|
| 1 | +# 题目描述(中等难度) |
| 2 | + |
| 3 | + |
| 4 | + |
| 5 | +二叉树的先序遍历。 |
| 6 | + |
| 7 | +# 思路分析 |
| 8 | + |
| 9 | +之前做过 [94 题](https://leetcode.wang/leetCode-94-Binary-Tree-Inorder-Traversal.html) 的中序遍历,先序遍历的话代码可以直接拿过来用,只需要改一改 `list.add` 的位置。 |
| 10 | + |
| 11 | +# 解法一 递归 |
| 12 | + |
| 13 | +递归很好理解了,代码也是最简洁的。 |
| 14 | + |
| 15 | +```java |
| 16 | +public List<Integer> preorderTraversal(TreeNode root) { |
| 17 | + List<Integer> list = new ArrayList<>(); |
| 18 | + preorderTraversalHelper(root, list); |
| 19 | + return list; |
| 20 | +} |
| 21 | + |
| 22 | +private void preorderTraversalHelper(TreeNode root, List<Integer> list) { |
| 23 | + if (root == null) { |
| 24 | + return; |
| 25 | + } |
| 26 | + list.add(root.val); |
| 27 | + preorderTraversalHelper(root.left, list); |
| 28 | + preorderTraversalHelper(root.right, list); |
| 29 | +} |
| 30 | +``` |
| 31 | + |
| 32 | +# 解法二 栈 |
| 33 | + |
| 34 | +第一种思路就是利用栈去模拟上边的递归。 |
| 35 | + |
| 36 | +```java |
| 37 | +public List<Integer> preorderTraversal(TreeNode root) { |
| 38 | + List<Integer> list = new ArrayList<>(); |
| 39 | + Stack<TreeNode> stack = new Stack<>(); |
| 40 | + TreeNode cur = root; |
| 41 | + while (cur != null || !stack.isEmpty()) { |
| 42 | + if (cur != null) { |
| 43 | + list.add(cur.val); |
| 44 | + stack.push(cur); |
| 45 | + cur = cur.left; //考虑左子树 |
| 46 | + }else { |
| 47 | + //节点为空,就出栈 |
| 48 | + cur = stack.pop(); |
| 49 | + //考虑右子树 |
| 50 | + cur = cur.right; |
| 51 | + } |
| 52 | + } |
| 53 | + return list; |
| 54 | +} |
| 55 | +``` |
| 56 | + |
| 57 | +第二种思路的话,我们还可以将左右子树分别压栈,然后每次从栈里取元素。需要注意的是,因为我们应该先访问左子树,而栈的话是先进后出,所以我们压栈先压右子树。 |
| 58 | + |
| 59 | +```java |
| 60 | +public List<Integer> preorderTraversal(TreeNode root) { |
| 61 | + List<Integer> list = new ArrayList<>(); |
| 62 | + if (root == null) { |
| 63 | + return list; |
| 64 | + } |
| 65 | + Stack<TreeNode> stack = new Stack<>(); |
| 66 | + stack.push(root); |
| 67 | + while (!stack.isEmpty()) { |
| 68 | + TreeNode cur = stack.pop(); |
| 69 | + if (cur == null) { |
| 70 | + continue; |
| 71 | + } |
| 72 | + list.add(cur.val); |
| 73 | + stack.push(cur.right); |
| 74 | + stack.push(cur.left); |
| 75 | + } |
| 76 | + return list; |
| 77 | +} |
| 78 | +``` |
| 79 | + |
| 80 | +# 解法三 Morris Traversal |
| 81 | + |
| 82 | +上边的两种解法,空间复杂度都是 `O(n)`,利用 Morris Traversal 可以使得空间复杂度变为 `O(1)`。 |
| 83 | + |
| 84 | +它的主要思想就是利用叶子节点的左右子树是 `null` ,所以我们可以利用这个空间去存我们需要的节点,详细的可以参考 [94 题](https://leetcode.wang/leetCode-94-Binary-Tree-Inorder-Traversal.html) 中序遍历。 |
| 85 | + |
| 86 | +```java |
| 87 | +public List<Integer> preorderTraversal(TreeNode root) { |
| 88 | + List<Integer> list = new ArrayList<>(); |
| 89 | + TreeNode cur = root; |
| 90 | + while (cur != null) { |
| 91 | + //情况 1 |
| 92 | + if (cur.left == null) { |
| 93 | + list.add(cur.val); |
| 94 | + cur = cur.right; |
| 95 | + } else { |
| 96 | + //找左子树最右边的节点 |
| 97 | + TreeNode pre = cur.left; |
| 98 | + while (pre.right != null && pre.right != cur) { |
| 99 | + pre = pre.right; |
| 100 | + } |
| 101 | + //情况 2.1 |
| 102 | + if (pre.right == null) { |
| 103 | + list.add(cur.val); |
| 104 | + pre.right = cur; |
| 105 | + cur = cur.left; |
| 106 | + } |
| 107 | + //情况 2.2 |
| 108 | + if (pre.right == cur) { |
| 109 | + pre.right = null; //这里可以恢复为 null |
| 110 | + cur = cur.right; |
| 111 | + } |
| 112 | + } |
| 113 | + } |
| 114 | + return list; |
| 115 | +} |
| 116 | +``` |
| 117 | + |
| 118 | +# 总 |
| 119 | + |
| 120 | +和 [94 题](https://leetcode.wang/leetCode-94-Binary-Tree-Inorder-Traversal.html) 没什么差别,解法三利用已有空间去存东西,从而降低空间复杂度的思想经常用到。 |
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