什么是的算法为做一个员额以穿越的二进制的树 没有 采用递归?

有帮助吗?

解决方案

这里有一个链接,提供了两个其他的解决方案没有使用任何访问标志。

https://leetcode.com/problems/binary-tree-postorder-traversal/

这显然是一堆为基础的解决方案由于缺乏父母指针在树。(我们就不需要一堆,如果有父母指针)。

我们将推动根节点的堆的第一次。同时堆叠的不是空的,我们继续推动左儿童的节点的堆。如果留下的孩子并不存在,我们推动其右的孩子。如果它是一个叶节点,我们过程中的节点和把它关闭。

我们还使用一个变量,以跟踪以前走过的节点。目的是要确定如果穿越是降/升树,我们还可以知道,如果它提升从左右。

如果我们登上树从左侧开始,我们就不会想要把它留儿童再次叠,并应继续升入下树,如果其权利的儿童存在。如果我们登上树从的权利,我们应该处理它,并把它关闭。

我们会过程中的节点和流行它的堆在这些情况下3:

  1. 节点是叶节点(没孩子)
  2. 我们只是历了树从的离开和没有对儿童存在。
  3. 我们只是历了树从的权利。

其他提示

下面是用一个叠层和没有被访问的标志的版本:

private void postorder(Node head) {
  if (head == null) {
    return;
  }
  LinkedList<Node> stack = new LinkedList<Node>();
  stack.push(head);

  while (!stack.isEmpty()) {
    Node next = stack.peek();

    boolean finishedSubtrees = (next.right == head || next.left == head);
    boolean isLeaf = (next.left == null && next.right == null);
    if (finishedSubtrees || isLeaf) {
      stack.pop();
      System.out.println(next.value);
      head = next;
    }
    else {
      if (next.right != null) {
        stack.push(next.right);
      }
      if (next.left != null) {
        stack.push(next.left);
      }
    }
  }
}

下面是从一个样品维基百科

nonRecursivePostorder(rootNode)
  nodeStack.push(rootNode)
  while (! nodeStack.empty())
    currNode = nodeStack.peek()
    if ((currNode.left != null) and (currNode.left.visited == false))
      nodeStack.push(currNode.left)
    else 
      if ((currNode.right != null) and (currNode.right.visited == false))
        nodeStack.push(currNode.right)
      else
        print currNode.value
        currNode.visited := true
        nodeStack.pop()

这种办法,我使用的迭代,后顺序遍历。我喜欢这做法因为:

  1. 它只处理一个单一的过渡每个循环周期,因此很容易遵守。
  2. 一个类似的解决方案适用于有序和预先顺序遍历

代码:

enum State {LEFT, RIGHT, UP, CURR}

public void iterativePostOrder(Node root) {
  Deque<Node> parents = new ArrayDeque<>();
  Node   curr = root;
  State state = State.LEFT;

  while(!(curr == root && state == State.UP)) {
    switch(state) {
      case LEFT:
        if(curr.left != null) {
          parents.push(curr);
          curr = curr.left;
        } else {
          state = RIGHT;
        }
        break;
      case RIGHT:
        if(curr.right != null) {
          parents.push(curr);
          curr = curr.right;
          state = LEFT;
        } else {
          state = CURR;
        }
        break; 
      case CURR:
        System.out.println(curr);
        state = UP;
        break;
      case UP: 
        Node child = curr;
        curr = parents.pop();
        state = child == curr.left ? RIGHT : CURR;
        break;
      default:
        throw new IllegalStateException();
    }
  }
}

说明:

你可以想想的步骤是这样的:

  1. 试图左
    • 如果左节点的存在:尝试再次离开
    • 如果左节点不存在:试试正确的
  2. 试试正确的
    • 如果一个正确的节点的存在:尝试离开那里
    • 如果没有权利存在的,你是在一片叶子:尝试电
  3. 尝试电
    • 印目前的节点
    • 所有节点下已经执行(后顺序):尝试了
  4. 尝试了
    • 如果节点是根,没有了,因此退出
    • 如果来自左,右
    • 如果来自权利,尽量电
import java.util.Stack;

public class IterativePostOrderTraversal extends BinaryTree {

    public static void iterativePostOrderTraversal(Node root){
        Node cur = root;
        Node pre = root;
        Stack<Node> s = new Stack<Node>();
        if(root!=null)
            s.push(root);
        System.out.println("sysout"+s.isEmpty());
        while(!s.isEmpty()){
            cur = s.peek();
            if(cur==pre||cur==pre.left ||cur==pre.right){// we are traversing down the tree
                if(cur.left!=null){
                    s.push(cur.left);
                }
                else if(cur.right!=null){
                    s.push(cur.right);
                }
                if(cur.left==null && cur.right==null){
                    System.out.println(s.pop().data);
                }
            }else if(pre==cur.left){// we are traversing up the tree from the left
                if(cur.right!=null){
                    s.push(cur.right);
                }else if(cur.right==null){
                    System.out.println(s.pop().data);
                }
            }else if(pre==cur.right){// we are traversing up the tree from the right
                System.out.println(s.pop().data);
            }
            pre=cur;
        }
    }

    public static void main(String args[]){
        BinaryTree bt = new BinaryTree();
        Node root = bt.generateTree();
        iterativePostOrderTraversal(root);
    }


}

下面是在C ++中,不需要用于在树记帐任何存储的溶液。结果 相反,它使用两个栈。一个帮助我们遍历和另一个存储节点,所以我们可以做他们的职位遍历。点击

std::stack<Node*> leftStack;
std::stack<Node*> rightStack;

Node* currentNode = m_root;
while( !leftStack.empty() || currentNode != NULL )
{
    if( currentNode )
    {
        leftStack.push( currentNode );
        currentNode = currentNode->m_left;
    }
    else
    {
        currentNode = leftStack.top();
        leftStack.pop();

        rightStack.push( currentNode );
        currentNode = currentNode->m_right;
    }
}

while( !rightStack.empty() )
{
    currentNode = rightStack.top();
    rightStack.pop();

    std::cout << currentNode->m_value;
    std::cout << "\n";
}

// java的版与标志

public static <T> void printWithFlag(TreeNode<T> root){
    if(null == root) return;

    Stack<TreeNode<T>> stack = new Stack<TreeNode<T>>();
    stack.add(root);

    while(stack.size() > 0){
        if(stack.peek().isVisit()){
            System.out.print(stack.pop().getValue() + "  ");
        }else{

            TreeNode<T> tempNode = stack.peek();
            if(tempNode.getRight()!=null){
                stack.add(tempNode.getRight());
            }

            if(tempNode.getLeft() != null){
                stack.add(tempNode.getLeft());
            }



            tempNode.setVisit(true);


        }
    }
}
void postorder_stack(Node * root){
    stack ms;
    ms.top = -1;
    if(root == NULL) return ;

    Node * temp ;
    push(&ms,root);
    Node * prev = NULL;
    while(!is_empty(ms)){
        temp = peek(ms);
        /* case 1. We are nmoving down the tree. */
        if(prev == NULL || prev->left == temp || prev->right == temp){
             if(temp->left)
                  push(&ms,temp->left);
             else if(temp->right)
                  push(&ms,temp->right);
             else {
                /* If node is leaf node */
                   printf("%d ", temp->value);
                   pop(&ms);
             }
         }
         /* case 2. We are moving up the tree from left child */
         if(temp->left == prev){
              if(temp->right)
                   push(&ms,temp->right);
              else
                   printf("%d ", temp->value);
         }

        /* case 3. We are moving up the tree from right child */
         if(temp->right == prev){
              printf("%d ", temp->value);
              pop(&ms);
         }
         prev = temp;
      }

}

请参阅本完整的Java实现。只要将代码复制,并在你的编译器粘贴。它将很好地工作。

import java.util.LinkedList;
import java.util.Queue;
import java.util.Stack;

class Node
{
    Node left;
    String data;
    Node right;

    Node(Node left, String data, Node right)
    {
        this.left = left;
        this.right = right;
        this.data = data;
    }

    public String getData()
    {
        return data;
    }
}

class Tree
{
    Node node;

    //insert
    public void insert(String data)
    {
        if(node == null)
            node = new Node(null,data,null);
        else
        {
            Queue<Node> q = new LinkedList<Node>();
            q.add(node);

            while(q.peek() != null)
            {
                Node temp = q.remove();
                if(temp.left == null)
                {
                    temp.left = new Node(null,data,null);
                    break;
                }
                else
                {
                    q.add(temp.left);
                }

                if(temp.right == null)
                {
                    temp.right = new Node(null,data,null);
                    break;
                }
                else
                {
                    q.add(temp.right);
                }
            }
        }
    }

    public void postorder(Node node)
    {
        if(node == null)
            return;
        postorder(node.left);
        postorder(node.right);
        System.out.print(node.getData()+" --> ");
    }

    public void iterative(Node node)
    {
        Stack<Node> s = new Stack<Node>();
        while(true)
        {
            while(node != null)
            {
                s.push(node);
                node = node.left;
            }



            if(s.peek().right == null)
            {
                node = s.pop();
                System.out.print(node.getData()+" --> ");
                if(node == s.peek().right)
                {
                    System.out.print(s.peek().getData()+" --> ");
                    s.pop();
                }
            }

            if(s.isEmpty())
                break;

            if(s.peek() != null)
            {
                node = s.peek().right;
            }
            else
            {
                node = null;
            }
        }
    }
}

class Main
{
    public static void main(String[] args) 
    {
        Tree t = new Tree();
        t.insert("A");
        t.insert("B");
        t.insert("C");
        t.insert("D");
        t.insert("E");

        t.postorder(t.node);
        System.out.println();

        t.iterative(t.node);
        System.out.println();
    }
}

我在这里贴的不同版本在c#(.净额)为参考:(在以迭代的穿越你可以指: 帮助我了解序穿越不使用递归)

  1. wiki(http://en.wikipedia.org/wiki/Post-order%5Ftraversal#Implementations)(优雅)
  2. 另一个版本的单一堆 (1和2:基本上使用的事实,即在以后历的右孩子的节点是访问之前访问的实际节点-所以,我们只是依靠检查,如果堆顶部是正确的儿童确实是最后发表了穿越节点,这就是被访问过-我已经加入的意见在以下代码段的详细信息)
  3. 使用两个堆栈版本(ref: http://www.geeksforgeeks.org/iterative-postorder-traversal/) (更容易:基本上员额以穿越的逆向是什么,但预以穿越一个简单的调整这一权利的节点是与第一,然后离开节点)
  4. 访问者使用的标志(简单)
  5. 单元测试

~

public string PostOrderIterative_WikiVersion()
        {
            List<int> nodes = new List<int>();
            if (null != this._root)
            {
                BinaryTreeNode lastPostOrderTraversalNode = null;
                BinaryTreeNode iterativeNode = this._root;
                Stack<BinaryTreeNode> stack = new Stack<BinaryTreeNode>();
                while ((stack.Count > 0)//stack is not empty
                    || (iterativeNode != null))
                {
                    if (iterativeNode != null)
                    {
                        stack.Push(iterativeNode);
                        iterativeNode = iterativeNode.Left;
                    }
                    else
                    {
                        var stackTop = stack.Peek();
                        if((stackTop.Right != null)
                            && (stackTop.Right != lastPostOrderTraversalNode))
                        {
                            //i.e. last traversal node is not right element, so right sub tree is not
                            //yet, traversed. so we need to start iterating over right tree 
                            //(note left tree is by default traversed by above case)
                            iterativeNode = stackTop.Right;
                        }
                        else
                        {
                            //if either the iterative node is child node (right and left are null)
                            //or, stackTop's right element is nothing but the last traversal node
                            //(i.e; the element can be popped as the right sub tree have been traversed)
                            var top = stack.Pop();
                            Debug.Assert(top == stackTop);
                            nodes.Add(top.Element);
                            lastPostOrderTraversalNode = top;
                        }
                    }
                }
            }
            return this.ListToString(nodes);
        }

这里是为了穿越一堆(我的版本)

public string PostOrderIterative()
        {
            List<int> nodes = new List<int>();
            if (null != this._root)
            {
                BinaryTreeNode lastPostOrderTraversalNode = null;
                BinaryTreeNode iterativeNode = null;
                Stack<BinaryTreeNode> stack = new Stack<BinaryTreeNode>();
                stack.Push(this._root);
                while(stack.Count > 0)
                {
                    iterativeNode = stack.Pop();
                    if ((iterativeNode.Left == null)
                        && (iterativeNode.Right == null))
                    {
                        nodes.Add(iterativeNode.Element);
                        lastPostOrderTraversalNode = iterativeNode;
                        //make sure the stack is not empty as we need to peek at the top
                        //for ex, a tree with just root node doesn't have to enter loop
                        //and also node Peek() will throw invalidoperationexception
                        //if it is performed if the stack is empty
                        //so, it handles both of them.
                        while(stack.Count > 0) 
                        {
                            var stackTop = stack.Peek();
                            bool removeTop = false;
                            if ((stackTop.Right != null) &&
                                //i.e. last post order traversal node is nothing but right node of 
                                //stacktop. so, all the elements in the right subtree have been visted
                                //So, we can pop the top element
                                (stackTop.Right == lastPostOrderTraversalNode))
                            {
                                //in other words, we can pop the top if whole right subtree is
                                //traversed. i.e. last traversal node should be the right node
                                //as the right node will be traverse once all the subtrees of
                                //right node has been traversed
                                removeTop = true;
                            }
                            else if(
                                //right subtree is null
                                (stackTop.Right == null) 
                                && (stackTop.Left != null) 
                                //last traversal node is nothing but the root of left sub tree node
                                && (stackTop.Left == lastPostOrderTraversalNode))
                            {
                                //in other words, we can pop the top of stack if right subtree is null,
                                //and whole left subtree has been traversed
                                removeTop = true;
                            }
                            else
                            {
                                break;
                            }
                            if(removeTop)
                            {
                                var top = stack.Pop();
                                Debug.Assert(stackTop == top);
                                lastPostOrderTraversalNode = top;
                                nodes.Add(top.Element);
                            }
                        }
                    }
                    else 
                    {
                        stack.Push(iterativeNode);
                        if(iterativeNode.Right != null)
                        {
                            stack.Push(iterativeNode.Right);
                        }
                        if(iterativeNode.Left != null)
                        {
                            stack.Push(iterativeNode.Left);
                        }
                    }
                }
            }
            return this.ListToString(nodes);
        }

使用两个堆栈

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

与访问过的国旗在C#(.净):

public string PostOrderIterative()
        {
            List<int> nodes = new List<int>();
            if (null != this._root)
            {
                BinaryTreeNode iterativeNode = null;
                Stack<BinaryTreeNode> stack = new Stack<BinaryTreeNode>();
                stack.Push(this._root);
                while(stack.Count > 0)
                {
                    iterativeNode = stack.Pop();
                    if(iterativeNode.visted)
                    {
                        //reset the flag, for further traversals
                        iterativeNode.visted = false;
                        nodes.Add(iterativeNode.Element);
                    }
                    else
                    {
                        iterativeNode.visted = true;
                        stack.Push(iterativeNode);
                        if(iterativeNode.Right != null)
                        {
                            stack.Push(iterativeNode.Right);
                        }
                        if(iterativeNode.Left != null)
                        {
                            stack.Push(iterativeNode.Left);
                        }
                    }
                }
            }
            return this.ListToString(nodes);
        }

定义:

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

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

单元测试

[TestMethod]
        public void PostOrderTests()
        {
            int[] a = { 13, 2, 18, 1, 5, 17, 20, 3, 6, 16, 21, 4, 14, 15, 25, 22, 24 };
            BinarySearchTree bst = new BinarySearchTree();
            foreach (int e in a)
            {
                string s1 = bst.PostOrderRecursive();
                string s2 = bst.PostOrderIterativeWithVistedFlag();
                string s3 = bst.PostOrderIterative();
                string s4 = bst.PostOrderIterative_WikiVersion();
                string s5 = bst.PostOrderIterative_TwoStacksVersion();
                Assert.AreEqual(s1, s2);
                Assert.AreEqual(s2, s3);
                Assert.AreEqual(s3, s4);
                Assert.AreEqual(s4, s5);
                bst.Add(e);
                bst.Delete(e);
                bst.Add(e);
                s1 = bst.PostOrderRecursive();
                s2 = bst.PostOrderIterativeWithVistedFlag();
                s3 = bst.PostOrderIterative();
                s4 = bst.PostOrderIterative_WikiVersion();
                s5 = bst.PostOrderIterative_TwoStacksVersion();
                Assert.AreEqual(s1, s2);
                Assert.AreEqual(s2, s3);
                Assert.AreEqual(s3, s4);
                Assert.AreEqual(s4, s5);
            }
            Debug.WriteLine(string.Format("PostOrderIterative: {0}", bst.PostOrderIterative()));
            Debug.WriteLine(string.Format("PostOrderIterative_WikiVersion: {0}", bst.PostOrderIterative_WikiVersion()));
            Debug.WriteLine(string.Format("PostOrderIterative_TwoStacksVersion: {0}", bst.PostOrderIterative_TwoStacksVersion()));
            Debug.WriteLine(string.Format("PostOrderIterativeWithVistedFlag: {0}", bst.PostOrderIterativeWithVistedFlag()));
            Debug.WriteLine(string.Format("PostOrderRecursive: {0}", bst.PostOrderRecursive()));
        }

Python和1堆和无标志:

def postorderTraversal(self, root):
    ret = []
    if not root:
        return ret
    stack = [root]
    current = None
    while stack:
        previous = current
        current = stack.pop()
        if previous and ((previous is current) or (previous is current.left) or (previous is current.right)):
            ret.append(current.val)
        else:
            stack.append(current)
            if current.right:
                stack.append(current.right)
            if current.left:
                stack.append(current.left)

    return ret

和是什么是更好地与类似的声明,为了穿越工程太

def inorderTraversal(self, root):
    ret = []
    if not root:
        return ret
    stack = [root]
    current = None
    while stack:
        previous = current
        current = stack.pop()
        if None == previous or previous.left is current or previous.right is current:
            if current.right:
                stack.append(current.right)
            stack.append(current)
            if current.left:
                stack.append(current.left)
        else:
            ret.append(current.val)

    return ret

我还没有添加的节点类作为其不是特别相关或任何测试用例,更让那些作为读者等的锻炼; Tibial。

void postOrderTraversal(node* root)
{
    if(root == NULL)
        return;

    stack<node*> st;
    st.push(root);

    //store most recent 'visited' node
    node* prev=root;

    while(st.size() > 0)
    {
        node* top = st.top();
        if((top->left == NULL && top->right == NULL))
        {
            prev = top;
            cerr<<top->val<<" ";
            st.pop();
            continue;
        }
        else
        {
            //we can check if we are going back up the tree if the current
            //node has a left or right child that was previously outputted
            if((top->left == prev) || (top->right== prev))
            {
                prev = top;
                cerr<<top->val<<" ";
                st.pop();
                continue;
            }

            if(top->right != NULL)
                st.push(top->right);

            if(top->left != NULL)
                st.push(top->left);
        }
    }
    cerr<<endl;
}

运行时间为O(n) - 所有节点需要访问 和空间为O(n) - 为堆栈,最坏的情况下树是一个单行链表

很高兴看到这么多热烈的办法,这一问题。很鼓舞人心的真的!

我碰到这个主题寻找简单的解决方案的迭代删除所有节点在我二进制树执行情况。我想他们中的一些,我尝试过类似的东西在其他地方发现的在网络上,但他们都不是真正给我的喜好。

事实是,我在开发一个数据库索引编制模块,用于一个非常具体的目(币区块链的索引),和我的数据存储磁盘上,不在RAM。我换的网页需要,做我自己的存管理。它的速度较慢的,但速度不够快的目的,并与具有的存储磁盘上,而不是RAM,我没有宗教承反对浪费空间(硬盘都是便宜)。

由于这个原因我的节点在我二进制的树有父母的指针。是的(所有)额外的空间,我谈论。我需要父母因为我需要循环的两个上升和下降,通过树于各种目的。

有,在我的脑海里,我很快写下来一小片的伪码在它如何可以做到的,那就是,一个后顺序历删除上的节点飞行。它的实施和测试,并成为我的一部分的解决方案。它是相当快了。

事情是:它变得真的,真的,简单的时的节点有父母的指针,而且自从我能空出来的父母的链接"只是离开了"节点。

这是伪代码,用于迭代后期以删除:

Node current = root;
while (current)
{
  if (current.left)       current = current.left;  // Dive down left
  else if (current.right) current = current.right; // Dive down right
  else
  {
    // Node "current" is a leaf, i.e. no left or right child
    Node parent = current.parent; // assuming root.parent == null
    if (parent)
    {
      // Null out the parent's link to the just departing node
      if (parent.left == current) parent.left = null;
      else                        parent.right = null;
    }
    delete current;
    current = parent;
  }
}
root = null;

如果你有兴趣更多的理论办法编码的复杂的收集(如我的二进制树,这是一个真正的自我平衡的红黑色树),然后检查了这些链接:

http://opendatastructures.org/versions/edition-0.1e/ods-java/6_2_BinarySearchTree_Unbala.html http://opendatastructures.org/versions/edition-0.1e/ods-java/9_2_RedBlackTree_Simulated_.html https://www.cs.auckland.ac.nz/software/AlgAnim/red_black.html

快乐码:-)

瑟伦*雾 http://iprotus.eu/

深度优先,交顺序,非递归的,无堆叠

在具有父:

   node_t
   {
     left,
     right
     parent
   }

   traverse(node_t rootNode)
   {
     bool backthreading = false 
     node_t node = rootNode

     while(node <> 0)

        if (node->left <> 0) and backthreading = false then
               node = node->left

            continue 
        endif

         >>> process node here <<<


        if node->right <> 0 then
            lNode = node->right
            backthreading = false
        else
            node = node->parent

            backthreading = true
        endif
    endwhile

1.1创建一个空的堆叠

2.1执行以下而根不是NULL

a) Push root's right child and then root to stack.

b) Set root as root's left child.

2.2从栈弹出的项目,并设置为根。

a) If the popped item has a right child and the right child 
   is at top of stack, then remove the right child from stack,
   push the root back and set root as root's right child.

b) Else print root's data and set root as NULL.

2.3重复步骤2.1和2.2,而堆栈不为空。

下面是Java实现与两个堆叠

public static <T> List<T> iPostOrder(BinaryTreeNode<T> root) {
    if (root == null) {
        return Collections.emptyList();
    }
    List<T> result = new ArrayList<T>();
    Deque<BinaryTreeNode<T>> firstLevel = new LinkedList<BinaryTreeNode<T>>();
    Deque<BinaryTreeNode<T>> secondLevel = new LinkedList<BinaryTreeNode<T>>();
    firstLevel.push(root);
    while (!firstLevel.isEmpty()) {
        BinaryTreeNode<T> node = firstLevel.pop();
        secondLevel.push(node);
        if (node.hasLeftChild()) {
            firstLevel.push(node.getLeft());
        }
        if (node.hasRightChild()) {
            firstLevel.push(node.getRight());
        }
    }
    while (!secondLevel.isEmpty()) {
        result.add(secondLevel.pop().getData());            
    }       
    return result;
}

下面是单元测试

@Test
public void iterativePostOrderTest() {
    BinaryTreeNode<Integer> bst = BinaryTreeUtil.<Integer>fromInAndPostOrder(new Integer[]{4,2,5,1,6,3,7}, new Integer[]{4,5,2,6,7,3,1});
    assertThat(BinaryTreeUtil.iPostOrder(bst).toArray(new Integer[0]), equalTo(new Integer[]{4,5,2,6,7,3,1}));

}
/**
 * This code will ensure holding of chain(links) of nodes from the root to till the level of the tree.
 * The number of extra nodes in the memory (other than tree) is height of the tree.
 * I haven't used java stack instead used this ParentChain. 
 * This parent chain is the link for any node from the top(root node) to till its immediate parent.
 * This code will not require any altering of existing BinaryTree (NO flag/parent on all the nodes).
 *  
 *  while visiting the Node 11; ParentChain will be holding the nodes 9 -> 8 -> 7 -> 1 where (-> is parent)
 *  
 *             1                               
              / \               
             /   \              
            /     \             
           /       \            
          /         \           
         /           \          
        /             \         
       /               \        
       2               7               
      / \             /         
     /   \           /          
    /     \         /           
   /       \       /            
   3       6       8               
  / \             /             
 /   \           /              
 4   5           9               
                / \             
                10 11

 *               
 * @author ksugumar
 *
 */
public class InOrderTraversalIterative {
    public static void main(String[] args) {
        BTNode<String> rt;
        String[] dataArray = {"1","2","3","4",null,null,"5",null,null,"6",null,null,"7","8","9","10",null,null,"11",null,null,null,null};
        rt = BTNode.buildBTWithPreOrder(dataArray, new Counter(0));
        BTDisplay.printTreeNode(rt);
        inOrderTravesal(rt);
    }

public static void postOrderTravesal(BTNode<String> root) {
    ParentChain rootChain = new ParentChain(root);
    rootChain.Parent = new ParentChain(null);

    while (root != null) {

        //Going back to parent
        if(rootChain.leftVisited && rootChain.rightVisited) {
            System.out.println(root.data); //Visit the node.
            ParentChain parentChain = rootChain.Parent;
            rootChain.Parent = null; //Avoid the leak
            rootChain = parentChain;
            root = rootChain.root;
            continue;
        }

        //Traverse Left
        if(!rootChain.leftVisited) {
            rootChain.leftVisited = true;
            if (root.left != null) {
                ParentChain local = new ParentChain(root.left); //It is better to use pool to reuse the instances.
                local.Parent = rootChain;
                rootChain = local;
                root = root.left;
                continue;
            }
        } 

        //Traverse RIGHT
        if(!rootChain.rightVisited) {
            rootChain.rightVisited = true;
            if (root.right != null) {
                ParentChain local = new ParentChain(root.right); //It is better to use pool to reuse the instances.
                local.Parent = rootChain;
                rootChain = local;
                root = root.right;
                continue;
            }
        }
    }
}

class ParentChain {
    BTNode<String> root;
    ParentChain Parent;
    boolean leftVisited = false;
    boolean rightVisited = false;

    public ParentChain(BTNode<String> node) {
        this.root = node; 
    }

    @Override
    public String toString() {
        return root.toString();
    }
}
void display_without_recursion(struct btree **b) 
{
    deque< struct btree* > dtree;
        if(*b)
    dtree.push_back(*b);
        while(!dtree.empty() )
    {
        struct btree* t = dtree.front();
        cout << t->nodedata << " " ;
        dtree.pop_front();
        if(t->right)
        dtree.push_front(t->right);
        if(t->left)
        dtree.push_front(t->left);
    }
    cout << endl;
}
    import java.util.Stack;
   class Practice
{

    public static void main(String arr[])
    {
        Practice prc = new Practice();
        TreeNode node1 = (prc).new TreeNode(1);
        TreeNode node2 = (prc).new TreeNode(2);
        TreeNode node3 = (prc).new TreeNode(3);
        TreeNode node4 = (prc).new TreeNode(4);
        TreeNode node5 = (prc).new TreeNode(5);
        TreeNode node6 = (prc).new TreeNode(6);
        TreeNode node7 = (prc).new TreeNode(7);
        node1.left = node2;
        node1.right = node3;
        node2.left = node4;
        node2.right = node5;
        node3.left = node6;
        node3.right = node7;
        postOrderIteratively(node1);
    }

    public static void postOrderIteratively(TreeNode root)
    {
        Stack<Entry> stack = new Stack<Entry>();
        Practice prc = new Practice();
        stack.push((prc).new Entry(root, false));
        while (!stack.isEmpty())
        {
            Entry entry = stack.pop();
            TreeNode node = entry.node;
            if (entry.flag == false)
            {
                if (node.right == null && node.left == null)
                {
                    System.out.println(node.data);
                } else
                {
                    stack.push((prc).new Entry(node, true));
                    if (node.right != null)
                    {
                        stack.push((prc).new Entry(node.right, false));
                    }
                    if (node.left != null)
                    {
                        stack.push((prc).new Entry(node.left, false));
                    }
                }
            } else
            {
                System.out.println(node.data);
            }
        }

    }

    class TreeNode
    {
        int data;
        int leafCount;
        TreeNode left;
        TreeNode right;

        public TreeNode(int data)
        {
            this.data = data;
        }

        public int getLeafCount()
        {
            return leafCount;
        }

        public void setLeafCount(int leafCount)
        {
            this.leafCount = leafCount;
        }

        public TreeNode getLeft()
        {
            return left;
        }

        public void setLeft(TreeNode left)
        {
            this.left = left;
        }

        public TreeNode getRight()
        {
            return right;
        }

        public void setRight(TreeNode right)
        {
            this.right = right;
        }

        @Override
        public String toString()
        {
            return "" + this.data;
        }
    }

    class Entry
    {
        Entry(TreeNode node, boolean flag)
        {
            this.node = node;
            this.flag = flag;
        }

        TreeNode node;
        boolean flag;

        @Override
        public String toString()
        {
            return node.toString();
        }
    }


}

我寻找性能良好并且是简单定制的代码片段。螺纹树不是“简单”。双栈溶液需要O(n)的存储器中。本文给出了溶液和溶液通过 TCB 有额外的检查,并推动...

下面是一个经典的算法翻译成C为我工作:

void postorder_traversal(TreeNode *p, void (*visit)(TreeNode *))
{
    TreeNode   *stack[40];      // simple C stack, no overflow check
    TreeNode  **sp = stack;
    TreeNode   *last_visited = NULL;

    for (; p != NULL; p = p->left)
        *sp++ = p;

    while (sp != stack) {
        p = sp[-1];
        if (p->right == NULL || p->right == last_visited) {
            visit(p);
            last_visited = p;
            sp--;
        } else {
            for (p = p->right; p != NULL; p = p->left)
                *sp++ = p;
        }
    }
}

IMHO这个算法比以及执行和可读wikipedia.org / Tree_traversal伪代码更容易遵循。对于辉煌的详情,请参阅答案二叉树练习Knuth的第1卷。

下面是一个Python版本太多::

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

def postOrderIterative(root):

    if root is None :
        return

    s1 = []
    s2 = []
    s1.append(root)

    while(len(s1)>0):
        node = s1.pop()
        s2.append(node)

        if(node.left!=None):
            s1.append(node.left)

        if(node.right!=None):
            s1.append(node.right)

    while(len(s2)>0):
        node = s2.pop()
        print(node.data)

root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)
root.right.left = Node(6)
root.right.right = Node(7)
postOrderIterative(root)

下面是输出:

“在这里输入的图像描述”

所以,你可以使用一个堆栈做了后序遍历的。

private void PostOrderTraversal(Node pos) {
    Stack<Node> stack = new Stack<Node>();
    do {
        if (pos==null && (pos=stack.peek().right)==null) {
            for (visit(stack.peek()); stack.pop()==(stack.isEmpty()?null:stack.peek().right); visit(stack.peek())) {}
        } else if(pos!=null) {
            stack.push(pos);
            pos=pos.left;
        }
    } while (!stack.isEmpty());
}

后序遍历的不使用递归的逻辑

Postorder traversal,处理顺序是left-right-current。因此,我们需要访问其他地方之前先访问左边的部分。我们会尽量向下左尽可能为树的每个节点来遍历树。对于每个当前节点,如果右子存在,则推入堆栈推当前节点之前,同时根不是NULL /无。现在从栈中弹出一个节点,并检查该节点的右子是否存在。如果存在,则检查它是否是一样的顶级元素与否。如果它们是相同的,然后它表明我们不与右半部分做呢,所以处理当前节点之前,我们必须处理的右部和该弹出顶部元素(右孩子),推动当前节点回到文件堆中。在每个时间我们的头是被弹起的元素。如果当前元素是不一样的顶部,头不为空,然后我们与左,右部分,因此现在我们可以处理当前节点都做。我们必须重复前面的步骤,直到堆栈为空。

def Postorder_iterative(head):
    if head is None:
        return None
    sta=stack()
    while True:
        while head is not None:
            if head.r:
                sta.push(head.r)
            sta.push(head)
            head=head.l
        if sta.top is -1:
            break
        head = sta.pop()
        if head.r is not None and sta.top is not -1  and head.r is sta.A[sta.top]:
            x=sta.pop()
            sta.push(head)
            head=x
        else:
            print(head.val,end = ' ')
            head=None
    print()    

的两种方法,而无需递归执行后序遍历:搜索结果 1.使用访问节点中的一个的HashSet和一个堆栈回溯:

private void postOrderWithoutRecursion(TreeNode root) {
    if (root == null || root.left == null && root.right == null) {
        return;
    }
    Stack<TreeNode> stack = new Stack<>();
    Set<TreeNode> visited = new HashSet<>();
    while (!stack.empty() || root != null) {
        if (root != null) {
            stack.push(root);
            visited.add(root);
            root = root.left;
        } else {
            root = stack.peek();
            if (root.right == null || visited.contains(root.right)) {
                System.out.print(root.val+" ");
                stack.pop();
                root = null;
            } else {
                root = root.right;
            }

        }
    }
}

,点击 时间复杂度:O(n)的结果 空间复杂度:O(2N)搜索结果 2.使用树涂改方法:结果

private void postOrderWithoutRecursionAlteringTree(TreeNode root) {
    if (root == null || root.left == null && root.right == null) {
        return;
    }
    Stack<TreeNode> stack = new Stack<>();
    while (!stack.empty() || root != null) {
        if (root != null) {
            stack.push(root);
            root = root.left;
        } else {
            root = stack.peek();
            if (root.right == null) {
                System.out.print(root.val+" ");
                stack.pop();
                root = null;
            } else {
                TreeNode temp = root.right;
                root.right = null;
                root = temp;
            }
        }
    }
}

,点击 时间复杂度:O(n)的结果 空间复杂度:O(n)的结果,

树节点类别:

public class TreeNode {
    public int val;

    public TreeNode left;

    public TreeNode right;

    public TreeNode(int x) {
        val = x;
    }
}

下面是一个简短的(助行是3行),我需要在Python编写的通用树版本。当然,适用于更有限的二叉树了。树是节点和孩子的列表的元组。它只有一个堆栈。所示的样品使用。

def postorder(tree):
    def do_something(x):  # Your function here
        print(x),
    def walk_helper(root_node, calls_to_perform):
        calls_to_perform.append(partial(do_something, root_node[0]))
        for child in root_node[1]:
            calls_to_perform.append(partial(walk_helper, child, calls_to_perform))
    calls_to_perform = []
    calls_to_perform.append(partial(walk_helper, tree, calls_to_perform))
    while calls_to_perform:
        calls_to_perform.pop()()
postorder(('a', [('b', [('c', []), ('d', [])])]))
  

d   C   b   一个

在简单的解决方案,它可能看起来像没有最佳答案,但它是很容易理解。而且我相信,如果你理解了解决方案,那么你可以修改它,使最好的解决方案。

使用两个堆叠//

public List<Integer> postorderTraversal(TreeNode root){

 Stack<TreeNode> st=new Stack<>();
 Stack<TreeNode> st2=new Stack<>();
 ArrayList<Integer> al = new ArrayList<Integer>(); 

    if(root==null)
        return al;

 st.push(root);  //push the root to 1st stack

 while(!st.isEmpty())
 {
     TreeNode curr=st.pop();

     st2.push(curr);

     if(curr.left!=null)
        st.push(curr.left);
     if(curr.right!=null)
         st.push(curr.right);

 }

while(!st2.isEmpty())
    al.add(st2.pop().val);

//this ArrayList contains the postorder traversal

  return al;  
}
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