109. Convert Sorted List to Binary Search Tree

本文介绍了一种将升序链表转换为高度平衡的二叉搜索树的方法。通过将链表转换为数组,利用数组中点作为根节点递归构建平衡二叉搜索树。此方法避免了多次遍历链表,提高了效率。

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Given a singly linked list where elements are sorted in ascending order, convert it to a height balanced BST.

这个题目和 108 很像,只是108本身就是有序数组转化为平衡二叉树,这里是链表转化为平衡二叉树,所以首先的想法就是把有序链表转化为有序数组,在使用 108 的函数得到答案。

这个题目做完后觉得不太理想,于是参考了别人的算法,基本都是要先找到链表的长度,再使用递归的,所以我的这种方法,除了占用了一个数组长度的空间,在递归时,不需要重复查找每一项,算是比较好了。

/**
 * Definition for singly-linked list.
 * function ListNode(val) {
 *     this.val = val;
 *     this.next = null;
 * }
 */
/**
 * Definition for a binary tree node.
 * function TreeNode(val) {
 *     this.val = val;
 *     this.left = this.right = null;
 * }
 */
/**
 * @param {ListNode} head
 * @return {TreeNode}
 */
var sortedListToBST = function(head) {
    var nums=[];
    var i=0;
    var myList=function(head){
        if(head) {
            nums[i++]=head.val;
            myList(head.next);
        }
    };
    myList(head);

    var sortedArrayToBST = function(nums) {
    if(nums.length==1)return new TreeNode(nums[0]);
    if(nums.length===0)return null;
    var halfL=Math.floor(nums.length/2);
    var root= new TreeNode(nums[halfL]);
    root.left=sortedArrayToBST(nums.slice(0,halfL));
    root.right=sortedArrayToBST(nums.slice(halfL+1));
    return root;
};

    return sortedArrayToBST(nums);
};
【Solution】 To convert a binary search tree into a sorted circular doubly linked list, we can use the following steps: 1. Inorder traversal of the binary search tree to get the elements in sorted order. 2. Create a doubly linked list and add the elements from the inorder traversal to it. 3. Make the list circular by connecting the head and tail nodes. 4. Return the head node of the circular doubly linked list. Here's the Python code for the solution: ``` class Node: def __init__(self, val): self.val = val self.prev = None self.next = None def tree_to_doubly_list(root): if not root: return None stack = [] cur = root head = None prev = None while cur or stack: while cur: stack.append(cur) cur = cur.left cur = stack.pop() if not head: head = cur if prev: prev.right = cur cur.left = prev prev = cur cur = cur.right head.left = prev prev.right = head return head ``` To verify the accuracy of the code, we can use the following test cases: ``` # Test case 1 # Input: [4,2,5,1,3] # Output: # Binary search tree: # 4 # / \ # 2 5 # / \ # 1 3 # Doubly linked list: 1 <-> 2 <-> 3 <-> 4 <-> 5 # Doubly linked list in reverse order: 5 <-> 4 <-> 3 <-> 2 <-> 1 root = Node(4) root.left = Node(2) root.right = Node(5) root.left.left = Node(1) root.left.right = Node(3) head = tree_to_doubly_list(root) print("Binary search tree:") print_tree(root) print("Doubly linked list:") print_list(head) print("Doubly linked list in reverse order:") print_list_reverse(head) # Test case 2 # Input: [2,1,3] # Output: # Binary search tree: # 2 # / \ # 1 3 # Doubly linked list: 1 <-> 2 <-> 3 # Doubly linked list in reverse order: 3 <-> 2 <-> 1 root = Node(2) root.left = Node(1) root.right = Node(3) head = tree_to_doubly_list(root) print("Binary search tree:") print_tree(root) print("Doubly linked list:") print_list(head) print("Doubly linked list in reverse order:") print_list_reverse(head) ``` The output of the test cases should match the expected output as commented in the code.
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