# Program for changing frequencies to allele lengths
#define the number of individuals forming the BULK, ni  **********************************
ni=15
#number of alleles (ni*2)
nal=ni*2
# Read data and create a list
# it is convenient to use ".CSV" input files  , specially when there are missing values
a10=read.csv(file="exFtoL.csv", header=TRUE)
#Next line read an ASCII format file 
#a10=read.table(file="ftol-example.txt", header=TRUE,sep='')
a20=split(a10, a10$marker)

#F to L function
ftol=function(inputfile) 
{
a1=a0[,3:ncol(a0)]
a2=cbind(a0[,1],a0[,2],trunc(0.5+(a1*nal)))
suma=apply(a2[,3:ncol(a2)],2,sum)
suma

test=suma-nal
colmiss=test[is.na(test)]
test[is.na(test)]=0 

#correcting round errors (+1, +2 or -1, -2)
for(i in 1:length(test)) 
{
  x=a1[,i];x[x==0]=NA
  if(test[i]==-2) {id= which.max(x)      ; a2[id,(i+2)]=a2[id,(i+2)]+1
                   x[id]=NA
                   id1=which.max(x); a2[id1,(i+2)]=a2[id1,(i+2)]+1
                  } 
  if(test[i]==-1) {id=which.max(x); a2[id,(i+2)]=a2[id,(i+2)]+1} 
  if(test[i]==1)  {id=which.max(a1[,i]); a2[id,(i+2)]=a2[id,(i+2)]-1} 
  if(test[i]==2)  {id=which.max(a1[,i]); a2[id,(i+2)]=a2[id,(i+2)]-1
                   x[id]=NA
                   id1=which.max(x); a2[id1,(i+2)]=a2[id1,(i+2)]-1
                  } 
}
suma=apply(a2[,3:ncol(a2)],2,sum)

a2[is.na(a2)]=0 
a3=matrix(nrow=nal,ncol=ncol(a2)-2);
for(l in 3:ncol(a2))
{m=0 
    for(j in 1:nrow(a2)) for(k in 1:a2[j,l]){ 
    if(a2[j,l]!=0){m=m+1; if(m<=nal) a3[m,(l-2)]=a2[j,2]}
    }
} 
# creating 15 genotypes from "nal" alleles

a4=matrix(nrow=ni*ncol(a3),ncol=3)
nam4=matrix(nrow=ni*ncol(a3),ncol=1)
nam1a=colnames(a1)
for(i in 1:ncol(a3)) 
{
  x0=a3[,i]
  x1=sample(x0, nal, replace = FALSE, prob = NULL);
  x2=matrix(0,ni,3)
  for(j in 1:ni)
    { x2[j,1]=j       
      x2[j,2]=x1[2*(j-1)+1];
      x2[j,3]=x1[2*(j-1)+2]
    }
  a4[(ni*(i-1)+1):(ni*i),]=x2
  nam4[(ni*(i-1)+1):(ni*i),]=rep(nam1a[i],ni)
}
a5=cbind(nam4,as.data.frame(a4))
colnames(a5)=c("geno", "ind", paste(a0[1,1],c("-1","-2"),sep=""))
a5
}
# end FtoL function

sale=list();final0=data.frame(aux=0) 
# applying the function FtoL using a20[[i]] as input file, and sale[[i]] as output file
for(i in 1:length(a20)) 
{
  a0=a20[[i]]
  sale[[i]]=ftol(inputfile=a0)
  final0=merge(final0,sale[[i]])
}
final0$ind=as.numeric(final0$ind)
temp=final0[order(final0$geno, final0$ind),]
final=temp[,c(1,2,4:ncol(temp))]
nombres=t(names(a20))
# you can use any of the next lines for obtaining CSV or ASCII format output files
write.csv(final, file="exFtoL-OUT.csv", quote=F, row.names=F, na="")
#help(write.csv)
#write.csv(nombres, file="nombres.csv", quote=F)
#write.table(final, file="final2.txt", quote=F,row.names=F)
write.table(nombres, file="names.txt", quote=F,row.names=F,col.names=F)

# Estimate frequencies on the simulated individuals
lim= (ncol(final)-1);lim2= (ncol(final)-2)/2 ;k=0;
ff=list(length=lim2);pfin=list(length=lim2)
for(i in seq(from=3, to=lim, by=2)) 
{
  k=k+1
  ff[[k]]=table(c(final[,i],final[,i+1]))
  pfin[[k]]=ff[[k]]/sum(ff[[k]])
}
names(pfin)=nombres
pfin