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二叉树解题的思维模式分两类:
无论使用哪种思维模式,你都需要思考:如果单独抽出一个二叉树节点,它需要做什么事情?需要在什么时候(前/中/后序位置)做?其他的节点不用你操心,递归函数会帮你在所有节点上执行相同的操作。
二叉树数据结构定义:
- public class TreeNode {
- int val;
- TreeNode left;
- TreeNode right;
-
- public TreeNode() {
- }
-
- public TreeNode(int val) {
- this.val = val;
- }
-
- public TreeNode(int val, TreeNode left, TreeNode right) {
- this.val = val;
- this.left = left;
- this.right = right;
- }
- }

思路
代码
- public class LevelOrder {
-
- public List<List<Integer>> levelOrder(TreeNode root) {
- List<List<Integer>> res = new ArrayList<>();
- Queue<TreeNode> queue = new LinkedList<>();
- if (root != null) {
- queue.add(root);
- }
- while (!queue.isEmpty()) {
- int n = queue.size();
- List<Integer> level = new ArrayList<>();
- for (int i = 0; i < n; i++) {
- TreeNode node = queue.poll();
- level.add(node.val);
- if (node.left != null) {
- queue.add(node.left);
- }
- if (node.right != null) {
- queue.add(node.right);
- }
- }
- res.add(level);
- }
- return res;
- }
-
- }

复杂度
思路
代码
- public class LowestCommonAncestor {
-
- public TreeNode lowestCommonAncestor(TreeNode root, TreeNode p, TreeNode q) {
- if (root == null || root == p || root == q) {
- return root;
- }
- TreeNode left = lowestCommonAncestor(root.left, p, q);
- TreeNode right = lowestCommonAncestor(root.right, p, q);
-
- if (left == null && right == null) {
- return null;
- } else if (left == null && right != null) {
- return right;
- } else if (left != null && right == null) {
- return left;
- } else {
- return root;
- }
- }
-
- }

复杂度
思路
代码
- import java.util.LinkedList;
- import java.util.List;
- import java.util.Queue;
-
- public class ZigzagLevelOrder {
-
- public List<List<Integer>> zigzagLevelOrder(TreeNode root) {
- List<List<Integer>> res = new LinkedList<>();
- if (root == null) {
- return res;
- }
- Queue<TreeNode> queue = new LinkedList<>();
- queue.offer(root);
- boolean flag = true; // 为 true 时从右边开始遍历,false 时从左边开始
- while (!queue.isEmpty()) {
- int size = queue.size();
- LinkedList<Integer> level = new LinkedList<>();
- for (int i = 0; i < size; i++) {
- TreeNode node = queue.poll();
- if (flag) {
- level.addLast(node.val);
- } else {
- level.addFirst(node.val);
- }
- if (node.left != null) {
- queue.offer(node.left);
- }
- if (node.right != null) {
- queue.offer(node.right);
- }
- }
- flag = !flag;
- res.add(level);
- }
- return res;
- }
-
- }

复杂度
思路
代码
- class Solution {
- int res = Integer.MIN_VALUE;
-
- public int maxPathSum(TreeNode root) {
- traverse(root);
- return res;
- }
-
- // 返回当前节点能为父亲提供的贡献
- private int traverse(TreeNode root) {
- if (root == null) {
- return 0;
- }
-
- int left = traverse(root.left);
- int right = traverse(root.right);
- res = Math.max(res, root.val + left + right);
- int max = Math.max(root.val + left, root.val + right); // 计算当前节点能为父亲提供的最大贡献
- return max < 0 ? 0 : max;
- }
-
- }

复杂度
思路
中序遍历的过程中收集节点的值。
代码
- import java.util.ArrayList;
- import java.util.List;
-
- public class InorderTraversal {
-
- public List<Integer> inorderTraversal(TreeNode root) {
- List<Integer> list = new ArrayList<>();
- traverse(root, list);
- return list;
- }
-
- private void traverse(TreeNode root, List list) {
- if (root == null) {
- traverse(root.left, list);
- list.add(root.val);
- traverse(root.right, list);
- }
- }
-
- }

复杂度
思路
BFS每一层最后一个元素 or DFS 先访问每一层的右边的元素。
代码
- import java.util.ArrayList;
- import java.util.LinkedList;
- import java.util.List;
- import java.util.Queue;
-
- public class RightSideView {
- private List<Integer> res = new ArrayList<>();
-
- public List<Integer> rightSideViewBFS(TreeNode root) {
- List<Integer> res = new ArrayList<>();
- if (root == null) {
- return res;
- }
- Queue<TreeNode> queue = new LinkedList<>();
- queue.offer(root);
- while (!queue.isEmpty()) {
- int size = queue.size();
- for (int i = 0; i < size; i++) {
- TreeNode node = queue.poll();
- if (node.left != null) {
- queue.offer(node.left);
- }
- if (node.right != null) {
- queue.offer(node.right);
- }
- if (i == size - 1) {
- res.add(node.val);
- }
- }
- }
- return res;
- }
-
- public List<Integer> rightSideViewDFS(TreeNode root) {
- DFS(root, 0);
- return res;
- }
-
- private void DFS(TreeNode root, int depth) {
- if (root == null) {
- return;
- }
- if (depth == res.size()) {
- res.add(root.val);
- }
- depth++;
- DFS(root.right, depth);
- DFS(root.left, depth);
- }
-
- }

复杂度
思路
代码
- import java.util.HashMap;
- import java.util.Map;
-
- public class BuildTree {
- private Map<Integer, Integer> map = new HashMap<>();
-
- public TreeNode buildTree(int[] preorder, int[] inorder) {
- for (int i = 0; i < inorder.length; i++) {
- map.put(inorder[i], i); // 记录中序序列每一个值的位置,用来划分左右子树的节点数量
- }
- return traverse(preorder, 0, preorder.length - 1,
- inorder, 0, inorder.length - 1);
- }
-
- private TreeNode traverse(int[] preorder, int preorderLeft, int preorderRight,
- int[] inorder, int inorderLeft, int inorderRight) {
- if (preorderLeft > preorderRight || inorderLeft > inorderRight) {
- return null;
- }
- int rootInInorderLocation = map.get(preorder[preorderLeft]);
- int sizeLeftSubtree = rootInInorderLocation - inorderLeft;
- TreeNode root = new TreeNode(preorder[preorderLeft]);
- root.left = traverse(preorder, preorderLeft + 1, preorderLeft + sizeLeftSubtree,
- inorder, inorderLeft, rootInInorderLocation - 1);
- root.right = traverse(preorder, preorderLeft + sizeLeftSubtree + 1, preorderRight,
- inorder, rootInInorderLocation + 1, inorderRight);
- return root;
- }
-
- }

复杂度
思路
DFS
代码
- public class SumNumbers {
-
- public int sumNumbers(TreeNode root) {
- return DFS(root, 0);
- }
-
- private int DFS(TreeNode root, int preSum) {
- if (root == null) {
- return 0;
- }
- int sum = preSum * 10 + root.val;
- if (root.left == null && root.right == null) {
- return sum;
- } else {
- return DFS(root.left, sum) + DFS(root.right, sum);
- }
- }
-
- }

复杂度
思路
后序遍历更新当前节点左右子树的最大深度。
代码
- class Solution {
-
- public int maxDepth(TreeNode root) {
- if (root == null) {
- return 0;
- }
-
- int leftHeight = maxDepth(root.left);
- int rightHeight = maxDepth(root.right);
- return Math.max(leftHeight, rightHeight) + 1;
- }
-
- }
复杂度
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