本文概述

• C++
• C
• python
• Java
• C#

与只有一种逻辑方式遍历线性数据结构(数组, 链表, 队列, 栈等)的树不同, 可以以不同的方式遍历树。以下是遍历树的常用方法。

文章图片
树示例
深度优先遍历：
(a)先序遍历(左, 根, 右)：4 2 5 1 3
(b)中序遍历(根, 左, 右)：1 2 4 5 3
(c)后续遍历(左, 右, 根)：4 5 2 3 1
广度优先或级别顺序遍历：1 2 3 4 5
请参阅这篇文章了解广度优先遍历。
先序遍历(实践)：

Algorithm Inorder(tree) 1. Traverse the left subtree, i.e., call Inorder(left-subtree) 2. Visit the root. 3. Traverse the right subtree, i.e., call Inorder(right-subtree)

中序遍历的使用
对于二叉搜索树(BST)， 中序遍历以非递减的顺序给出节点。为了以非递增的顺序获取BST节点，可以使用中序遍历的一种变体，即中序遍历的反转。
示例：上面给出的数字的顺序遍历为4 2 5 1 3。
先序遍历：

Algorithm Preorder(tree) 1. Visit the root. 2. Traverse the left subtree, i.e., call Preorder(left-subtree) 3. Traverse the right subtree, i.e., call Preorder(right-subtree)

先序遍历的用法
先序遍历遍历用于创建树的副本。先序遍历还用于在表达式树上获取前缀表达式。请参阅：http://en.wikipedia.org/wiki/Polish_notation了解为什么前缀表达式有用。
示例：上图给定的遍历为1 2 4 5 3。
后序遍历

Algorithm Postorder(tree) 1. Traverse the left subtree, i.e., call Postorder(left-subtree) 2. Traverse the right subtree, i.e., call Postorder(right-subtree) 3. Visit the root.

后序遍历
后序遍历用于删除树。请参阅删除树的问题
有关详细信息。后序遍历对于获取表达式树的后缀表达式也很有用。请参阅http://en.wikipedia.org/wiki/Reverse_Polish_notation了解后缀表达式的用法。
示例：上图给定的事后遍历为4 5 2 3 1。
C++

// C program for different tree traversals #include < iostream> using namespace std; /* A binary tree node has data, pointer to left child and a pointer to right child */ struct Node { int data; struct Node* left, *right; Node( int data) { this -> data = https://www.lsbin.com/data; left = right = NULL; } }; /* Given a binary tree, print its nodes according to the"bottom-up" postorder traversal. */ void printPostorder( struct Node* node) { if (node == NULL) return ; // first recur on left subtree printPostorder(node-> left); // then recur on right subtree printPostorder(node-> right); // now deal with the node cout < < node-> data < < " " ; }/* Given a binary tree, print its nodes in inorder*/ void printInorder( struct Node* node) { if (node == NULL) return ; /* first recur on left child */ printInorder(node-> left); /* then print the data of node */ cout < < node-> data < < " " ; /* now recur on right child */ printInorder(node-> right); }/* Given a binary tree, print its nodes in preorder*/ void printPreorder( struct Node* node) { if (node == NULL) return ; /* first print data of node */ cout < < node-> data < < " " ; /* then recur on left sutree */ printPreorder(node-> left); /* now recur on right subtree */ printPreorder(node-> right); } /* Driver program to test above functions*/ int main() { struct Node *root = new Node(1); root-> left= new Node(2); root-> right= new Node(3); root-> left-> left= new Node(4); root-> left-> right = new Node(5); cout < < "\nPreorder traversal of binary tree is \n" ; printPreorder(root); cout < < "\nInorder traversal of binary tree is \n" ; printInorder(root); cout < < "\nPostorder traversal of binary tree is \n" ; printPostorder(root); return 0; }

C

// C program for different tree traversals #include < stdio.h> #include < stdlib.h> /* A binary tree node has data, pointer to left child and a pointer to right child */ struct node { int data; struct node* left; struct node* right; }; /* Helper function that allocates a new node with the given data and NULL left and right pointers. */ struct node* newNode( int data) { struct node* node = ( struct node*) malloc ( sizeof ( struct node)); node-> data = https://www.lsbin.com/data; node-> left = NULL; node-> right = NULL; return (node); }/* Given a binary tree, print its nodes according to the"bottom-up" postorder traversal. */ void printPostorder( struct node* node) { if (node == NULL) return ; // first recur on left subtree printPostorder(node-> left); // then recur on right subtree printPostorder(node-> right); // now deal with the node printf ( "%d " , node-> data); }/* Given a binary tree, print its nodes in inorder*/ void printInorder( struct node* node) { if (node == NULL) return ; /* first recur on left child */ printInorder(node-> left); /* then print the data of node */ printf ( "%d " , node-> data); /* now recur on right child */ printInorder(node-> right); }/* Given a binary tree, print its nodes in preorder*/ void printPreorder( struct node* node) { if (node == NULL) return ; /* first print data of node */ printf ( "%d " , node-> data); /* then recur on left sutree */ printPreorder(node-> left); /* now recur on right subtree */ printPreorder(node-> right); }/* Driver program to test above functions*/ int main() { struct node *root= newNode(1); root-> left= newNode(2); root-> right= newNode(3); root-> left-> left= newNode(4); root-> left-> right= newNode(5); printf ( "\nPreorder traversal of binary tree is \n" ); printPreorder(root); printf ( "\nInorder traversal of binary tree is \n" ); printInorder(root); printf ( "\nPostorder traversal of binary tree is \n" ); printPostorder(root); getchar (); return 0; }

python

# Python program to for tree traversals# A class that represents an individual node in a # Binary Tree class Node: def __init__( self , key): self .left = None self .right = None self .val = key# A function to do inorder tree traversal def printInorder(root):if root:# First recur on left child printInorder(root.left)# then print the data of node print (root.val), # now recur on right child printInorder(root.right)# A function to do postorder tree traversal def printPostorder(root):if root:# First recur on left child printPostorder(root.left)# the recur on right child printPostorder(root.right)# now print the data of node print (root.val), # A function to do preorder tree traversal def printPreorder(root):if root:# First print the data of node print (root.val), # Then recur on left child printPreorder(root.left)# Finally recur on right child printPreorder(root.right)# Driver code root = Node( 1 ) root.left= Node( 2 ) root.right= Node( 3 ) root.left.left= Node( 4 ) root.left.right= Node( 5 ) print "Preorder traversal of binary tree is" printPreorder(root)print "\nInorder traversal of binary tree is" printInorder(root)print "\nPostorder traversal of binary tree is" printPostorder(root)

Java

// Java program for different tree traversals/* Class containing left and right child of current node and key value*/ class Node { int key; Node left, right; public Node( int item) { key = item; left = right = null ; } }class BinaryTree { // Root of Binary Tree Node root; BinaryTree() { root = null ; }/* Given a binary tree, print its nodes according to the "bottom-up" postorder traversal. */ void printPostorder(Node node) { if (node == null ) return ; // first recur on left subtree printPostorder(node.left); // then recur on right subtree printPostorder(node.right); // now deal with the node System.out.print(node.key + " " ); }/* Given a binary tree, print its nodes in inorder*/ void printInorder(Node node) { if (node == null ) return ; /* first recur on left child */ printInorder(node.left); /* then print the data of node */ System.out.print(node.key + " " ); /* now recur on right child */ printInorder(node.right); }/* Given a binary tree, print its nodes in preorder*/ void printPreorder(Node node) { if (node == null ) return ; /* first print data of node */ System.out.print(node.key + " " ); /* then recur on left sutree */ printPreorder(node.left); /* now recur on right subtree */ printPreorder(node.right); }// Wrappers over above recursive functions void printPostorder(){printPostorder(root); } void printInorder(){printInorder(root); } void printPreorder(){printPreorder(root); }// Driver method public static void main(String[] args) { BinaryTree tree = new BinaryTree(); tree.root = new Node( 1 ); tree.root.left = new Node( 2 ); tree.root.right = new Node( 3 ); tree.root.left.left = new Node( 4 ); tree.root.left.right = new Node( 5 ); System.out.println( "Preorder traversal of binary tree is " ); tree.printPreorder(); System.out.println( "\nInorder traversal of binary tree is " ); tree.printInorder(); System.out.println( "\nPostorder traversal of binary tree is " ); tree.printPostorder(); } }

C#

// C# program for different // tree traversals using System; /* Class containing left and right child of current node and key value*/ class Node { public int key; public Node left, right; public Node( int item) { key = item; left = right = null ; } }class BinaryTree { // Root of Binary Tree Node root; BinaryTree() { root = null ; }/* Given a binary tree, print its nodes according to the "bottom-up" postorder traversal. */ void printPostorder(Node node) { if (node == null ) return ; // first recur on left subtree printPostorder(node.left); // then recur on right subtree printPostorder(node.right); // now deal with the node Console.Write(node.key + " " ); }/* Given a binary tree, print its nodes in inorder*/ void printInorder(Node node) { if (node == null ) return ; /* first recur on left child */ printInorder(node.left); /* then print the data of node */ Console.Write(node.key + " " ); /* now recur on right child */ printInorder(node.right); }/* Given a binary tree, print its nodes in preorder*/ void printPreorder(Node node) { if (node == null ) return ; /* first print data of node */ Console.Write(node.key + " " ); /* then recur on left sutree */ printPreorder(node.left); /* now recur on right subtree */ printPreorder(node.right); }// Wrappers over above recursive functions void printPostorder() {printPostorder(root); } void printInorder(){printInorder(root); } void printPreorder() {printPreorder(root); }// Driver Code static public void Main(String []args) { BinaryTree tree = new BinaryTree(); tree.root = new Node(1); tree.root.left = new Node(2); tree.root.right = new Node(3); tree.root.left.left = new Node(4); tree.root.left.right = new Node(5); Console.WriteLine( "Preorder traversal " + "of binary tree is " ); tree.printPreorder(); Console.WriteLine( "\nInorder traversal " + "of binary tree is " ); tree.printInorder(); Console.WriteLine( "\nPostorder traversal " + "of binary tree is " ); tree.printPostorder(); } }// This code is contributed by Arnab Kundu

输出如下：

Preorder traversal of binary tree is 1 2 4 5 3 Inorder traversal of binary tree is 4 2 5 1 3 Postorder traversal of binary tree is 4 5 2 3 1

再举一个例子：

文章图片
时间复杂度：O(n)
让我们看看不同的极端情况。
对于涉及树遍历的所有问题, 复杂度函数T(n)可以定义为：
T(n)= T(k)+ T(n – k – 1)+ c
其中k是根的一侧上的节点数, 而n-k-1在另一侧上。
让我们来分析边界条件
情况1：倾斜的树(子树之一为空, 其他子树为非空)
在这种情况下, k为0。
T(n)= T(0)+ T(n-1)+ c
T(n)= 2T(0)+ T(n-2)+ 2c
T(n)= 3T(0)+ T(n-3)+ 3c
T(n)= 4T(0)+ T(n-4)+ 4c
…………………………………………
…………………………………………。
T(n)=(n-1)T(0)+ T(1)+(n-1)c
T(n)= nT(0)+(n)c
T(0)的值将是一个常数, 例如d。 (遍历一棵空树将花费一些常量时间)
T(n)= n(c + d)
T(n)=Θ(n)(n的θ)
情况2：左右子树的节点数相等。
T(n)= 2T(| _n / 2_ |)+ c
对于主方法, 此递归函数为标准形式(T(n)= aT(n / b)+(-)(n))http://en.wikipedia.org/wiki/Master_theorem。如果我们通过主方法解决它, 我们得到(-)(n)
【如何实现树遍历（先序、中序和后序遍历详细代码）】辅助空间：如果我们不考虑函数调用的栈大小, 则为O(1)否则为O(n)。

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