Nodes at a distance k in binary tree - algorithm

You are given a function printKDistanceNodes which takes in a root node of a binary tree, a start node and an integer K. Complete the function to print the value of all the nodes (one-per-line) which are a K distance from the given start node in sorted order. Distance can be upwards or downwards.

private void printNodeAtN(Node root, Node start, int k) {
if (root != null) {
// calculate if the start is in left or right subtree - if start is
// root this variable is null
Boolean left = isLeft(root, start);
int depth = depth(root, start, 0);
if (depth == -1)
return;
printNodeDown(root, k);
if (root == start)
return;
if (left) {
if (depth > k) {
// print the nodes at depth-k level in left tree
printNode(depth - k - 1, root.left);
} else if (depth < k) {
// print the nodes at right tree level k-depth
printNode(k - depth - 1, root.right);
} else {
System.out.println(root.data);
}
} else {
// similar if the start is in right subtree
if (depth > k) {
// print the nodes at depth-k level in left tree
printNode(depth - k - 1, root.right);
} else if (depth < k) {
// print the nodes at right tree level k-depth
printNode(k - depth - 1, root.left);
} else {
System.out.println(root.data);
}
}
}
}
// print the nodes at depth - "level" from root
void printNode(int level, Node root) {
if (level == 0 && root != null) {
System.out.println(root.data);
} else {
printNode(level - 1, root.left);
printNode(level - 1, root.right);
}
}
// print the children of the start
void printNodeDown(Node start, int k) {
if (start != null) {
if (k == 0) {
System.out.println(start.data);
}
printNodeDown(start.left, k - 1);
printNodeDown(start.right, k - 1);
}
}
private int depth(Node root, Node node, int d) {
if (root == null)
return -1;
if (root != null && node == root) {
return d;
} else {
int left = depth(root.left, node, d + 1);
int right = depth(root.right, node, d + 1);
if (left > right)
return left;
else
return right;
}
}

There is at most one node at distance K which upwards - just start from the start node and move up along parents for K steps. Add this to a sorted data structure.
Then you need to add the downward nodes. To do that you can do a BFS with queue, where you store the depth together with the node when you insert it in the queue (the starting node is at level 0, it's children at level 1 and so on). Then when you pop the nodes if they are at level K add them to the sorted data structure. when you start poping nodes at level K+1 you can stop.
Finally print the nodes from the sorted data structure (they will be sorted).
EDIT: If there is no parent pointer:
Write a recursive function int Go(Node node), which returns the depth of the start node with respect to the passed in node and -1 if the subtree of node doesn't contain start. The function will find the K-th parent as a side effect. Pseudo code:
static Node KthParent = null;
static Node start = ...;
static int K = ...;
int Go(Node node) {
if (node == start) return 0;
intDepth = -1;
if(node.LeftChild != null) {
int leftDepth = Go(node.LeftChild);
if(leftDepth >= 0) intDepth = leftDepth+1;
}
if (intDepth < 0 && node.rightChild != null) {
int rightDepth = Go(node.RightChild);
if(rightDepth >= 0) intDepth = rightDepth+1;
}
if(intDepth == K) KthParent = node;
return intDepth;
}

private static int printNodeAtK(Node root, Node start, int k, boolean found){
if(root != null){
if(k == 0 && found){
System.out.println(root.data);
}
if(root==start || found == true){
int leftd = printNodeAtK(root.left, start, k-1, true);
int rightd = printNodeAtK(root.right,start,k-1,true);
return 1;
}else{
int leftd = printNodeAtK(root.left, start, k, false);
int rightd = printNodeAtK(root.right,start,k,false);
if(leftd == k || rightd == k){
System.out.println(root.data);
}
if(leftd != -1 && leftd > rightd){
return leftd+1;
}else if(rightd != -1 && rightd>leftd){
return rightd+1;
}else{
return -1;
}
}
}
return -1;
}

struct node{
int data;
node* left;
node* right;
bool printed;
};
void print_k_dist(node** root,node** p,int k,int kmax);
void reinit_printed(node **root);
void print_k_dist(node** root,node **p,int k,int kmax)
{
if(*p==NULL) return;
node* par=parent(root,p);
if(k<=kmax &&(*p)->printed==0)
{
cout<<(*p)->data<<" ";
(*p)->printed=1;
k++;
print_k_dist(root,&par,k,kmax);
print_k_dist(root,&(*p)->left,k,kmax);
print_k_dist(root,&(*p)->right,k,kmax);
}
else
return;
}
void reinit_printed(node **root)
{
if(*root==NULL) return;
else
{
(*root)->printed=0;
reinit_printed(&(*root)->left);
reinit_printed(&(*root)->right);
}
}

typedef struct node
{
int data;
struct node *left;
struct node *right;
}node;
void printkdistanceNodeDown(node *n, int k)
{
if(!n)
return ;
if(k==0)
{
printf("%d\n",n->data);
return;
}
printkdistanceNodeDown(n->left,k-1);
printkdistanceNodeDown(n->right,k-1);
}
void printkdistanceNodeDown_fromUp(node* target ,int *k)
{
if(!target)
return ;
if(*k==0)
{
printf("%d\n",target->data);
return;
}
else
{
int val=*k;
printkdistanceNodeDown(target,val-1);
}
}
int printkdistanceNodeUp(node* root, node* n , int k)
{
if(!root)
return 0;
if(root->data==n->data)
return 1;
int pl=printkdistanceNodeUp(root->left,n,k);
int pr=printkdistanceNodeUp(root->right,n,k);
if(pl )
{
k--;
if(k==0)
printf("%d\n",root->data);
else
{
printkdistanceNodeDown_fromUp(root->right,k);
printkdistanceNodeDown_fromUp(root->left,k-1);
}
return 1;
}
if(pr )
{
k--;
if(k==0)
printf("%d\n",root->data);
else
{
printkdistanceNodeDown_fromUp(root->left,k);
printkdistanceNodeDown_fromUp(root->right,k-1);
}
return 1;
}
return 0;
}
void printkdistanceNode(node* root, node* n , int k )
{
if(!root)
return ;
int val=k;
printkdistanceNodeUp(root,n,k);
printkdistanceNodeDown(n,val);
}
caller function: printkdistanceNode(root,n,k);
The output will print all the nodes at a distance k from given node upward and downward.

Here in this code PrintNodesAtKDistance will first try to find the required node.
if(root.value == requiredNode)
When we find the desired node we print all the child nodes at the distance K from this node.
Now our task is to print all nodes which are in other branches(Go up and print). We return -1 till we didn't find our desired node. As we get our desired node we get lPath or rPath >=0 . Now we have to print all nodes which are at distance (lPath/rPath) -1
public void PrintNodes(Node Root, int requiredNode, int iDistance)
{
PrintNodesAtKDistance(Root, requiredNode, iDistance);
}
public int PrintNodesAtKDistance(Node root, int requiredNode, int iDistance)
{
if ((root == null) || (iDistance < 0))
return -1;
int lPath = -1, rPath = -1;
if(root.value == requiredNode)
{
PrintChildNodes(root, iDistance);
return iDistance - 1;
}
lPath = PrintNodesAtKDistance(root.left, requiredNode, iDistance);
rPath = PrintNodesAtKDistance(root.right, requiredNode, iDistance);
if (lPath > 0)
{
PrintChildNodes(root.right, lPath - 1);
return lPath - 1;
}
else if(lPath == 0)
{
Debug.WriteLine(root.value);
}
if(rPath > 0)
{
PrintChildNodes(root.left, rPath - 1);
return rPath - 1;
}
else if (rPath == 0)
{
Debug.WriteLine(root.value);
}
return -1;
}
public void PrintChildNodes(Node aNode, int iDistance)
{
if (aNode == null)
return;
if(iDistance == 0)
{
Debug.WriteLine(aNode.value);
}
PrintChildNodes(aNode.left, iDistance - 1);
PrintChildNodes(aNode.right, iDistance - 1);
}

Here is complete java program . Inspired from geeksforgeeks Algorith
// Java program to print all nodes at a distance k from given node
class BinaryTreePrintKDistance {
Node root;
/*
* Recursive function to print all the nodes at distance k in tree (or
* subtree) rooted with given root.
*/
void printKDistanceForDescendant(Node targetNode, int currentDist,
int inputDist) {
// Base Case
if (targetNode == null || currentDist > inputDist)
return;
// If we reach a k distant node, print it
if (currentDist == inputDist) {
System.out.print(targetNode.data);
System.out.println("");
return;
}
++currentDist;
// Recur for left and right subtrees
printKDistanceForDescendant(targetNode.left, currentDist, inputDist);
printKDistanceForDescendant(targetNode.right, currentDist, inputDist);
}
public int printkdistance(Node targetNode, Node currentNode,
int inputDist) {
if (currentNode == null) {
return -1;
}
if (targetNode.data == currentNode.data) {
printKDistanceForDescendant(currentNode, 0, inputDist);
return 0;
}
int ld = printkdistance(targetNode, currentNode.left, inputDist);
if (ld != -1) {
if (ld + 1 == inputDist) {
System.out.println(currentNode.data);
} else {
printKDistanceForDescendant(currentNode.right, 0, inputDist
- ld - 2);
}
return ld + 1;
}
int rd = printkdistance(targetNode, currentNode.right, inputDist);
if (rd != -1) {
if (rd + 1 == inputDist) {
System.out.println(currentNode.data);
} else {
printKDistanceForDescendant(currentNode.left, 0, inputDist - rd
- 2);
}
return rd + 1;
}
return -1;
}
// Driver program to test the above functions
#SuppressWarnings("unchecked")
public static void main(String args[]) {
BinaryTreePrintKDistance tree = new BinaryTreePrintKDistance();
/* Let us construct the tree shown in above diagram */
tree.root = new Node(20);
tree.root.left = new Node(8);
tree.root.right = new Node(22);
tree.root.left.left = new Node(4);
tree.root.left.right = new Node(12);
tree.root.left.right.left = new Node(10);
tree.root.left.right.right = new Node(14);
Node target = tree.root.left;
tree.printkdistance(target, tree.root, 2);
}
static class Node<T> {
public Node left;
public Node right;
public T data;
Node(T data) {
this.data = data;
}
}
}

Related

Algorithm to print the total sum of all the path

Giving you a binary tree which defined as follows:
public class TreeNode {
public int val;
public TreeNode left, right;
public TreeNode(int val) {
this.val = val;
this.left = this.right = null;
}
}
print the total sum of all the path, a path is defined as the line from the root node to any leaf node
For example:
4 5 6 7 8 10 # # # # 9
should return:
path1: 4 + 5 + 7
path2: 4 + 5 + 8 + 9
path3: 4 + 6 + 10
so the total path sum should be: path1 + path2 + path3
how can we solve the problem by using
recursive
non-recursive
I have find a solution by using non-recursive, but have some little problem about recursive method
Non-Recursive Method:
/**
* non-recursive
*/
public static int pathSum2(TreeNode root) {
int sum = 0;
if (root == null) {
return sum;
}
Queue<TreeNode> queueNode = new LinkedList<TreeNode>();
Queue<Integer> queueSum = new LinkedList<Integer>();
queueNode.add(root);
queueSum.add(root.val);
while (!queueNode.isEmpty()) {
TreeNode node = queueNode.poll();
int temp = queueSum.poll();
if (node.left == null && node.right == null) {
sum += temp;
}
if (node.left != null) {
queueNode.add(node.left);
queueSum.add(node.left.val + temp);
}
if (node.right != null) {
queueNode.add(node.right);
queueSum.add(node.right.val + temp);
}
}
return sum;
}
Recursive Method:
/**
* recursive
*/
public List<List<Integer>> pathSum(TreeNode root) {
List<List<Integer>> rst = new ArrayList<List<Integer>>();
helper(rst, new ArrayList<Integer>(), root);
return rst;
}
public void helper(List<List<Integer>> rst, ArrayList<Integer> list,
TreeNode root) {
if (root == null) {
return;
}
list.add(root.val);
if (root.left == null && root.right == null) {
rst.add(new ArrayList<Integer>(list));
}
helper(rst, list, root.left);
helper(rst, list, root.right);
list.remove(list.size() - 1);
}
but in this way, what I have output is all the path, what if I want to get the total sum of those path?
One way to get the answer is iterator the List> and get the answer but I think it's inefficient. How can we deal with this just in the helper() method because for the sum, java is just pass-by-value
I have find a solution by using recursive
/**
* recursive
*/
public List<List<Integer>> pathSum(TreeNode root, int sum) {
List<List<Integer>> rst = new ArrayList<List<Integer>>();
helper(rst, new ArrayList<Integer>(), root, sum);
return rst;
}
public void helper(List<List<Integer>> rst, ArrayList<Integer> list,
TreeNode root, int sum) {
if (root == null) {
return;
}
list.add(root.val);
if (root.left == null && root.right == null) {
rst.add(new ArrayList<Integer>(list));
}
helper(rst, list, root.left, sum - root.val);
helper(rst, list, root.right, sum - root.val);
list.remove(list.size() - 1);
}

How to convert a Ternary expression to a Binary tree structure?

I came across this problem that has Ternary expression (a?b:c) and needs the ternary expression to be converted into a Binary tree structure.
a?b:c
a
/ \
b c
a?b?c:d:e
a
/ \
b e
/ \
c d
My approach using a Binary tree implemented using a array :-
Parent resides at - i
Left child - 2i
Right child - 2i+1
Start parsing the ternary expression the first character will form the root node so it will be at position 1 in the array. If the next character is a '?' then the characters that follow will be its children so left child (b in this case will be at position 2). If the next character is a ":" then we have found the right child (c in the first case) so we add that to position 3.
In the second case we face a "?" after b so whatever follows will be its children and will be added to 2j and 2j+1 respectively where j is the position of b in the array.Now we face a ":" we check the parent of the current child if it has two children then we backtrack and check the previous node until we find a node that is missing a right child.
Is there any other way to do this? Hope I have been articulate enough.
Below is my solution which has been tested thoroughly.
class TreeNode {
char c;
TreeNode left;
TreeNode right;
TreeNode(char c) {
this.c = c;
left = null;
right = null;
}
}
public TreeNode tenaryToTree(String s) {
if (s.length() == 0) {
return null;
}
TreeNode root = new TreeNode(s.charAt(0));
Stack<TreeNode> stack = new Stack<>();
stack.push(root);
for (int i = 1; i < s.length(); i++) {
if (s.charAt(i) == '?') {
TreeNode node = stack.peek();
node.left = new TreeNode(s.charAt(i + 1));
stack.push(node.left);
} else if (s.charAt(i) == ':') {
stack.pop();
TreeNode node = stack.pop();
node.right = new TreeNode(s.charAt(i + 1));
stack.push(node.right);
}
}
return root;
}
This one would be without using parent node. But using stack.
public NodeC convertTtoBT (char[] values) {
char xx = values[0];
NodeC n = new NodeC(xx);
Stack<NodeC> a = new Stack<NodeC>();
for (int i = 1; i < values.length; i += 2) {
if (values[i] == '?') {
n.left = new NodeC (values[i + 1]);
a.add(n);
n = n.left;
}
else if (values[i] == ':') {
n = a.pop();
while (n.right != null) {
n = a.pop();
}
n.right = new NodeC (values[i + 1]);
a.add(n);
n = n.right;
}
}
return n;
}
Walk through the expression from right to left, pushing any letters as nodes to the stack. If you see '?', then instead of pushing the next letter, take it as the root, pop two last nodes from the stack as left and right root's children, and push the root back into the stack.
public TreeNode ternaryToTree(char[] exp) {
LinkedList<TreeNode> stack = new LinkedList<TreeNode>();
for (int i = exp.length-1; i >= 0; i--) {
if (exp[i] == ':') continue;
if (exp[i] == '?') {
TreeNode node = new TreeNode(exp[--i]);
node.left = stack.pop();
node.right = stack.pop();
stack.push(node);
} else {
stack.push(new TreeNode(exp[i]));
}
}
return stack.isEmpty() ? null : stack.pop();
}
if this a?b:c?d?e:f:g?h:i?j:k is the ternary expression then tree would be like this
a
/ \
b c
/ \
d g
/ \ / \
e f h i
/ \
j k
Below is the Java solution...
private static TreeNode convertTernaryExpression(String s)
{
Stack<TreeNode> stack = new Stack<>();
int length = s.length();
int index = 0;
TreeNode rootNode = null;
while(index < length)
{
while(s.charAt(index) != ':')
{
if(s.charAt(index) == '?' && stack.peek().right != null)
{
TreeNode temp = stack.pop();
if(rootNode == null)
{
rootNode = temp;
}
stack.push(temp.right);
}
stack.push(new TreeNode(s.charAt(index++)));
}
TreeNode left = stack.pop();
TreeNode questionMark = stack.pop();
TreeNode root = stack.pop();
index++;
TreeNode right = new TreeNode(s.charAt(index++));
root.left = left;
root.right = right;
stack.push(root);
}
if(rootNode == null)
{
return stack.pop();
}
else
{
return rootNode;
}
}
class TreeNode
{
TreeNode left;
TreeNode right;
char val;
public TreeNode(char val)
{
this.val = val;
this.left = null;
this.right = null;
}
}
I came up with something like this using trees. Not tested thoroughly:
When I see a '?', it's my left child, so add to my left and go left.
If I see ':', then:
Go to my parent
If right is not null and parent is not not null, keep going to my parent
My right child is empty. Add right. Go to right.
Note: You will never go back to the root if it has a right child.
public NodeC convertTtoBT (char[] values) {
NodeC n = new NodeC (values[0]);
for (int i = 1; i < values.length; i += 2) {
if (values[i] == '?') {
n.left = new NodeC (values[i + 1]);
n = n.left;
}
else if (values[i] == ':') {
n = n.parent;
while (n.right != null && n.parent != null ) {
n = n.parent;
}
n.right = new NodeC (values[i + 1]);
n = n.right;
}
}
return n;
Idea is to start parsing the string from left to right and when you come across a '?' you go deeper in the tree else just return the new node created.
Here is my recursive solution :
struct node{
char val;
node *left;
node *right;
node(char v):val(v),left(NULL),right(NULL){
}
};
node* create_tree(string input, int &current){
if(current>=(int)input.size()){
return NULL;
}
node *temp = new node(input[current]);
current+=2;
if(current<(int)input.size()){
if(input[current-1]=='?'){
temp->left=create_ternary_tree(input,current);
temp->right=create_ternary_tree(input,current);
}
}
return temp;
}
My solution:
Each treenode doen't have parent link, so I use stack to keep them.
The advantages of this solution are that I only push root into stack, hence in the (if x==':' {}) sentence, no while loop, no push sentence.
public static TreeNode convert(String ternary) {
char[] chs = ternary.toCharArray();
Stack<TreeNode> stack = new Stack<TreeNode>();
TreeNode cur=new TreeNode(chs[0]);
TreeNode root= cur;
for (int i=1; i<chs.length; i+=2) {
if (chs[i]=='?') {
stack.push(cur);
TreeNode node = new TreeNode(chs[i+1]);
cur.left = node;
cur = node;
}
else if (chs[i]==':') {
cur = stack.pop();
TreeNode node = new TreeNode(chs[i+1]);
cur.right = node;
cur = node;
}
}
return root;
}
public static TreeNode convert_loop(char[] expr) {
if (expr == null || expr.length < 1) {
return null;
}
if (expr.length == 1) {
return new TreeNode(expr[0]);
}
if ((expr.length - 1) % 4 != 0) {
throw new InputMismatchException("wrong expression");
}
int start = 0, end = expr.length - 1;
TreeNode<Character> root = new TreeNode<>(expr[start]);
root.right = new TreeNode<>(expr[end]);
start += 2;
end -= 2;
TreeNode<Character> cur = root;
while (start != end) {
TreeNode<Character> node = new TreeNode<>(expr[start]);
node.right = new TreeNode<>(expr[end]);
cur.left = node;
cur = node;
start += 2;
end -= 2;
}
cur.left = new TreeNode(expr[start]);// care
return root;
}

Min Depth of binary tree

I am reading Binary Trees. while practicing coding problems I came across some solutions where it is asked to find Min Depth of Binary Tree.
Now as per my understanding depth is no of edges from root to node (leaf node in case of leaf nodes / binary tree)
What is the min depth of Binary tree {1,2}
As per my solution it should be 1.
My tested solution
public int minDepth(TreeNode root) {
if(root == null){
return 0;
}
int ldepth = minDepth(root.left);
int rdepth = minDepth(root.right);
if(ldepth == 0){
return 1+rdepth;
}else if(rdepth == 0){
return 1+ldepth;
}
return (1 + Math.min(rdepth, ldepth));
}
Here, we calculate ldepth (minimum left subtree depth) and rdepth (minimum right subtree depth) for a node. Then, if ldepth is zero but rdepth is not, that means current node is not a leaf node, so return 1 + rdepth. If both rdepth and ldepth are zeros then still 'if' condition works as we return 1+0 for current leaf node.
Similar logic for 'else if' branch. In 'return' statement as both 'if' conditions has been failed we return 1 (current node) + minimum value of recursive calls to both left and right branch.
Remember a leaf node has neither left nor right child.
1
/
/
2
so here 2 is the leaf node but 1 is not. so minimum depth for this case is 2 assuming depth of root node is 1.
#include<vector>
#include<iostream>
#include<climits>
using namespace std;
struct TreeNode {
int val;
TreeNode *left;
TreeNode *right;
TreeNode(int x) : val(x), left(NULL), right(NULL) {}
};
class Solution {
public:
int minDepth(TreeNode *root) {
if(root == NULL) return 0;
return getDepth(root);
}
int getDepth(TreeNode *r ){
if(r == NULL) return INT_MAX;
if(r->left == NULL && r->right == NULL)
return 1;
return 1+ min(getDepth(r->left), getDepth(r->right));
}
};
A root node will have a depth of 0, so here depth of the given tree will be 1, refer below recursion and iterative solution to find min dept of binary tree.
Recursive solution :
public static int findMinDepth(BTNode root) {
if (root == null || (root.getLeft() == null && root.getRight() == null)) {
return 0;
}
int ldepth = findMinDepth(root.getLeft());
int rdepth = findMinDepth(root.getRight());
return (Math.min(rdepth + 1, ldepth + 1));
}
Iterative solution :
public static int minDepth(BTNode root) {
int minDepth = Integer.MAX_VALUE;
Stack<BTNode> nodes = new Stack<>();
Stack<BTNode> path = new Stack<>();
if (root == null) {
return -1;
}
nodes.push(root);
while (!nodes.empty()) {
BTNode node = nodes.peek();
if (!path.empty() && node == path.peek()) {
if (node.getLeft() == null && node.getRight() == null && path.size() <= minDepth) {
minDepth = path.size() - 1;
}
path.pop();
nodes.pop();
} else {
path.push(node);
if (node.getRight() != null) {
nodes.push(node.getRight());
}
if (node.getLeft() != null) {
nodes.push(node.getLeft());
}
}
}
return minDepth;
}
The depth o a binary tree is the length of the longest route from the root to the leaf. In my opinion the depth should be 2.
public int minDepth(TreeNode root){
if(root==null)
return 0;
else if(root.left==null && root.right==null)
return 1;
else if(root.left==null)
return 1+minDepth(root.right);
else if(root.right==null)
return 1+minDepth(root.left);
else
return 1+Math.min(minDepth(root.right), minDepth(root.left));
}
As others stated, solution should be 2... But it's semantic, you could simply take result and subtract 1 if your definition of depth is different.
Here's an iterative answer (in C#) (Rajesh Surana answer is a good Recusive answer):
public static int FindMinDepth<T>(BinarySearchTree<T> tree) where T : IComparable<T>
{
var current = tree._root;
int level = 0;
Queue<BSTNode<T>> q = new Queue<BSTNode<T>>();
if (current != null)
q.Enqueue(current);
while (q.Count > 0)
{
level++;
Queue<BSTNode<T>> nq = new Queue<BSTNode<T>>();
foreach (var element in q)
{
if (element.Left == null && element.Right == null)
return level;
if (element.Left != null) nq.Enqueue(element.Left);
if (element.Right != null) nq.Enqueue(element.Right);
}
q = nq;
}
return 0;
//throw new Exception("Min Depth not found!");
}
JavaScript Solution
Given the following Binary Tree structure:
function BT(value, left = null, right = null) {
this.value = value;
this.left = left;
this.right = right;
}
A method to find the minimum depth can be something like so:
BT.prototype.getMinDepth = function() {
if (!this.value) {
return 0;
}
if (!this.left && !this.right) {
return 1;
}
if (this.left && this.right) {
return Math.min(this.left.getMinDepth(), this.right.getMinDepth()) + 1;
}
if (this.left) {
return this.left.getMinDepth() + 1;
}
if (this.right) {
return this.right.getMinDepth() + 1;
}
}
The time complexity of the above solution is O(n) as it traverses all the tree nodes.
A better runtime solution will be to use a breadth traversal method that ends when reaching the first leaf node:
BT.prototype.getMinDepth = function(depth = 0) {
if (!this.value) {
return depth;
}
depth++;
if (!this.left || !this.right) {
return depth;
}
return Math.min(this.left.getMinDepth(depth), this.right.getMinDepth(depth));
}
Given the depth of a path is the number of nodes from the root to the leaf node along this path. The minimum is the path with minimum number of nodes from the root to the LEAF node. In this case, the only leaf node is 2. (A leaf node is defined as a node with no children) Therefore, the only depth and also min depth is 2.
A sample code in Java:
public class Solution {
public int minDepth(TreeNode root) {
if (root==null) return 0;
if ((root.left==null) || (root.right==null)) {
return 1+Math.max(minDepth(root.left),minDepth(root.right));
}
return 1+Math.min(minDepth(root.left),minDepth(root.right));
}
}
Minimum depth is the minimum of the depth of leftsubtree and rightsubtree.
public static int maxDepth(TreeNode root) {
if(root == null) {
return 0;
}
return getDepth(root);
}
private static int getDepth(TreeNode a) {
if(a.left == null & a.right == null) {
return 1;
}
int leftDepth = 0;
int rightDepth = 0;
if(a.left != null) {
leftDepth = getDepth(a.left);
}
if(a.right != null) {
rightDepth = getDepth(a.right);
}
return (Math.min(leftDepth, rightDepth)+1);
}
The minDepth of a binary tree means the shortest distance from the root to a leaf node. Though it is arguable whether the minDepth of your binary tree is 1 or 2, depending on whether you want the shortest distance to a null node, in which case the answer would be 1 OR the shortest distance to a null node whose sibling is ALSO a null node, in which case the answer to Binary tree{1,2} would be 2. Generally, the former is asked, and following the algorithm mentioned in Cracking the Coding Interview , we have the solution as
int minDepth(TreeNode root) {
if (root == null) { return 0;}
return 1 + Math.min(minDepth(root.left), minDepth(root.right));
}

Trying to insert an Avl tree

I am trying to make an insertion method for an Avl tree but the structure and order of my nodes turns out to be incorrect. I am having trouble finding where i am going wrong.
Here are my methods
Any sort of help would be appreciated
template
void AvL<T>::insert(string val, T k)
{
if (head == NULL) {
head = new AvLNode<T>(val, k);
} else {
put(head, val, k);
}
}
template <class T>
void AvL<T>::put(AvLNode<T>* root,string val,T key1) {
if (root->key > key1) {
if (root->left != NULL) {
put(root->left, val, key1);
Balance(root, key1);
} else {
root->left = new AvLNode<T>(val, key1);
root->bf = nodeHeight(root->left) - nodeHeight(root->right);
root->left->parent = root;
}
} else {
if (root->right != NULL) {
put(root->right, val, key1);
Balance(root, key1);
} else {
root->right = new AvLNode<T>(val, key1);
root->bf = nodeHeight(root->left) - nodeHeight(root->right);
root->right->parent = root;
}
}
}
template<class T>
void AvL<T>::Balance(AvLNode<T>* root, T key1)
{ root->bf = nodeHeight(root->left) - nodeHeight(root->right);
if (root->bf < -1 && key1 > root->right->key) {
cout << "here1 ";
LeftRotate(root);
} else if (root->bf > 1 && key1 < root->left->key) {
cout << "here2 ";
RightRotate(root);
} else if (root->bf < -1 && key1 < root->right->key) {
RightRotate(root->right);
cout << "here3 ";
LeftRotate(root);
} else if (root->bf > 1 && key1 > root->left->key) {
LeftRotate(root->left);
cout << "here4 ";
RightRotate(root);
}
}
template<class T>
void AvL<T>::RightRotate(AvLNode<T>* node)
{
AvLNode<T>* node1 = node->left;
node->left = node1->right;
node1->right = node;
node->bf = nodeHeight(node->left) - nodeHeight(node->right);
node1->bf = nodeHeight(node1->left) - nodeHeight(node1->right);
node = node1;
}
template<class T>
void AvL<T>::LeftRotate(AvLNode<T>* node)
{
AvLNode<T>* node1 = node->right;
node->right = node1->left;
node1->left = node;
node->bf = nodeHeight(node->left) - nodeHeight(node->right);
node1->bf = nodeHeight(node1->left) - nodeHeight(node1->right);
node = node1;
}
template<class T>
int AvL<T>::nodeHeight( AvLNode<T> *n)
{
int lheight=0;
int rheight=0;
int h = 0;
if (n == NULL)
{
return -1;
} else {
lheight = nodeHeight(n->left);
rheight = nodeHeight(n->right);
h = 1+max(lheight,rheight);
return h;
}
}
My .h file
template <class T>
struct AvLNode
{
string value;
T key;
AvLNode *parent; // pointer to parent node
AvLNode *left; // pointer to left child
AvLNode *right; // pointer to right child
int bf; // Balance factor of node
AvLNode(string Val, T k)
{
this->value = Val;
this->key = k;
this->parent = NULL;
this->left = NULL;
this->right = NULL;
bf = 0;
}
};
template <class T>
class AvL
{
AvLNode<T> *head;
public:
// Constructor
AvL();
// Destructor
~AvL();
// Insertion Function
void insert(string val, T k); // inserts the given key value pair into the tree
void Balance(AvLNode<T>* node, T key1);
void delete_node(T k); // deletes the node for the given key
void RightRotate(AvLNode<T>* node);
void LeftRotate(AvLNode<T>* node);
void put(AvLNode<T>* root,string val,T key1);
int nodeHeight(AvLNode<T> *n); // returns height of the subtree from given node
};
Your balance function is wrong. Since you've already inserted your new node into the tree, you don't need to worry about the key any more in Balance() - so the prototype should look like this:
template<class T>
void AvL<T>::Balance(AvLNode<T>* root);
The way you're doing it now seems to be attempting to balance based on the key you just inserted - which isn't necessary! You can balance the tree just based on the balance factors of nodes - here's how.
template<class T>
void AvL<T>::Balance(AvLNode<T>* root) {
if (root->bf > 1) {
if (root->left->bf == -1) LeftRotate(root->left);
RightRotate(root);
} else if (root->bf < -1) {
if (root->right->bf == 1) RightRotate(root->right);
LeftRotate(root);
}
}
You can read more about it here - but you seem to have the idea almost down. The only thing you need to change conceptually is the idea that you're balancing based on the key you just inserted. You're not - you're balancing based on the shape of the tree, which you can get from just the balance factors of each subtree.

Finding height in Binary Search Tree

I was wondering if anybody could help me rework this method to find the height of a binary search tree. So far, my code looks like this. However, the answer I'm getting is larger than the actual height by 1. But when I remove the +1 from my return statements, it's less than the actual height by 1. I'm still trying to wrap my head around recursion with these BST. Any help would be much appreciated.
public int findHeight(){
if(this.isEmpty()){
return 0;
}
else{
TreeNode<T> node = root;
return findHeight(node);
}
}
private int findHeight(TreeNode<T> aNode){
int heightLeft = 0;
int heightRight = 0;
if(aNode.left!=null)
heightLeft = findHeight(aNode.left);
if(aNode.right!=null)
heightRight = findHeight(aNode.right);
if(heightLeft > heightRight){
return heightLeft+1;
}
else{
return heightRight+1;
}
}
The problem lies in your base case.
"The height of a tree is the length of the path from the root to the deepest node in the tree. A (rooted) tree with only a node (the root) has a height of zero." - Wikipedia
If there is no node, you want to return -1 not 0. This is because you are adding 1 at the end.
So if there isn't a node, you return -1 which cancels out the +1.
int findHeight(TreeNode<T> aNode) {
if (aNode == null) {
return -1;
}
int lefth = findHeight(aNode.left);
int righth = findHeight(aNode.right);
if (lefth > righth) {
return lefth + 1;
} else {
return righth + 1;
}
}
The height of a binary search tree is equal to number of layers - 1.
See the diagram at http://en.wikipedia.org/wiki/Binary_tree
Your recursion is good, so just subtract one at the root level.
Also note, you can clean up the function a bit by handling null nodes:
int findHeight(node) {
if (node == null) return 0;
return 1 + max(findHeight(node.left), findHeight(node.right));
}
int getHeight(Node node) {
if (node == null) return -1;
return 1 + Math.max(getHeight(node.left), getHeight(node.right));
}
In my opinion, your code would benefit from being simplified a bit. Rather than attempting to end the recursion when a child pointer is null, only end it when the current pointer is null. That makes the code a lot simpler to write. In pseudo-code, it looks something like this:
if (node = null)
return 0;
else
left = height(node->left);
right = height(node->right);
return 1 + max(left, right);
class Solution{
public static int getHeight(Node root) {
int height = -1;
if (root == null) {
return height;
} else {
height = 1 + Math.max(getHeight(root.left), getHeight(root.right));
}
return height;
}
For people like me who like one line solutions:
public int getHeight(Node root) {
return Math.max(root.left != null ? getHeight(root.left) : -1,
root.right != null ? getHeight(root.right) : -1)
+ 1;
}
Here's a concise and hopefully correct way to express it:
private int findHeight(TreeNode<T> aNode){
if(aNode == null || (aNode.left == null && aNode.right == null))
return 0;
return Math.max(findHeight(aNode.left), findHeight(aNode.right)) + 1;
}
If the current node is null, there's no tree. If both children are, there's a single layer, which means 0 height. This uses the definition of height (mentioned by Stephen) as # of layers - 1
This is untested, but fairly obviously correct:
private int findHeight(Treenode<T> aNode) {
if (aNode.left == null && aNode.right == null) {
return 0; // was 1; apparently a node with no children has a height of 0.
} else if (aNode.left == null) {
return 1 + findHeight(aNode.right);
} else if (aNode.right == null) {
return 1 + findHeight(aNode.left);
} else {
return 1 + max(findHeight(aNode.left), findHeight(aNode.right));
}
}
Often simplifying your code is easier than figuring out why it's off by one. This code is easy to understand: the four possible cases are clearly handled in an obviously correct manner:
If both the left and right trees are null, return 0, since a single node by definition has a height of 0. (was 1)
If either the left or right trees (but not both!) are null, return the height of the non-null tree, plus 1 to account for the added height of the current node.
If neither tree is null, return the height of the taller subtree, again plus one for the current node.
public void HeightRecursive()
{
Console.WriteLine( HeightHelper(root) );
}
private int HeightHelper(TreeNode node)
{
if (node == null)
{
return -1;
}
else
{
return 1 + Math.Max(HeightHelper(node.LeftNode),HeightHelper(node.RightNode));
}
}
C# code.
Include these two methods in your BST class. you need two method to calculate height of tree. HeightHelper calculate it, & HeightRecursive print it in main().
The definition given above of the height is incorrect. That is the definition of the depth.
"The depth of a node M in a tree is the length of the path from the root of the tree to M. The height of a tree is one more than the depth of the deepest node in the tree. All nodes of depth d are at level d in the tree. The root is the only node at level 0, and its depth is 0."
Citation: "A Practical Introduction to Data Structures and Algorithm Analysis"
Edition 3.2 (Java Version)
Clifford A. Shaffer
Department of Computer Science
Virginia Tech
Blacksburg, VA 24061
public int height(){
if(this.root== null) return 0;
int leftDepth = nodeDepth(this.root.left, 1);
int rightDepth = nodeDepth(this.root.right, 1);
int height = leftDepth > rightDepth? leftDepth: rightDepth;
return height;
}
private int nodeDepth(Node node, int startValue){
int nodeDepth = 0;
if(node.left == null && node.right == null) return startValue;
else{
startValue++;
if(node.left!= null){
nodeDepth = nodeDepth(node.left, startValue);
}
if(node.right!= null){
nodeDepth = nodeDepth(node.right, startValue);
}
}
return nodeDepth;
}
//function to find height of BST
int height(Node* root) {
if(root == NULL){
return -1;
}
int sum=0;
int rheight = height(root->right);
int lheight = height(root->left);
if(lheight>rheight){
sum = lheight +1;
}
if(rheight > lheight){
sum = rheight + 1;
}
return sum;
}
int height(Node* root) {
if(root==NULL) return -1;
return max(height(root->left),height(root->right))+1;
}
Take of maximum height from left and right subtree and add 1 to it.This also handles the base case(height of Tree with 1 node is 0).
I know that I’m late to the party. After looking into wonderful answers provided here, I thought mine will add some value to this post. Although the posted answers are amazing and easy to understand however, all are calculating the height to the BST in linear time. I think this can be improved and Height can be retrieved in constant time, hence writing this answer – hope you will like it.
Let’s start with the Node class:
public class Node
{
public Node(string key)
{
Key = key;
Height = 1;
}
public int Height { get; set; }
public string Key { get; set; }
public Node Left { get; set; }
public Node Right { get; set; }
public override string ToString()
{
return $"{Key}";
}
}
BinarySearchTree class
So you might have guessed the trick here… Im keeping node instance variable Height to keep track of each node when added.
Lets move to the BinarySearchTree class that allows us to add nodes into our BST:
public class BinarySearchTree
{
public Node RootNode { get; private set; }
public void Put(string key)
{
if (ContainsKey(key))
{
return;
}
RootNode = Put(RootNode, key);
}
private Node Put(Node node, string key)
{
if (node == null) return new Node(key);
if (node.Key.CompareTo(key) < 0)
{
node.Right = Put(node.Right, key);
}
else
{
node.Left = Put(node.Left, key);
}
// since each node has height property that is maintained through this Put method that creates the binary search tree.
// calculate the height of this node by getting the max height of its left or right subtree and adding 1 to it.
node.Height = Math.Max(GetHeight(node.Left), GetHeight(node.Right)) + 1;
return node;
}
private int GetHeight(Node node)
{
return node?.Height ?? 0;
}
public Node Get(Node node, string key)
{
if (node == null) return null;
if (node.Key == key) return node;
if (node.Key.CompareTo(key) < 0)
{
// node.Key = M, key = P which results in -1
return Get(node.Right, key);
}
return Get(node.Left, key);
}
public bool ContainsKey(string key)
{
Node node = Get(RootNode, key);
return node != null;
}
}
Once we have added the key, values in the BST, we can just call Height property on the RootNode object that will return us the Height of the RootNode tree in constant time.
The trick is to keep the height updated when a new node is added into the tree.
Hope this helps someone out there in the wild world of computer science enthusiast!
Unit test:
[TestCase("SEARCHEXAMPLE", 6)]
[TestCase("SEBAQRCHGEXAMPLE", 6)]
[TestCase("STUVWXYZEBAQRCHGEXAMPLE", 8)]
public void HeightTest(string data, int expectedHeight)
{
// Arrange.
var runner = GetRootNode(data);
// Assert.
Assert.AreEqual(expectedHeight, runner.RootNode.Height);
}
private BinarySearchTree GetRootNode(string data)
{
var runner = new BinarySearchTree();
foreach (char nextKey in data)
{
runner.Put(nextKey.ToString());
}
return runner;
}
Note: This idea of keeping the Height of tree maintained in every Put operation is inspired by the Size of BST method found in the 3rd chapter (page 399) of Algorithm (Fourth Edition) book.
I guess this question could mean two different things...
Height is the number of nodes in the longest branch:-
int calcHeight(node* root){
if(root==NULL)
return 0;
int l=calcHeight(root->left);
int r=calcHeight(root->right);
if(l>r)
return l+1;
else
return r+1;
}
Height is the total number of nodes in the tree itself:
int calcSize(node* root){
if(root==NULL)
return 0;
return(calcSize(root->left)+1+calcSize(root->right));
}
public int getHeight(Node node)
{
if(node == null)
return 0;
int left_val = getHeight(node.left);
int right_val = getHeight(node.right);
if(left_val > right_val)
return left_val+1;
else
return right_val+1;
}
Set a tempHeight as a static variable(initially 0).
static void findHeight(Node node, int count) {
if (node == null) {
return;
}
if ((node.right == null) && (node.left == null)) {
if (tempHeight < count) {
tempHeight = count;
}
}
findHeight(node.left, ++count);
count--; //reduce the height while traversing to a different branch
findHeight(node.right, ++count);
}
Here is a solution in Java a bit lengthy but works..
public static int getHeight (Node root){
int lheight = 0, rheight = 0;
if(root==null) {
return 0;
}
else {
if(root.left != null) {
lheight = 1 + getHeight(root.left);
System.out.println("lheight" + " " + lheight);
}
if (root.right != null) {
rheight = 1+ getHeight(root.right);
System.out.println("rheight" + " " + rheight);
}
if(root != null && root.left == null && root.right == null) {
lheight += 1;
rheight += 1;
}
}
return Math.max(lheight, rheight);
}
int getHeight(Node* root)
{
if(root == NULL) return -1;
else return max(getHeight(root->left), getHeight(root->right)) + 1;
}
Here is a solution in C#
private static int heightOfTree(Node root)
{
if (root == null)
{
return 0;
}
int left = 1 + heightOfTree(root.left);
int right = 1 + heightOfTree(root.right);
return Math.Max(left, right);
}
For anyone else that reads this!!!!
HEIGHT is defined as the number of nodes in the longest path from the root node to a leaf node. Therefore: a tree with only a root node has a height of 1 and not 0.
The LEVEL of a given node is the distance from the root plus 1. Therefore: The root is on level 1, its child nodes are on level 2 and so on.
(Information courtesy of Data Structures: Abstraction and Design Using Java, 2nd Edition, by Elliot B. Koffman & Paul A. T. Wolfgang) - Book used in Data Structures Course I am currently taking at Columbus State University.
enter image description here
According to "Introduction to Algorithms" by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, following is the definition of tree height:
The height of a node in a
tree is the number of edges on the longest simple downward path from the node to
a leaf, and the height of a tree is the height of its root. The height of a tree is also
equal to the largest depth of any node in the tree.
Following is my ruby solution. Most of the people forgot about height of empty tree or tree of single node in their implementation.
def height(node, current_height)
return current_height if node.nil? || (node.left.nil? && node.right.nil?)
return [height(node.left, current_height + 1), height(node.right, current_height + 1)].max if node.left && node.right
return height(node.left, current_height + 1) if node.left
return height(node.right, current_height + 1)
end
int maxDepth(BinaryTreeNode root) {
if(root == null || (root.left == null && root.right == null)) {
return 0;
}
return 1 + Math.max(maxDepth(root.left), maxDepth(root.right));
}
Height of Binary Tree
public static int height(Node root)
{
// Base case: empty tree has height 0
if (root == null) {
return 0;
}
// recursively for left and right subtree and consider maximum depth
return 1 + Math.max(height(root.left), height(root.right));
}
I struggled with this myself trying to find something elegant that still resulted in the correct value. Here's what I came up with using Swift. Note that height is a computed variable and technically not a function.
class Node<T: Comparable>: NSObject
{
var left: Node<T>? = nil
var right: Node<T>? = nil
var isLeaf: Bool { left == nil && right == nil }
var height: Int {
if isLeaf { return 0 }
return 1 + max(left?.height ?? 0, right?.height ?? 0)
}
}
There's more to this Node definition but you can see the left and right variables (possibly nil) and an isLeaf var that is true when both left and right are nil. Might not be the most efficient but I believe it yields the correct result.
The BST definition also has a computed height variable and returns -1 when the tree is empty.
class BST<T: Comparable>: NSObject
{
var root: Node<T>?
var height: Int { root != nil ? root!.height : -1 }
}
HackerRank Day 22: Finding height in Binary Search Tree, in C#.
static int getHeight(Node root)
{
//Write your code here
int countr = 0,countl=0;
Node Leftsubtree=root.left;
Node rightsubtree = root.right;
int data=root.data;
if(root==null ||(root.left == null && root.right == null))
{
return 0;
}
else
{
while (Leftsubtree != null)
{
if(Leftsubtree.data<data)
{
Leftsubtree = Leftsubtree.left==null?Leftsubtree.right:Leftsubtree.left;
countl++;
}
}
while (rightsubtree != null)
{
if (rightsubtree.data > data)
{
rightsubtree = rightsubtree.right == null ? rightsubtree.left : rightsubtree.right;
countr++;
}
}
}
return countr >= countl ? countr : countl;
}

Resources