177题 Convert Sorted Array to Binary Search Tree With Minimal Height.

最小高度二叉搜索树构造
该博客讨论如何从有序数组构建最小高度的二叉搜索树。解决方案通过递归地将数组分成左右子数组来实现,每次选择中间元素作为根节点,确保平衡。

Convert Sorted Array to Binary Search Tree With Minimal Height.

Description
Given a sorted (increasing order) array, Convert it to a binary search tree with minimal height.

/**
 * Definition of TreeNode:
 * public class TreeNode {
 *     public int val;
 *     public TreeNode left, right;
 *     public TreeNode(int val) {
 *         this.val = val;
 *         this.left = this.right = null;
 *     }
 * }
 */


public class Solution {
    /*
     * @param A: an integer array
     * @return: A tree node
     */
    public TreeNode sortedArrayToBST(int[] A) {
        // write your code here
        if(A == null){
            return null; 
        }
        int n = A.length - 1 ;
        return toBST(A, 0 , n) ;
        
    }
    public TreeNode toBST(int[] A , int L , int R){
        if(L > R){
          return null ;
        }
        int mid = (L + R) >>>1 ;
        TreeNode left = toBST(A, L , mid-1);
        TreeNode curt = new TreeNode(A[mid]);
        curt.left = left ;
        TreeNode right = toBST(A, mid+1 , R);
        curt.right = right ;
        return curt ;
    }
}
【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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