r - How to avoid using global variables in this case -

the following code tries build simple binary tree. non-leaf node contains left child 'lchild' , right child 'rchild'. leaf node contains nothing. nodes generated 1 one, first left branch right. nodes numbered time generated. node information including lchild , rchild , added bitree grow tree. question is, how can achieve goal avoiding defining 'bitree' , 'i' global? since cause

## rm(list=ls()) ## anti-social set.seed(1234)  ##this part generate dataset numvar <- 40  ##number of variables numsamples <- 400  ##number of samples class <- sample(c(0,1), replace = 1, numsamples)  ##categorical outcome '0' or '1' predictor <- matrix( sample(c(-1,0,1), replace=1, numsamples*numvar), ncol=numvar) data <- data.frame(predictor, class)  ##bitree list storing nodes information, reprenting tree, defined global bitree <- array( list(null), dim = 15 )  ##set global variable store id of each node on tree, defiend global <- 1  ##function create tree ##parameter 'root' id of root node each sub-tree createtree <- function( data, root ) {      force( root ) ##without result wrong     ##stop grow sub-tree if data size smaller 10    if( (nrow(data) <= 10 ) )  { <<- + 1; return(); }     ##seperate data 2 parts grow left-sub-tree , right-sub-tree    index.p1 <- 1:floor( nrow( data )/2 )    index.p2 <- !index.p1    data.p1 <- data[ index.p1,  ]    data.p2 <- data[ index.p2,  ]     ##note here: result differ or without execute of following call of root      ##i records id of node in tree. increments after 1 new node added     tree    <<- + 1     ##record node id left child of root    bitree[[ root ]]$lchild <<-     ##create left branch    createtree( data.p1, )     ##record node id right child of root    bitree[[ root ]]$rchild <<-     ##create right branch    createtree( data.p2, ) }  createtree( data, 1 ) 

if programming exercise , wish use pure r, other way using environments. no other r objects passed "reference", i.e. changes made args "visible" after function call.

here primitive implementation of bst on environments, mimics usage of dynamically allocated memory , pointers. not recommend using in practice. solution fun.

if need access "ordered set" container, should rather use stl's set in rcpp program.

a "school" implementation of bst

  # assumption: elements can compared < , ==    # each node represented list 3 elements   # (object, left, right)   # instead of pointer use strings    # note maximal number of nodes   # can created restricted    # create new empty tree   bst_new <- function() {      e <- new.env()      e$root <- null      e$last <- 0l # emulate "heap"      class(e) <- 'bst'      e   }     # insert element   # duplicates ignored   bst_insert <- function(bst, val) {      stopifnot(is.environment(bst), class(bst) == 'bst')       if (is.null(bst$root)) {         bst$root <- as.character(bst$last)         bst$last <- bst$last + 1l         assign(bst$root, list(val, null, null), bst)      }      else {         cur_id <- bst$root         repeat {            cur_node <- get(cur_id, bst)            if (val == cur_node[[1]])               return(invisible(null)) # ignore            else if (val < cur_node[[1]]) {               if (is.null(cur_node[[2]])) {                  cur_node[[2]] <- as.character(bst$last)                  assign(cur_id, cur_node, bst)                  bst$last <- bst$last + 1l                  assign(cur_node[[2]], list(val, null, null), bst)                  return(invisible(null))               }               else {                  cur_id <- cur_node[[2]]               }            }            else {               if (is.null(cur_node[[3]])) {                  cur_node[[3]] <- as.character(bst$last)                  assign(cur_id, cur_node, bst)                  bst$last <- bst$last + 1l                  assign(cur_node[[3]], list(val, null, null), bst)                  return(invisible(null))               }               else {                  cur_id <- cur_node[[3]]               }            }         }      }   }    # print elems, in order   bst_print <- function(bst) # or print.bst   {      stopifnot(is.environment(bst), class(bst) == 'bst')       bst_print_tmp <- function(bst, id_node) {         if (is.null(id_node)) return(invisible(null))          cur_node <- get(as.character(id_node), envir=bst)         bst_print_tmp(bst, cur_node[[2]]) # left         print(cur_node[[1]]) #         bst_print_tmp(bst, cur_node[[3]]) # right      }       bst_print_tmp(bst, bst$root)      invisible(null)   }     tree <- bst_new()   bst_insert(tree, 3)   bst_insert(tree, 5)   bst_insert(tree, 1)   bst_insert(tree, 2)   bst_insert(tree, 8)   bst_insert(tree, 7)   bst_print(tree)  ## [1] 1 ## [1] 2 ## [1] 3 ## [1] 5 ## [1] 7 ## [1] 8