu$Opercentage[i]*sumResu$Spercentage[i]
        }
        else if(c2 %in% rel){
          sumResu[i,c2] = sumResu$Opercentage[i]*sumResu$Spercentage[i]
        }
        else{
          sumResu[i,c3] = sumResu$Opercentage[i]*sumResu$Spercentage[i]
        }
        
      }
      
    }
    
    for(i in 1:nrow(sumAnce)){
      s = as.character(sumAnce [i,5])
      dags = model2network(s)
      
      for(j in 1:ncol(co)){
        X = co[1,j]
        Y = co[2,j]
        c1 = paste(X, "->", Y, sep = "")
        c2 = paste(Y, "->", X, sep = "")
        c3 = paste(X, " NA ", Y, sep = "")
        
        pXY = path(dags, from = X, to = Y)
        pYX = path(dags, from = Y, to = X)
        
        if (pXY){
          sumAnce[i,c1] = sumAnce$Opercentage[i]*sumAnce$Spercentage[i]
        }
        else if(pYX){
          sumAnce[i,c2] = sumAnce$Opercentage[i]*sumAnce$Spercentage[i]
        }
        else{
          sumAnce[i,c3] = sumAnce$Opercentage[i]*sumAnce$Spercentage[i]
        }
        
      }
      
    }
    
    
    
    sumP = colSums(sumResu[, -c(1:8)])
    sumA = colSums(sumAnce[, -c(1:8)])
    
    reP = read.xlsx(xlsxfile, sheetName = "Sheet1", colIndex = 1:3)
    reA = read.xlsx(xlsxfile, sheetName = "Sheet2", colIndex = 1:3)
    
    sP = cbind(reP, sumP,  diffT = abs(sumP-reP[,2]), diffB = abs(sumP-reP[,3]))
    sA = cbind(reA, sumA,  diffT = abs(sumA-reA[,2]), diffB = abs(sumA-reA[,3]))
    
    distanceP = colSums(sP[,c(5,6)])
    distanceA = colSums(sA[,c(5,6)])
    
    
    
    write.xlsx(sumResu, exfilename, sheetName = "Parents Detail", col.names = TRUE, row.names = FALSE, append = FALSE)
    write.xlsx(sP, exfilename, sheetName = "Parents Summary", col.names = TRUE, row.names = TRUE, append = TRUE)
    write.xlsx(distanceP, exfilename, sheetName = "Parents Distance", col.names = TRUE, row.names = TRUE, append = TRUE)
    write.xlsx(sumAnce, exfilename, sheetName = "Ancestor Detail", col.names = TRUE, row.names = FALSE, append = TRUE)
    write.xlsx(sA, exfilename, sheetName = "Ancestor Summary", col.names = TRUE, row.names = TRUE, append = TRUE)
    write.xlsx(distanceA, exfilename, sheetName = "Ancestor Distance", col.names = TRUE, row.names = TRUE, append = TRUE)
    
    
    #   return(sP)
    
  }

#---------------------------------------------------------------------------------
sortStru = function(st = "[5][6][8][7|5:8][1|5:7][3|7:8][2|6:1][4|1][0|2]"){
  library(dplyr)
  re = ""
  temstr = substr(st, 2, nchar(st)-1)
  stlist = strsplit(chartr(old = "][", new = "##", temstr), "##")
  stlist = sort(stlist[[1]])
  for(i in 1:length(stlist)){
    if(nchar(stlist[i])>3){
      
      temc = chartr(old = "|", new = "g", stlist[i])
      
      temc2 = strsplit(temc, "g")
      X = temc2[[1]][1]
      TY = strsplit(temc2[[1]][2], ":")
      TY = sort(TY[[1]])
      
      TY2 = paste(TY, collapse = ":")
      
      stlist[i] = paste(X,"|", TY2, sep = "")
      
      stlist[i] <- TY %>%
        paste(., collapse=":") %>%
        paste(X, "|", ., sep = "") 
      
    }
    
  }
  
  re <- stlist %>%
    paste(., collapse="][") %>%
    paste("[", ., "]", sep = "") 
  
  return(re)
}

MB = 
  function (struc ="[6][8][5][7|6:8:5][3|7][1|7:3][4|1][2|4][0|2]", v ="1"){
    
    library(xlsx)
    library(bnlearn)
    library(dplyr)
    
    
    mbs = ""
    
    strutem <- struc %>%
      as.character(.) %>%
      substr(., 2, nchar(.)-1) 
    
    stru =  strsplit(chartr(old = "][", new = "##", strutem), "##")
    
    for(j in 1:length(stru[[1]])){
      if(grepl(v,stru[[1]][j])){
        mbs = paste(mbs, "[", stru[[1]][j], "]", sep = "")
      }
    }
    return(mbs)
  }

sumBlanket2 = 
  function (xlsxfile = "/home/zgong001/Documents/Alarm/D50S9v2/D50S9v2-newswap-0.5NONE-2-1h/Strus_D50S9v2_E30r3_o.xlsx",
            xlsxfile2 = "/home/zgong001/Documents/Alarm/D50S9v2/D50S9vRS.xlsx"){
    
    library(xlsx)
    library(bnlearn)
    library(dplyr)
    
    re = read.xlsx(xlsxfile, sheetName = "Parents Detail", colIndex = 1:8)
    re = na.omit(re)
    
    colnames(re) = c("Order", "OrderScore", "OP", "OPC", "Structures", "StructureScore", "SP", "SPC")
    
    truDis = vector()
    besDis = vector()
    
    for(l in 1:9){
      a = l*4-3
      b = l*4-1
      n = as.character(l-1)
      
      rebm = read.xlsx(xlsxfile2, sheetName = "Sheet3", colIndex = a:b)
      rebm = na.omit(rebm)
      colnames(rebm) = c("LableM", "TrueB", "BestB")
      
      MBS = vector(mode="character", length=0)
      for(i in 1:nrow(re)){
        
        mbt = MB(struc = re[i,5], v = n)
        st = sortStru(as.character(mbt))
        MBS = append(MBS,st)
        
      }
      
      blankScore = re$OP*re$SP
      REE = cbind(re, MBS, blankScore)
      
      ag = aggregate(blankScore ~ MBS, data = REE, sum )
      
      
      truedist = 0
      
      
      if(rebm[1,1] %in% ag[,1]){
        tem = ag
        tem[which(tem$MBS == as.character(rebm[1,1])),2] = abs(1-tem[which(tem$MBS == as.character(rebm[1,1])),2])
        truedist = sum(tem[,2])
      }
      else{
        truedist = 2
      }
      
      truDis = append(truDis, truedist)
      
      
      
      bestdist = 0
      
      tem2 = rebm[-1,1]
      tem3 = ag[,1]
      tt = vector()
      
      di1 = setdiff(tem2, tem3)
      di2 = setdiff(tem3, tem2)
      
      if(length(di1) == 0 & length(di2) == 0){
        temm = ag[order(ag[,1]),]
        temm1 =rebm[-1,c(1,3)]
        
        temmm11= temm1[order(temm1[,1]),]
        
        temm[,2] = abs(temmm11[,2] - temm[,2])
        
        bestdist = sum(temm[,2])
        
      }
      else if(length(di1) == 0){
        
        temm = ag[which(ag[,1] %in% di2),]
        temm2 =rebm[-1,c(1,3)]
        temm1 = ag[which(! ag[,1] %in% di2),]
        
        temmm21= temm1[order(temm1[,1]),]
        temmm22= temm2[order(temm2[,1]),]
        temmm21[,2] = abs(temmm21[,2] - temmm22[,2])
        temm=rbind(temm,temmm21)
        
        
        bestdist = sum(temm[,2])
        
      }else if(length(di2) == 0){
        
        temm2 =rebm[-1,c(1,3)]
        
        temm = temm2[which(temm2[,1] %in% di1),]
        
        temm1 = temm2[which(! temm2[,1] %in% di1),]
        
        
        temmm21= temm1[order(temm1[,1]),]
        temmm22= ag[order(ag[,1]),]
        
        
        temmm21[,2] = abs(temmm21[,2] - temmm22[,2])
        temm=rbind(temm,temmm21)
        
        
        bestdist = sum(temm[,2])
        
        
      }else{
        comm = intersect(tem2, tem3)
        
        
        temmm1 = rebm[which(rebm$LableM %in% comm),c(1,3)]
        temmm12= temmm1[order(temmm1[,1]),]
        temmm2 = ag[which(ag[,1] %in% comm),]
        temmm22= temmm2[order(temmm2[,1]),]
        temmm12[,2] = abs(temmm12[,2] - temmm22[,2])
        temt = rbind(temmm12, rebm[which(rebm$LableM %in% di1),c(1,3)])
        
        temt = rbind(data.frame(MBS = temt[,1], blankScore =temt[,2] ), ag[which(ag[,1] %in% di2),])
        bestdist = sum(temt[,2])
      }
      
      besDis = append(besDis, bestdist)
      
      
    }
    
    td = sum(truDis)
    bd = sum(besDis)
    
    write.xlsx(data.frame("True dis"= td, "Best dis" = bd), xlsxfile, sheetName = "Blanket Distance", col.names = TRUE, row.names = FALSE, append = TRUE)
    
    return(re)
  }

processFile = function(filepath = "/home/zgong001/Documents/Alarm/D50S9v2/D50S9v2-newswap-0.5NONE-1h/D50S9v2-E15-1hr1.txt") {
  re = data.frame()
  li = vector()
  con = file(filepath, "r")
  while ( TRUE ) {
    line = readLines(con, n = 1)
    if ( length(line) == 0 ) {
      break
    }
    li = append(li, line)
  }
  close(con)
  
  for(i in 1:length(li)){
    s = strsplit(li[i], "       ")
    b = strsplit(s[[1]][2], "      ")
    l = data.frame(st=s[[1]][1], sc= as.numeric(as.character(b[[1]][1])))
    re = rbind(re, l)
  }
  
  re = na.omit(re)
  
  re = unique(re)
  re = re[order(-re[,2]), ]
  
  m = re[1,2]
  
  n=0
  
  for(j in 2:nrow(re) ){
    s0 = re[j,2]
    
    te = -log(exp(s0-m)+1)
    
    m = m - te;
    
    if(exp(te) >= 0.99){
      break
    }
    n = j
  }
  
  ree = re[1:n,]
  
  #  sink("/home/zgong001/Documents/Alarm/D50S9v2/D50S9v2-newswap-0.5NONE-1h/myfile.txt", append=TRUE, split=TRUE)
  
  write.table("------", filepath, sep="\t", row.names=F, col.names=F, append=TRUE)
  
  write.table(ree, filepath, sep="\t", row.names=F, col.names=F,append=TRUE)
  
  return(ree)
  
  
}