目录
94_二叉树的中序遍历
@
描述
给定一个二叉树,返回它的中序遍历。
示例:
输入: [1,null,2,3]
1
\
2
/
3
输出: [1,3,2]
进阶: 递归算法很简单,你可以通过迭代算法完成吗?
方法一:递归
Java 代码
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode(int x) { val = x; }
* }
*/
class Solution {
public List<Integer> inorderTraversal(TreeNode root) {
List<Integer> ret = new ArrayList<>();
inorderTraversal(root, ret);
return ret;
}
private void inorderTraversal(TreeNode root, List<Integer> ret) {
if (root == null) {
return;
}
inorderTraversal(root.left, ret);
ret.add(root.val);
inorderTraversal(root.right, ret);
}
}
复杂度分析:
- 时间复杂度:\(O(n)\),其中,\(n\) 为二叉树节点的数目
- 空间复杂度:平均为 \(O(log(n))\),最坏的情况为 \(O(n)\)
Python代码
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def inorderTraversal(self, root):
"""
:type root: TreeNode
:rtype: List[int]
"""
def dfs(root, ret):
if root is None:
return
dfs(root.left, ret)
ret.append(root.val)
dfs(root.right, ret)
ret = list()
dfs(root, ret)
return ret
复杂度分析同上。
方法二:非递归
Java 代码
/**
* Definition for a binary tree node.
* public class TreeNode {
* int val;
* TreeNode left;
* TreeNode right;
* TreeNode(int x) { val = x; }
* }
*/
class Solution {
public List<Integer> inorderTraversal(TreeNode root) {
List<Integer> ret = new ArrayList<>();
Stack<TreeNode> stack = new Stack<>();
TreeNode cur = root;
while (cur != null || !stack.isEmpty()) {
while (cur != null) {
stack.push(cur);
cur = cur.left;
}
cur = stack.pop();
ret.add(cur.val);
cur = cur.right;
}
return ret;
}
}
复杂度分析:
- 时间复杂度:\(O(n)\),其中,\(n\) 为二叉树节点的数目
- 空间复杂度:\(O(h)\),其中,\(h\) 为二叉树的高度
Python 代码
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def inorderTraversal(self, root):
"""
:type root: TreeNode
:rtype: List[int]
"""
ret, stack = [], []
cur = root
while cur is not None or len(stack) > 0:
while cur is not None:
stack.append(cur)
cur = cur.left
cur = stack.pop()
ret.append(cur.val)
cur = cur.right
return ret
复杂度分析同上。