Maximum Width of Binary Tree

Maximum Width of Binary Tree

Leetcode Daily Challenge (20th April, 2023)

Problem Statement:-

Given the root of a binary tree, return the maximum width of the given tree.

The maximum width of a tree is the maximum width among all levels.

The width of one level is defined as the length between the end-nodes (the leftmost and rightmost non-null nodes), where the null nodes between the end-nodes that would be present in a complete binary tree extending down to that level are also counted into the length calculation.

It is guaranteed that the answer will in the range of a 32-bit signed integer.

Link: https://leetcode.com/problems/maximum-width-of-binary-tree/description/

Problem Explanation with examples:-

Example 1

Input: root = [1,3,2,5,3,null,9]
Output: 4
Explanation: The maximum width exists in the third level with length 4 (5,3,null,9).

Example 2

Input: root = [1,3,2,5,null,null,9,6,null,7]
Output: 7
Explanation: The maximum width exists in the fourth level with length 7 (6,null,null,null,null,null,7).

Example 3

Input: root = [1,3,2,5]
Output: 2
Explanation: The maximum width exists in the second level with length 2 (3,2).

Constraints

  • The number of nodes in the tree is in the range [1, 3000].

  • -100 <= Node.val <= 100

Intuition:-

  • BFS will be used to traverse the tree level by level.

  • The width of the tree at a level is the difference between the last node and the first node.

  • The first node is the node that is encountered first at a level.

  • The last node is the node that is encountered last at a level.

  • ans variable will be used to store the maximum width of the tree.

  • We don't need the node values so we will store the ordered nodes numbers in the nodes.

Solution:-

  • Initialize ans to 0.

  • Initialize a queue with the root node, its number and level. The root node will have number 1 and level 0.

  • Initialize prevLvl to 0 and prevNum to 1.

  • While the queue is not empty:

  • Pop the first node from the queue.

  • If the level of the node is greater than the previous level:

  • Update prevLvl to the current level. Update prevNum to the current node number.

  • Update ans to the maximum of ans and the difference between the current node number and the previous node number.

  • If the left child of the node is not null, append it to the queue with its number, 2*current node number and level+1.

  • If the right child of the node is not null, append it to the queue with its number, 2*current node number+1 and level+1.

  • Return ans.

Code:-

JAVA Solution

class Solution {
    public int widthOfBinaryTree(TreeNode root) {
        Deque<TreeNode> queue=new ArrayDeque<>();
        root.val=0;
        queue.add(root);
        return bfs(queue);
    }

    public int bfs(Deque<TreeNode> queue){
        int maxWidth = 1;
        while(!queue.isEmpty()){
            int s=queue.size();
            int left = queue.peek().val;
            int right = left;
            for(int i=0;i<s;i++){
                TreeNode node=queue.removeFirst();           

                if(node.left!=null){
                    node.left.val = node.val * 2 - 1;
                    queue.add(node.left);
                }
                if(node.right!=null){
                    node.right.val = node.val * 2;
                    queue.add(node.right);
                }
                if(i==s-1)
                    right=node.val;
            }
            maxWidth=Math.max(maxWidth,right-left+1);
        }
        return maxWidth;
    }
}

Python Solution

class Solution:
    def widthOfBinaryTree(self, root: Optional[TreeNode]) -> int:
        ans = 0
        q = deque([[root,1,0]])
        prevLvl = 0
        prevNum = 1

        while q:
            node, num, lvl = q.popleft()

            if lvl > prevLvl:
                prevLvl = lvl
                prevNum = num

            ans = max(ans, num - prevNum + 1)

            if node.left:
                q.append([node.left, 2*num, lvl+1])
            if node.right:
                q.append([node.right, 2*num+1, lvl+1])
        return ans

Complexity Analysis:-

TIME:-

The time complexity of the given Python code is O(n) where n is the number of nodes in the tree. We will traverse the tree once.

SPACE:-

The space complexity of the code is also O(n) where n is the number of nodes in the tree. We will store the nodes in the queue.

References:-

Connect with me:-

Did you find this article valuable?

Support Leeting-LCS by becoming a sponsor. Any amount is appreciated!