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Posts tagged as “tree”

花花酱 LeetCode 2265. Count Nodes Equal to Average of Subtree

Given the root of a binary tree, return the number of nodes where the value of the node is equal to the average of the values in its subtree.

Note:

  • The average of n elements is the sum of the n elements divided by n and rounded down to the nearest integer.
  • subtree of root is a tree consisting of root and all of its descendants.

Example 1:

Input: root = [4,8,5,0,1,null,6]
Output: 5
Explanation: 
For the node with value 4: The average of its subtree is (4 + 8 + 5 + 0 + 1 + 6) / 6 = 24 / 6 = 4.
For the node with value 5: The average of its subtree is (5 + 6) / 2 = 11 / 2 = 5.
For the node with value 0: The average of its subtree is 0 / 1 = 0.
For the node with value 1: The average of its subtree is 1 / 1 = 1.
For the node with value 6: The average of its subtree is 6 / 1 = 6.

Example 2:

Input: root = [1]
Output: 1
Explanation: For the node with value 1: The average of its subtree is 1 / 1 = 1.

Constraints:

  • The number of nodes in the tree is in the range [1, 1000].
  • 0 <= Node.val <= 1000

Solution: Recursion

Time complexity: O(n)
Space complexity: O(h)

C++

花花酱 LeetCode 2236. Root Equals Sum of Children

You are given the root of a binary tree that consists of exactly 3 nodes: the root, its left child, and its right child.

Return true if the value of the root is equal to the sum of the values of its two children, or false otherwise.

Example 1:

Input: root = [10,4,6]
Output: true
Explanation: The values of the root, its left child, and its right child are 10, 4, and 6, respectively.
10 is equal to 4 + 6, so we return true.

Example 2:

Input: root = [5,3,1]
Output: false
Explanation: The values of the root, its left child, and its right child are 5, 3, and 1, respectively.
5 is not equal to 3 + 1, so we return false.

Constraints:

  • The tree consists only of the root, its left child, and its right child.
  • -100 <= Node.val <= 100

Solution:

Just want to check whether you know binary tree or not.

Time complexity: O(1)
Space complexity: O(1)

C++

花花酱 LeetCode 2196. Create Binary Tree From Descriptions

You are given a 2D integer array descriptions where descriptions[i] = [parenti, childi, isLefti] indicates that parenti is the parent of childi in a binary tree of unique values. Furthermore,

  • If isLefti == 1, then childi is the left child of parenti.
  • If isLefti == 0, then childi is the right child of parenti.

Construct the binary tree described by descriptions and return its root.

The test cases will be generated such that the binary tree is valid.

Example 1:

Input: descriptions = [[20,15,1],[20,17,0],[50,20,1],[50,80,0],[80,19,1]]
Output: [50,20,80,15,17,19]
Explanation: The root node is the node with value 50 since it has no parent.
The resulting binary tree is shown in the diagram.

Example 2:

Input: descriptions = [[1,2,1],[2,3,0],[3,4,1]]
Output: [1,2,null,null,3,4]
Explanation: The root node is the node with value 1 since it has no parent.
The resulting binary tree is shown in the diagram.

Constraints:

  • 1 <= descriptions.length <= 104
  • descriptions[i].length == 3
  • 1 <= parenti, childi <= 105
  • 0 <= isLefti <= 1
  • The binary tree described by descriptions is valid.

Solution: Hashtable + Recursion

  1. Use one hashtable to track the children of each node.
  2. Use another hashtable to track the parent of each node.
  3. Find the root who doesn’t have parent.
  4. Build the tree recursively from root.

Time complexity: O(n)
Space complexity: O(n)

C++

花花酱 LeetCode 222. Count Complete Tree Nodes

Given the root of a complete binary tree, return the number of the nodes in the tree.

According to Wikipedia, every level, except possibly the last, is completely filled in a complete binary tree, and all nodes in the last level are as far left as possible. It can have between 1 and 2h nodes inclusive at the last level h.

Design an algorithm that runs in less than O(n) time complexity.

Example 1:

Input: root = [1,2,3,4,5,6]
Output: 6

Example 2:

Input: root = []
Output: 0

Example 3:

Input: root = [1]
Output: 1

Constraints:

  • The number of nodes in the tree is in the range [0, 5 * 104].
  • 0 <= Node.val <= 5 * 104
  • The tree is guaranteed to be complete.

Solution: Recursion


For each node, count the height of it’s left and right subtree by going left only.

Let L = height(left) R = height(root), if L == R, which means the left subtree is perfect.
It has (2^L – 1) nodes, +1 root, we only need to count nodes of right subtree recursively.
If L != R, L must be R + 1 since the tree is complete, which means the right subtree is perfect.
It has (2^(L-1) – 1) nodes, +1 root, we only need to count nodes of left subtree recursively.

Time complexity: T(n) = T(n/2) + O(logn) = O(logn*logn)

Space complexity: O(logn)

C++

花花酱 LeetCode 2096. Step-By-Step Directions From a Binary Tree Node to Another

You are given the root of a binary tree with n nodes. Each node is uniquely assigned a value from 1 to n. You are also given an integer startValue representing the value of the start node s, and a different integer destValue representing the value of the destination node t.

Find the shortest path starting from node s and ending at node t. Generate step-by-step directions of such path as a string consisting of only the uppercase letters 'L''R', and 'U'. Each letter indicates a specific direction:

  • 'L' means to go from a node to its left child node.
  • 'R' means to go from a node to its right child node.
  • 'U' means to go from a node to its parent node.

Return the step-by-step directions of the shortest path from node s to node t.

Example 1:

Input: root = [5,1,2,3,null,6,4], startValue = 3, destValue = 6
Output: "UURL"
Explanation: The shortest path is: 3 → 1 → 5 → 2 → 6.

Example 2:

Input: root = [2,1], startValue = 2, destValue = 1
Output: "L"
Explanation: The shortest path is: 2 → 1.

Constraints:

  • The number of nodes in the tree is n.
  • 2 <= n <= 105
  • 1 <= Node.val <= n
  • All the values in the tree are unique.
  • 1 <= startValue, destValue <= n
  • startValue != destValue

Solution: Lowest common ancestor

It’s no hard to see that the shortest path is from the start node to the lowest common ancestor (LCA) of (start, end), then to the end node. The key is to find the LCA while finding paths from root to two nodes.

We can use recursion to find/build a path from root to a target node.
The common prefix of these two paths is the path from root to the LCA that we need to remove from the shortest path.
e.g.
root to start “LLRLR”
root to dest “LLLR”
common prefix is “LL”, after removing, it becomes:
LCA to start “RLR”
LCA to dest “LR”
Final path becomes “UUU” + “LR” = “UUULR”

The final step is to replace the L/R with U for the start path since we are moving up and then concatenate with the target path.

Time complexity: O(n)
Space complexity: O(n)

C++