mirror of
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448 lines
13 KiB
Markdown
448 lines
13 KiB
Markdown
---
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comments: true
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---
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# 二叉树遍历
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非线性数据结构的遍历操作比线性数据结构更加复杂,往往需要使用搜索算法来实现。常见的二叉树遍历方式有层序遍历、前序遍历、中序遍历、后序遍历。
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## 层序遍历
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「层序遍历 Hierarchical-Order Traversal」从顶至底、一层一层地遍历二叉树,并在每层中按照从左到右的顺序访问结点。
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层序遍历本质上是「广度优先搜索 Breadth-First Traversal」,其体现着一种“一圈一圈向外”的层进遍历方式。
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![binary_tree_bfs](binary_tree_traversal.assets/binary_tree_bfs.png)
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<p align="center"> Fig. 二叉树的层序遍历 </p>
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广度优先遍历一般借助「队列」来实现。队列的规则是“先进先出”,广度优先遍历的规则是 ”一层层平推“ ,两者背后的思想是一致的。
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=== "Java"
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```java title="binary_tree_bfs.java"
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/* 层序遍历 */
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List<Integer> hierOrder(TreeNode root) {
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// 初始化队列,加入根结点
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Queue<TreeNode> queue = new LinkedList<>() {{ add(root); }};
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// 初始化一个列表,用于保存遍历序列
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List<Integer> list = new ArrayList<>();
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while (!queue.isEmpty()) {
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TreeNode node = queue.poll(); // 队列出队
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list.add(node.val); // 保存结点值
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if (node.left != null)
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queue.offer(node.left); // 左子结点入队
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if (node.right != null)
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queue.offer(node.right); // 右子结点入队
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}
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return list;
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}
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```
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=== "C++"
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```cpp title="binary_tree_bfs.cpp"
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/* 层序遍历 */
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vector<int> hierOrder(TreeNode* root) {
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// 初始化队列,加入根结点
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queue<TreeNode*> queue;
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queue.push(root);
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// 初始化一个列表,用于保存遍历序列
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vector<int> vec;
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while (!queue.empty()) {
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TreeNode* node = queue.front();
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queue.pop(); // 队列出队
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vec.push_back(node->val); // 保存结点
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if (node->left != nullptr)
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queue.push(node->left); // 左子结点入队
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if (node->right != nullptr)
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queue.push(node->right); // 右子结点入队
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}
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return vec;
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}
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```
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=== "Python"
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```python title="binary_tree_bfs.py"
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""" 层序遍历 """
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def hier_order(root: TreeNode):
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# 初始化队列,加入根结点
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queue = collections.deque()
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queue.append(root)
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# 初始化一个列表,用于保存遍历序列
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res = []
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while queue:
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node = queue.popleft() # 队列出队
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res.append(node.val) # 保存节点值
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if node.left is not None:
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queue.append(node.left) # 左子结点入队
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if node.right is not None:
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queue.append(node.right) # 右子结点入队
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return res
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```
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=== "Go"
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```go title="binary_tree_bfs.go"
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/* 层序遍历 */
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func levelOrder(root *TreeNode) []int {
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// 初始化队列,加入根结点
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queue := list.New()
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queue.PushBack(root)
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// 初始化一个切片,用于保存遍历序列
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nums := make([]int, 0)
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for queue.Len() > 0 {
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// poll
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node := queue.Remove(queue.Front()).(*TreeNode)
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// 保存结点
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nums = append(nums, node.Val)
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if node.Left != nil {
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// 左子结点入队
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queue.PushBack(node.Left)
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}
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if node.Right != nil {
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// 右子结点入队
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queue.PushBack(node.Right)
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}
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}
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return nums
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}
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```
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=== "JavaScript"
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```js title="binary_tree_bfs.js"
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/* 层序遍历 */
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function hierOrder(root) {
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// 初始化队列,加入根结点
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let queue = [root];
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// 初始化一个列表,用于保存遍历序列
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let list = [];
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while (queue.length) {
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let node = queue.shift(); // 队列出队
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list.push(node.val); // 保存结点
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if (node.left)
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queue.push(node.left); // 左子结点入队
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if (node.right)
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queue.push(node.right); // 右子结点入队
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}
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return list;
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}
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```
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=== "TypeScript"
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```typescript title="binary_tree_bfs.ts"
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/* 层序遍历 */
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function hierOrder(root: TreeNode | null): number[] {
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// 初始化队列,加入根结点
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const queue = [root];
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// 初始化一个列表,用于保存遍历序列
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const list: number[] = [];
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while (queue.length) {
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let node = queue.shift() as TreeNode; // 队列出队
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list.push(node.val); // 保存结点
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if (node.left) {
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queue.push(node.left); // 左子结点入队
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}
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if (node.right) {
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queue.push(node.right); // 右子结点入队
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}
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}
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return list;
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}
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```
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=== "C"
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```c title="binary_tree_bfs.c"
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```
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=== "C#"
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```csharp title="binary_tree_bfs.cs"
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/* 层序遍历 */
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public List<int?> hierOrder(TreeNode root)
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{
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// 初始化队列,加入根结点
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Queue<TreeNode> queue = new();
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queue.Enqueue(root);
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// 初始化一个列表,用于保存遍历序列
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List<int> list = new();
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while (queue.Count != 0)
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{
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TreeNode node = queue.Dequeue(); // 队列出队
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list.Add(node.val); // 保存结点值
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if (node.left != null)
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queue.Enqueue(node.left); // 左子结点入队
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if (node.right != null)
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queue.Enqueue(node.right); // 右子结点入队
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}
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return list;
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}
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```
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## 前序、中序、后序遍历
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相对地,前、中、后序遍历皆属于「深度优先遍历 Depth-First Traversal」,其体现着一种“先走到尽头,再回头继续”的回溯遍历方式。
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如下图所示,左侧是深度优先遍历的的示意图,右上方是对应的递归实现代码。深度优先遍历就像是绕着整个二叉树的外围“走”一圈,走的过程中,在每个结点都会遇到三个位置,分别对应前序遍历、中序遍历、后序遍历。
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![binary_tree_dfs](binary_tree_traversal.assets/binary_tree_dfs.png)
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<p align="center"> Fig. 二叉树的前 / 中 / 后序遍历 </p>
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<div class="center-table" markdown>
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| 位置 | 含义 | 此处访问结点时对应 |
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| ---------- | ------------------------------------ | ----------------------------- |
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| 橙色圆圈处 | 刚进入此结点,即将访问该结点的左子树 | 前序遍历 Pre-Order Traversal |
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| 蓝色圆圈处 | 已访问完左子树,即将访问右子树 | 中序遍历 In-Order Traversal |
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| 紫色圆圈处 | 已访问完左子树和右子树,即将返回 | 后序遍历 Post-Order Traversal |
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</div>
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=== "Java"
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```java title="binary_tree_dfs.java"
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/* 前序遍历 */
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void preOrder(TreeNode root) {
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if (root == null) return;
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// 访问优先级:根结点 -> 左子树 -> 右子树
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list.add(root.val);
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preOrder(root.left);
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preOrder(root.right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode root) {
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if (root == null) return;
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root.left);
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list.add(root.val);
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inOrder(root.right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode root) {
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if (root == null) return;
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root.left);
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postOrder(root.right);
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list.add(root.val);
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}
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```
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=== "C++"
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```cpp title="binary_tree_dfs.cpp"
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/* 前序遍历 */
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void preOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:根结点 -> 左子树 -> 右子树
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vec.push_back(root->val);
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preOrder(root->left);
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preOrder(root->right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root->left);
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vec.push_back(root->val);
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inOrder(root->right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode* root) {
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if (root == nullptr) return;
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root->left);
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postOrder(root->right);
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vec.push_back(root->val);
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}
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```
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=== "Python"
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```python title="binary_tree_dfs.py"
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""" 前序遍历 """
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def pre_order(root: typing.Optional[TreeNode]):
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if root is None:
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return
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# 访问优先级:根结点 -> 左子树 -> 右子树
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res.append(root.val)
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pre_order(root=root.left)
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pre_order(root=root.right)
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""" 中序遍历 """
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def in_order(root: typing.Optional[TreeNode]):
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if root is None:
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return
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# 访问优先级:左子树 -> 根结点 -> 右子树
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in_order(root=root.left)
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res.append(root.val)
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in_order(root=root.right)
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""" 后序遍历 """
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def post_order(root: typing.Optional[TreeNode]):
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if root is None:
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return
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# 访问优先级:左子树 -> 右子树 -> 根结点
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post_order(root=root.left)
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post_order(root=root.right)
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res.append(root.val)
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```
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=== "Go"
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```go title="binary_tree_dfs.go"
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/* 前序遍历 */
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func preOrder(node *TreeNode) {
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if node == nil {
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return
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}
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// 访问优先级:根结点 -> 左子树 -> 右子树
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nums = append(nums, node.Val)
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preOrder(node.Left)
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preOrder(node.Right)
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}
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/* 中序遍历 */
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func inOrder(node *TreeNode) {
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if node == nil {
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return
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}
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(node.Left)
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nums = append(nums, node.Val)
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inOrder(node.Right)
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}
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/* 后序遍历 */
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func postOrder(node *TreeNode) {
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if node == nil {
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return
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}
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(node.Left)
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postOrder(node.Right)
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nums = append(nums, node.Val)
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}
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```
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=== "JavaScript"
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```js title="binary_tree_dfs.js"
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/* 前序遍历 */
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function preOrder(root){
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if (root === null) return;
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// 访问优先级:根结点 -> 左子树 -> 右子树
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list.push(root.val);
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preOrder(root.left);
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preOrder(root.right);
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}
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/* 中序遍历 */
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function inOrder(root) {
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if (root === null) return;
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root.left);
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list.push(root.val);
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inOrder(root.right);
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}
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/* 后序遍历 */
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function postOrder(root) {
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if (root === null) return;
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root.left);
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postOrder(root.right);
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list.push(root.val);
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}
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```
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=== "TypeScript"
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```typescript title="binary_tree_dfs.ts"
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/* 前序遍历 */
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function preOrder(root: TreeNode | null): void {
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if (root === null) {
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return;
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}
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// 访问优先级:根结点 -> 左子树 -> 右子树
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list.push(root.val);
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preOrder(root.left);
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preOrder(root.right);
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}
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/* 中序遍历 */
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function inOrder(root: TreeNode | null): void {
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if (root === null) {
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return;
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}
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root.left);
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list.push(root.val);
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inOrder(root.right);
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}
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/* 后序遍历 */
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function postOrder(root: TreeNode | null): void {
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if (root === null) {
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return;
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}
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root.left);
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postOrder(root.right);
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list.push(root.val);
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}
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```
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=== "C"
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```c title="binary_tree_dfs.c"
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```
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=== "C#"
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```csharp title="binary_tree_dfs.cs"
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/* 前序遍历 */
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void preOrder(TreeNode? root)
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{
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if (root == null) return;
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// 访问优先级:根结点 -> 左子树 -> 右子树
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list.Add(root.val);
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preOrder(root.left);
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preOrder(root.right);
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}
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/* 中序遍历 */
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void inOrder(TreeNode? root)
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{
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if (root == null) return;
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// 访问优先级:左子树 -> 根结点 -> 右子树
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inOrder(root.left);
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list.Add(root.val);
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inOrder(root.right);
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}
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/* 后序遍历 */
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void postOrder(TreeNode? root)
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{
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if (root == null) return;
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// 访问优先级:左子树 -> 右子树 -> 根结点
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postOrder(root.left);
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postOrder(root.right);
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list.Add(root.val);
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}
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```
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!!! note
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使用循环一样可以实现前、中、后序遍历,但代码相对繁琐,有兴趣的同学可以自行实现。
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