帮助我理解不使用递归的有序遍历

Question

我能够在不使用递归的情况下理解前序遍历，但我很难理解中序遍历。也许我只是似乎不明白，因为我还没有理解递归的内部工作原理。

这是我到目前为止所尝试过的：

def traverseInorder(node):
    lifo = Lifo()
    lifo.push(node)
    while True:
        if node is None:
            break
        if node.left is not None:
            lifo.push(node.left)
            node = node.left
            continue
        prev = node
        while True:
            if node is None:
                break
            print node.value
            prev = node
            node = lifo.pop()
        node = prev
        if node.right is not None:
            lifo.push(node.right)
            node = node.right
        else:
            break

内部的 while 循环感觉不太对劲。此外，某些元素会被打印两次；也许我可以通过检查该节点之前是否已打印来解决这个问题，但这需要另一个变量，这又感觉不对。我哪里出错了？

我还没有尝试过后序遍历，但我想它是相似的，我也会在那里面临同样的概念障碍。

谢谢你的时间！

附：的定义 Lifo 和 Node:

class Node:
    def __init__(self, value, left=None, right=None):
        self.value = value
        self.left = left
        self.right = right

class Lifo:
    def __init__(self):
        self.lifo = ()
    def push(self, data):
        self.lifo = (data, self.lifo)
    def pop(self):
        if len(self.lifo) == 0:
            return None
        ret, self.lifo = self.lifo
        return ret

Answer 1

开始与递归算法（伪码）：

traverse(node):
  if node != None do:
    traverse(node.left)
    print node.value
    traverse(node.right)
  endif

这是尾递归的一个明显的例子，这样就可以很容易地把它变成一个while循环。

traverse(node):
  while node != None do:
    traverse(node.left)
    print node.value
    node = node.right
  endwhile

你留下了一个递归调用。什么是递归调用确实是推栈上一个新的环境，运行从一开始的代码，然后检索方面，继续做它在做什么。所以，你创建的存储堆栈，并决定，在每次迭代循环，无论我们是在“第一跑”的局面（非空节点）或“返回”的情况（空节点，非空栈）并运行相应的代码：

traverse(node):
  stack = []
  while !empty(stack) || node != None do:
    if node != None do: // this is a normal call, recurse
      push(stack,node)
      node = node.left
    else // we are now returning: pop and print the current node
      node = pop(stack)
      print node.value
      node = node.right
    endif
  endwhile

在辛苦的事情要把握的是“回归”的一部分：你要确定，你的循环，你的代码是否正在运行处于“进入功能”的情况，或在“从调用返回”的局面，你将有一个if/else链作为你有非末端递归在代码的情况较多。

在这种特定情况下，我们使用节点保持有关情况的信息。另一种方法是将存储在堆栈本身（就像一台计算机做递归）。用该技术中，该代码是最佳的少，但更容易遵循

traverse(node):
  // entry:
  if node == NULL do return
  traverse(node.left)
  // after-left-traversal:
  print node.value
  traverse(node.right)

traverse(node):
   stack = [node,'entry']
   while !empty(stack) do:
     [node,state] = pop(stack)
     switch state: 
       case 'entry': 
         if node == None do: break; // return
         push(stack,[node,'after-left-traversal']) // store return address
         push(stack,[node.left,'entry']) // recursive call
         break;
       case 'after-left-traversal': 
         print node.value;
         // tail call : no return address
         push(stack,[node.right,'entry']) // recursive call
      end
    endwhile 

Answer 2

下面是一个简单的有序非递归C ++代码..

void inorder (node *n)
{
    stack s;

    while(n){
        s.push(n);
        n=n->left;
    }

    while(!s.empty()){
        node *t=s.pop();
        cout<<t->data;
        t=t->right;

        while(t){
            s.push(t);
            t = t->left;
        }
    }
}

Answer 3

def print_tree_in(root):
    stack = []
    current = root
    while True:
        while current is not None:
            stack.append(current)
            current = current.getLeft();
        if not stack:
            return
        current = stack.pop()
        print current.getValue()
        while current.getRight is None and stack:
            current = stack.pop()
            print current.getValue()
        current = current.getRight();

Answer 4

def traverseInorder(node):
   lifo = Lifo()

  while node is not None:
    if node.left is not None:
       lifo.push(node)
       node = node.left
       continue

   print node.value

   if node.right is not None:
      node = node.right
      continue

   node = lifo.Pop()
   if node is not None :
      print node.value
      node = node.right

PS：我不知道Python的所以可能有一些语法问题

Answer 5

以下是在 C# (.net) 中使用堆栈进行中序遍历的示例：

（对于后序迭代您可以参考： 不使用递归的二叉树后序遍历)

public string InOrderIterative()
        {
            List<int> nodes = new List<int>();
            if (null != this._root)
            {
                Stack<BinaryTreeNode> stack = new Stack<BinaryTreeNode>();
                var iterativeNode = this._root;
                while(iterativeNode != null)
                {
                    stack.Push(iterativeNode);
                    iterativeNode = iterativeNode.Left;
                }
                while(stack.Count > 0)
                {
                    iterativeNode = stack.Pop();
                    nodes.Add(iterativeNode.Element);
                    if(iterativeNode.Right != null)
                    {
                        stack.Push(iterativeNode.Right);
                        iterativeNode = iterativeNode.Right.Left;
                        while(iterativeNode != null)
                        {
                            stack.Push(iterativeNode);
                            iterativeNode = iterativeNode.Left;
                        }
                    }
                }
            }
            return this.ListToString(nodes);
        }

这是带有已访问标志的示例：

public string InorderIterative_VisitedFlag()
        {
            List<int> nodes = new List<int>();
            if (null != this._root)
            {
                Stack<BinaryTreeNode> stack = new Stack<BinaryTreeNode>();
                BinaryTreeNode iterativeNode = null;
                stack.Push(this._root);
                while(stack.Count > 0)
                {
                    iterativeNode = stack.Pop();
                    if(iterativeNode.visted)
                    {
                        iterativeNode.visted = false;
                        nodes.Add(iterativeNode.Element);
                    }
                    else
                    {
                        iterativeNode.visted = true;
                        if(iterativeNode.Right != null)
                        {
                            stack.Push(iterativeNode.Right);
                        }
                        stack.Push(iterativeNode);
                        if (iterativeNode.Left != null)
                        {
                            stack.Push(iterativeNode.Left);
                        }
                    }
                }
            }
            return this.ListToString(nodes);
        }

binarytreenode、listtostring 实用程序的定义：

string ListToString(List<int> list)
        {
            string s = string.Join(", ", list);
            return s;
        }


class BinaryTreeNode
    {
        public int Element;
        public BinaryTreeNode Left;
        public BinaryTreeNode Right;        
    }

Answer 6

状态可被隐式地记住，

traverse(node) {
   if(!node) return;
   push(stack, node);
   while (!empty(stack)) {
     /*Remember the left nodes in stack*/
     while (node->left) {
        push(stack, node->left);
        node = node->left;
      }

      /*Process the node*/
      printf("%d", node->data);

      /*Do the tail recursion*/
      if(node->right) {
         node = node->right
      } else {
         node = pop(stack); /*New Node will be from previous*/
      }
    }
 }

Answer 7

@Victor，我对您的实现努力的状态推入堆栈的一些建议。我不认为这是必要的。因为每次你从叠搭元素已经走过左边。因此，而不是将信息存储到堆栈，我们需要的是一个标志，表示如果要处理的下一个节点是从栈或没有。以下是我的执行工作正常：

def intraverse(node):
    stack = []
    leftChecked = False
    while node != None:
        if not leftChecked and node.left != None:
            stack.append(node)
            node = node.left
        else:
            print node.data
            if node.right != None:
                node = node.right
                leftChecked = False
            elif len(stack)>0:
                node = stack.pop()
                leftChecked = True
            else:
                node = None

Answer 8

答案的小优化由@Emadpres

def in_order_search(node):
    stack = Stack()
    current = node

    while True:
        while current is not None:
            stack.push(current)
            current = current.l_child

        if stack.size() == 0:
            break

        current = stack.pop()
        print(current.data)
        current = current.r_child

Answer 9

这可以是有帮助的（Java实现）

public void inorderDisplay(Node root) {
    Node current = root;
    LinkedList<Node> stack = new LinkedList<>();
    while (true) {
        if (current != null) {
            stack.push(current);
            current = current.left;
        } else if (!stack.isEmpty()) {
            current = stack.poll();
            System.out.print(current.data + " ");
            current = current.right;
        } else {
            break;
        }
    }
}

Answer 10

简单的迭代序遍历没有递归

'''iterative inorder traversal, O(n) time & O(n) space '''

class Node:
    def __init__(self, value, left = None, right = None):
        self.value = value
        self.left = left
        self.right = right

def inorder_iter(root):

    stack = [root]
    current = root

    while len(stack) > 0:
        if current:
            while current.left:
                stack.append(current.left)
                current = current.left
        popped_node = stack.pop()
        current = None
        if popped_node:
            print popped_node.value
            current = popped_node.right
            stack.append(current)

a = Node('a')
b = Node('b')
c = Node('c')
d = Node('d')

b.right = d
a.left = b
a.right = c

inorder_iter(a)

Answer 11

class Tree:

    def __init__(self, value):
        self.left = None
        self.right = None
        self.value = value

    def insert(self,root,node):
        if root is None:
            root = node
        else:
            if root.value < node.value:
                if root.right is None:
                    root.right = node
                else:
                    self.insert(root.right, node)
            else:
                if root.left is None:
                    root.left = node
                else:
                    self.insert(root.left, node)       

    def inorder(self,tree):
        if tree.left != None:
            self.inorder(tree.left)
        print "value:",tree.value

        if tree.right !=None:
            self.inorder(tree.right)

    def inorderwithoutRecursion(self,tree):
        holdRoot=tree
        temp=holdRoot
        stack=[]
        while temp!=None:
            if temp.left!=None:
                stack.append(temp)
                temp=temp.left
                print "node:left",temp.value

            else:
                if len(stack)>0:
                    temp=stack.pop();
                    temp=temp.right
                    print "node:right",temp.value

Answer 12

下面是一个迭代C ++溶液作为替代什么@Emadpres贴：

void inOrderTraversal(Node *n)
{
    stack<Node *> s;
    s.push(n);
    while (!s.empty()) {
        if (n) {
            n = n->left;
        } else {
            n = s.top(); s.pop();
            cout << n->data << " ";
            n = n->right;
        }
        if (n) s.push(n);
    }
}

Answer 13

下面是一种迭代的Python代码序遍历::

class Node:
    def __init__(self, data):
        self.data = data
        self.left = None
        self.right = None

def inOrder(root):
    current = root
    s = []
    done = 0

    while(not done):
        if current is not None :
            s.append(current)
            current = current.left
        else :
            if (len(s)>0):
                current = s.pop()
                print current.data
                current = current.right
            else :
                done =1

root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)

inOrder(root)

Answer 14

我认为问题的一部分是利用"上一个"变量。你不应该来储存前一个节点你应该能够维持的国家组(后进先出)本身。

从 维基百科, ，算法你的目标是：

1. 访问的根源。
2. 穿越左子树
3. 遍历右子树

在伪代码(免责声明，我不知道蟒蛇这样的道歉Python/C++style代码下面！) 你的算法，将是这样的：

lifo = Lifo();
lifo.push(rootNode);

while(!lifo.empty())
{
    node = lifo.pop();
    if(node is not None)
    {
        print node.value;
        if(node.right is not None)
        {
            lifo.push(node.right);
        }
        if(node.left is not None)
        {
            lifo.push(node.left);
        }
    }
}

为postorder穿越你只是换了你推左右子树栈。