R/partitionlev.R

In delt: Estimation of Multivariate Densities Using Adaptive Partitions

partitionlev<-function(tree,suppo){

#if (is.null(tree$label)) tree$label<-tree$mean

xlkm<-length(suppo)/2
sollkm<-length(tree$val)           #solmujen lkm

#Find parents and number of leaves:

leafloc<-findleafs(tree$left,tree$right)

N<-matrix(0,sollkm,1)   #number of leaves in the tree whose root is i
p<-matrix(0,sollkm,1)   #parent
t<-sollkm
while (t>=1){
  if ((!is.na(leafloc[t])) && (leafloc[t]==1)){  #l(t)=0 eli ollaan lehdessa
   N[t]<-1
  }
  else if ((!is.na(leafloc[t])) && (leafloc[t]==0)){ #non-terminal node
     p[tree$left[t]]<-t       #p[t+1]<-t
     p[tree$right[t]]<-t      #p[endpoint(tree,t)+1]<-t
     N[t]<-N[tree$left[t]]+N[tree$right[t]]
  }
  t<-t-1
}

leafnum<-N[1]
recs<-matrix(0,leafnum,2*xlkm)
values<-matrix(0,leafnum,1)
frekv<-matrix(0,leafnum,1)

if (leafnum==1){ 
  recs<-suppo
  values<-tree$val[1]
}
else{
 ind<-1
 for (i in 1:sollkm){
   if ((!is.na(leafloc[i])) && (leafloc[i]==1)){  #i is leaf
     values[ind]<-tree$mean[i]
     recs[ind,]<-suppo
     frekv[ind]<-tree$nelem[i]
     j<-i
     while (p[j]>0){  #we are not in the root
         pare<-p[j]
         vari<-tree$vec[pare]
         split<-tree$val[pare]
         if (tree$left[pare]==j){  #i is left child
           if (split<recs[ind,2*vari]){ #if we have new restriction 
               recs[ind,2*vari]<-split
           }
         }
         else{  #i is right child
           if (split>recs[ind,2*vari-1]){ #if we have new restriction 
               recs[ind,2*vari-1]<-split
           }
         }
         j<-pare
     }
     ind<-ind+1
   }
 }
}

return(list(values=values,recs=recs,frekv=frekv))
}