R script

numsplits<-1000

f=file.choose()
text<-readLines(f,encoding="UTF-8")
nrows<-length(text)
writeLines(text[length(text)], con = "D:\\projects\\basicToR\\junk.txt", sep = "\n", useBytes = FALSE)
k<-read.table("D:\\projects\\basicToR\\junk.txt",sep=",")
ncolumns<-length(k)
print("nrows="); print(nrows)
print("ncolumns="); print(ncolumns)

t<-read.table(f,sep=",")
nentries=0;for (i in t){for (k in i){nentries=nentries+1}}
print("nentries=");print(nentries)

if(nentries==nrows*ncolumns)    {
     print("Columns, rows, and entries check; we're good to go.")
    }
else{
     print("Columns, rows, and entries don't check; please look at your data file to make sure each line has equal no. of entries.")
    }



#t<-read.table(f,sep=",")
#for (i in seq(1, nrows, 1)) {
#   for (j in seq(1, ncolumns, 1)) {
#       if(j!=ncolumns){
#           print(t[i,j]);print(",");
#       }
#       else{
#           print(t[i,j]);#chr$(10)
#       }
#   }
#}



nfirsthalf<-ncolumns/2
nsechalf<-ncolumns-nfirsthalf
sumr<-0
sumsteppedr<-0

for (split in seq(1, numsplits, 1)){
    firstsofar=0
    sum1=0
    count1=0
    sum2=0
    count2=0
    sumsteppedrspear=0
    sumsteppedrrulon=0
    randnum<-list()
  score1<-list()
  randnum2<-list()

    for (i in seq(1, nfirsthalf, 1)) {
        randnum[i]=round(ncolumns*runif(1, min=0, max=1)+1)
        taken<-"no"
        for (q in seq(1,firstsofar,1)) {
            if( randnum[i]==randnum[q]) {taken="yes"}
        }
        if (taken=="yes"){randnum[i]=round(ncolumns*runif(1, min=0, max=1)+1)}
        print("Keeper is");print(randnum(i))
        firstsofar=firstsofar+1
    }

    for (i in seq(1, nfirsthalf, 1)) {
        print(randnum[i])
    }

    j<-0
    for (i in seq(1, ncolumns, 1)) {
        taken<-"no"
        for (q in seq(1, nfirsthalf, 1)) {
            if (randnum[q]==i){taken="yes"}
        }
        if (taken=="no"){
            j=j+1
            randnum2[j]=i
        }
    }

    for (i in seq(1, nsechalf, 1)) {
        print("randnum2="); print(randnum2[i])
    }


    sum1=0
    count1=0
    for (z in seq(1, nrows, 1)) {
        sum1=0
        count1=0
        for (i in seq(1, nfirsthalf, 1)) {
            y=randnum[i]
            if (t[z,y]!="n"){sum1=sum1+as.numeric(t[z,y]);count1=count1+1}
        }
        if(count1==0){print("a split where all were missing! line number=");print(z);count1=1}
        av1[z]=sum1/count1
        score1[z]=av1[z]*nfirsthalf
    }


    sum2=0
    count2=0
    for (z in seq(1, nrows, 1)) {
        sum2=0
        count2=0
        for (i in seq(1, nfirsthalf, 1)) {
            y=randnum2[i]
            if(t[z,y]!="n"){sum2=sum2+as.numeric(t[z,y]);count2=count2+1}
        }
        av2[z]=sum2/count2
        score2[z]=av2[z]*nsechalf
    }

    for (z in seq(1, nrows, 1)) {
        scoretot[z]=score1[z]+score2[z]
    }

    sumxy=0
    sumx=0
    sumy=0
    sumx2=0
    sumy2=0
    sumscoretot2=0
    sumscoretot=0

    for (i in seq(1, nrows, 1)) {
        sumxy=sumxy+score1[i]*score2[i]
        sumx=sumx+score1[i]
        sumy=sumy+score2[i]
        sumx2=sumx2+(score1[i])^2
        sumy2=sumy2+(score2[i])^2
        sumscoretot2=sumscoretot2+scoretot[i]^2
        sumscoretot=sumscoretot+scoretot[i]
    }

    r=(sumxy-sumx*sumy/nrows)/((sumx2-sumx^2/nrows)*(sumy2-sumy^2/nrows))^0.5
    sdforx=((1/nrows)*(sumx2-sumx^2/nrows))^0.5
    sdfory=((1/nrows)*(sumy2-sumy^2/nrows))^0.5
    varfortot=((1/nrows)*(sumscoretot2-sumscoretot^2/nrows))

    steppedrspear=(2*r)/(1+r)
    steppedrrulon=4*r*sdforx*sdfory/varfortot
    sumsteppedrspear=sumsteppedrspear+steppedrspear
    sumsteppedrrulon=sumsteppedrrulon+steppedrrulon
}

avsteppedrspear=sumsteppedrspear/numsplits
print("average of stepped up r's, using Spearman method=");print(avsteppedrspear)
avsteppedrrulon=sumsteppedrrulon/numsplits
print("average of stepped up r's, using Rulon method="); print(avsteppedrrulon)

sumvariances=0
for (i in seq(1, ncolumns, 1)) {
    sumfirsts=0
    sumsq=0
    variance=0
    for (j in seq(1, nrows, 1)) {
        sumfirsts=sumfirsts+as.numeric(t[j,i])
        sumsq=sumsq+(as.numeric(t[j,i]))^2
    }
    sfs=sumfirsts^2
    variance=(1/nrows)*(sumsq-sfs/nrows)
    sumvariances=sumvariances+variance
}

for (i in seq(1, ncolumns, 1)) {
    mean=0
    sumdevs2=0
    sumfirsts=0
    for (j in seq(1, nrows, 1)) {
        sumfirsts=sumfirsts+as.numeric(t[j,i])
    }
    mean=sumfirsts/nrows
    for (j in seq(1, nrows, 1)) {
        sumdevs2=sumdevs2+(as.numeric(t[j,i])-mean)^2
    }
    sumvariances=sumvariances+sumdevs2/nrows
}

alphatrad=(ncolumns/(ncolumns-1))*(1-sumvariances/varfortot)

print("alphatrad=");print(alphatrad)