Given an N-ary tree, find the number of siblings of given node x. Assume that x exists in the given n-ary tree.
Example :
Input : 30 Output : 3
Approach: For every node in the given n-ary tree, push the children of the current node in the queue. While adding the children of current node in queue, check if any children is equal to the given value x or not. If yes, then return the number of siblings of x.
Below is the implementation of the above idea :
// C++ program to find number // of siblings of a given node #include <bits/stdc++.h> using namespace std;
// Represents a node of an n-ary tree class Node {
public :
int key;
vector<Node*> child;
Node( int data)
{
key = data;
}
}; // Function to calculate number // of siblings of a given node int numberOfSiblings(Node* root, int x)
{ if (root == NULL)
return 0;
// Creating a queue and
// pushing the root
queue<Node*> q;
q.push(root);
while (!q.empty()) {
// Dequeue an item from queue and
// check if it is equal to x If YES,
// then return number of children
Node* p = q.front();
q.pop();
// Enqueue all children of
// the dequeued item
for ( int i = 0; i < p->child.size(); i++) {
// If the value of children
// is equal to x, then return
// the number of siblings
if (p->child[i]->key == x)
return p->child.size() - 1;
q.push(p->child[i]);
}
}
} // Driver program int main()
{ // Creating a generic tree as shown in above figure
Node* root = new Node(50);
(root->child).push_back( new Node(2));
(root->child).push_back( new Node(30));
(root->child).push_back( new Node(14));
(root->child).push_back( new Node(60));
(root->child[0]->child).push_back( new Node(15));
(root->child[0]->child).push_back( new Node(25));
(root->child[0]->child[1]->child).push_back( new Node(70));
(root->child[0]->child[1]->child).push_back( new Node(100));
(root->child[1]->child).push_back( new Node(6));
(root->child[1]->child).push_back( new Node(1));
(root->child[2]->child).push_back( new Node(7));
(root->child[2]->child[0]->child).push_back( new Node(17));
(root->child[2]->child[0]->child).push_back( new Node(99));
(root->child[2]->child[0]->child).push_back( new Node(27));
(root->child[3]->child).push_back( new Node(16));
// Node whose number of
// siblings is to be calculated
int x = 100;
// Function calling
cout << numberOfSiblings(root, x) << endl;
return 0;
} |
// Java program to find number // of siblings of a given node import java.util.*;
public class GFG
{ // Represents a node of an n-ary tree static class Node
{ int key;
Vector<Node> child;
Node( int data)
{
key = data;
child = new Vector<Node>();
}
}; // Function to calculate number // of siblings of a given node static int numberOfSiblings(Node root, int x)
{ if (root == null )
return 0 ;
// Creating a queue and
// pushing the root
Queue<Node> q = new LinkedList<>();
q.add(root);
while (q.size() > 0 )
{
// Dequeue an item from queue and
// check if it is equal to x If YES,
// then return number of children
Node p = q.peek();
q.remove();
// Enqueue all children of
// the dequeued item
for ( int i = 0 ; i < p.child.size(); i++)
{
// If the value of children
// is equal to x, then return
// the number of siblings
if (p.child.get(i).key == x)
return p.child.size() - 1 ;
q.add(p.child.get(i));
}
}
return - 1 ;
} // Driver code public static void main(String args[])
{ // Creating a generic tree as shown in above figure
Node root = new Node( 50 );
(root.child).add( new Node( 2 ));
(root.child).add( new Node( 30 ));
(root.child).add( new Node( 14 ));
(root.child).add( new Node( 60 ));
(root.child.get( 0 ).child).add( new Node( 15 ));
(root.child.get( 0 ).child).add( new Node( 25 ));
(root.child.get( 0 ).child.get( 1 ).child).add( new Node( 70 ));
(root.child.get( 0 ).child.get( 1 ).child).add( new Node( 100 ));
(root.child.get( 1 ).child).add( new Node( 6 ));
(root.child.get( 1 ).child).add( new Node( 1 ));
(root.child.get( 2 ).child).add( new Node( 7 ));
(root.child.get( 2 ).child.get( 0 ).child).add( new Node( 17 ));
(root.child.get( 2 ).child.get( 0 ).child).add( new Node( 99 ));
(root.child.get( 2 ).child.get( 0 ).child).add( new Node( 27 ));
(root.child.get( 3 ).child).add( new Node( 16 ));
// Node whose number of
// siblings is to be calculated
int x = 100 ;
// Function calling
System.out.println( numberOfSiblings(root, x) );
} } // This code is contributed by Arnab Kundu |
# Python3 program to find number # of siblings of a given node from queue import Queue
# Represents a node of an n-ary tree class newNode:
def __init__( self ,data):
self .child = []
self .key = data
# Function to calculate number # of siblings of a given node def numberOfSiblings(root, x):
if (root = = None ):
return 0
# Creating a queue and
# pushing the root
q = Queue()
q.put(root)
while ( not q.empty()):
# Dequeue an item from queue and
# check if it is equal to x If YES,
# then return number of children
p = q.queue[ 0 ]
q.get()
# Enqueue all children of
# the dequeued item
for i in range ( len (p.child)):
# If the value of children
# is equal to x, then return
# the number of siblings
if (p.child[i].key = = x):
return len (p.child) - 1
q.put(p.child[i])
# Driver Code if __name__ = = '__main__' :
# Creating a generic tree as
# shown in above figure
root = newNode( 50 )
(root.child).append(newNode( 2 ))
(root.child).append(newNode( 30 ))
(root.child).append(newNode( 14 ))
(root.child).append(newNode( 60 ))
(root.child[ 0 ].child).append(newNode( 15 ))
(root.child[ 0 ].child).append(newNode( 25 ))
(root.child[ 0 ].child[ 1 ].child).append(newNode( 70 ))
(root.child[ 0 ].child[ 1 ].child).append(newNode( 100 ))
(root.child[ 1 ].child).append(newNode( 6 ))
(root.child[ 1 ].child).append(newNode( 1 ))
(root.child[ 2 ].child).append(newNode( 7 ))
(root.child[ 2 ].child[ 0 ].child).append(newNode( 17 ))
(root.child[ 2 ].child[ 0 ].child).append(newNode( 99 ))
(root.child[ 2 ].child[ 0 ].child).append(newNode( 27 ))
(root.child[ 3 ].child).append(newNode( 16 ))
# Node whose number of
# siblings is to be calculated
x = 100
# Function calling
print (numberOfSiblings(root, x))
# This code is contributed by PranchalK |
// C# program to find number // of siblings of a given node using System;
using System.Collections.Generic;
class GFG
{ // Represents a node of an n-ary tree public class Node
{ public int key;
public List<Node> child;
public Node( int data)
{
key = data;
child = new List<Node>();
}
}; // Function to calculate number // of siblings of a given node static int numberOfSiblings(Node root, int x)
{ if (root == null )
return 0;
// Creating a queue and
// pushing the root
Queue<Node> q = new Queue<Node>();
q.Enqueue(root);
while (q.Count > 0)
{
// Dequeue an item from queue and
// check if it is equal to x If YES,
// then return number of children
Node p = q.Peek();
q.Dequeue();
// Enqueue all children of
// the dequeued item
for ( int i = 0; i < p.child.Count; i++)
{
// If the value of children
// is equal to x, then return
// the number of siblings
if (p.child[i].key == x)
return p.child.Count - 1;
q.Enqueue(p.child[i]);
}
}
return -1;
} // Driver code public static void Main(String []args)
{ // Creating a generic tree
// as shown in above figure
Node root = new Node(50);
(root.child).Add( new Node(2));
(root.child).Add( new Node(30));
(root.child).Add( new Node(14));
(root.child).Add( new Node(60));
(root.child[0].child).Add( new Node(15));
(root.child[0].child).Add( new Node(25));
(root.child[0].child[1].child).Add( new Node(70));
(root.child[0].child[1].child).Add( new Node(100));
(root.child[1].child).Add( new Node(6));
(root.child[1].child).Add( new Node(1));
(root.child[2].child).Add( new Node(7));
(root.child[2].child[0].child).Add( new Node(17));
(root.child[2].child[0].child).Add( new Node(99));
(root.child[2].child[0].child).Add( new Node(27));
(root.child[3].child).Add( new Node(16));
// Node whose number of
// siblings is to be calculated
int x = 100;
// Function calling
Console.WriteLine( numberOfSiblings(root, x));
} } // This code is contributed by PrinciRaj1992 |
<script> // JavaScript program to find number // of siblings of a given node // Represents a node of an n-ary tree class Node { constructor(data)
{
this .key = data;
this .child = [];
}
}; // Function to calculate number // of siblings of a given node function numberOfSiblings(root, x)
{ if (root == null )
return 0;
// Creating a queue and
// pushing the root
var q = [];
q.push(root);
while (q.length > 0)
{
// Dequeue an item from queue and
// check if it is equal to x If YES,
// then return number of children
var p = q[0];
q.shift();
// push all children of
// the dequeued item
for ( var i = 0; i < p.child.length; i++)
{
// If the value of children
// is equal to x, then return
// the number of siblings
if (p.child[i].key == x)
return p.child.length - 1;
q.push(p.child[i]);
}
}
return -1;
} // Driver code // Creating a generic tree // as shown in above figure var root = new Node(50);
(root.child).push( new Node(2));
(root.child).push( new Node(30));
(root.child).push( new Node(14));
(root.child).push( new Node(60));
(root.child[0].child).push( new Node(15));
(root.child[0].child).push( new Node(25));
(root.child[0].child[1].child).push( new Node(70));
(root.child[0].child[1].child).push( new Node(100));
(root.child[1].child).push( new Node(6));
(root.child[1].child).push( new Node(1));
(root.child[2].child).push( new Node(7));
(root.child[2].child[0].child).push( new Node(17));
(root.child[2].child[0].child).push( new Node(99));
(root.child[2].child[0].child).push( new Node(27));
(root.child[3].child).push( new Node(16));
// Node whose number of // siblings is to be calculated var x = 100;
// Function calling document.write( numberOfSiblings(root, x)); </script> |
1
Complexity Analysis:
- Time Complexity: O(N), where N is the number of nodes in tree.
- Auxiliary Space: O(N), where N is the number of nodes in tree.
Example no 2:
Algorithmic steps for implementing the given concept:
Create a hash map to store the parent of each node.
For each node in the tree, map it to its parent in the hash map.
Given the node for which you want to find the number of siblings, look up its parent in the hash map.
If the parent is not found, return 0 as the node has no siblings.
If the parent is found, count the number of children the parent has.
Return the count minus 1 as the given node is included in the count.
Note: This algorithm assumes that the parent array is complete and accurately represents the n-ary tree.
Program: Implementing the given concept by using hash map:
#include <iostream> #include <vector> #include <unordered_map> using namespace std;
int findSiblingCount( int node, unordered_map< int , vector< int >> &treeMap) {
int parent = treeMap.count(node) ? treeMap[node][0] : -1;
if (parent == -1) {
return 0;
}
int siblingCount = treeMap[parent].size() - 1;
return siblingCount;
} int main() {
unordered_map< int , vector< int >> treeMap;
treeMap[0] = {-1, 1, 2, 3};
treeMap[1] = {0, 4, 5};
treeMap[2] = {0, 6};
treeMap[3] = {0};
treeMap[4] = {1};
treeMap[5] = {1};
treeMap[6] = {2};
int node = 4;
cout << "The number of siblings for node " << node << " is: " << findSiblingCount(node, treeMap) << endl;
return 0;
} |
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class SiblingCounter {
// Define method to count the number of siblings for a
// given node in a tree
public static int findSiblingCount( int node,Map<Integer, List<Integer> > treeMap)
{
int parent = treeMap.containsKey(node)
? treeMap.get(node).get( 0 )
: - 1 ;
if (parent == - 1 ) {
return 0 ;
}
int siblingCount = treeMap.get(parent).size() - 1 ;
return siblingCount;
}
public static void main(String[] args)
{
// Define the tree using an unordered map of integer
// keys and vector values
Map<Integer, List<Integer> > treeMap = new HashMap<>();
treeMap.put( 0 , new ArrayList<Integer>() {{add(- 1 );
add( 1 );
add( 2 );
add( 3 );
}
});
treeMap.put( 1 , new ArrayList<Integer>() {
{
add( 0 );
add( 4 );
add( 5 );
}
});
treeMap.put( 2 , new ArrayList<Integer>() {
{
add( 0 );
add( 6 );
}
});
treeMap.put( 3 , new ArrayList<Integer>() {
{
add( 0 );
}
});
treeMap.put( 4 , new ArrayList<Integer>() {
{
add( 1 );
}
});
treeMap.put( 5 , new ArrayList<Integer>() {
{
add( 1 );
}
});
treeMap.put( 6 , new ArrayList<Integer>() {
{
add( 2 );
}
});
int node = 4 ;
// Call the findSiblingCount method and print the
// result
System.out.println(
"The number of siblings for node " + node
+ " is: " + findSiblingCount(node, treeMap));
}
} |
def findSiblingCount(node, treeMap):
parent = treeMap[node][ 0 ] if node in treeMap else - 1
if parent = = - 1 :
return 0
siblingCount = len (treeMap[parent]) - 1
return siblingCount
treeMap = {
0 : [ - 1 , 1 , 2 , 3 ],
1 : [ 0 , 4 , 5 ],
2 : [ 0 , 6 ],
3 : [ 0 ],
4 : [ 1 ],
5 : [ 1 ],
6 : [ 2 ]
} node = 4
print (f "The number of siblings for node {node} is: {findSiblingCount(node, treeMap)}" )
|
// Creating a new Map to represent the tree structure let treeMap = new Map();
// Adding nodes and their children to the treeMap treeMap.set(0, [-1, 1, 2, 3]); treeMap.set(1, [0, 4, 5]); treeMap.set(2, [0, 6]); treeMap.set(3, [0]); treeMap.set(4, [1]); treeMap.set(5, [1]); treeMap.set(6, [2]); // Function to find the number of siblings for a given node in the treeMap function findSiblingCount(node, treeMap) {
// Finding the parent node of the given node
let parent = treeMap.has(node) ? treeMap.get(node)[0] : -1;
// If the given node does not have a parent, it has no siblings
if (parent === -1) {
return 0;
}
// Finding the number of siblings for the given node
// by subtracting 1 from the length of the parent node's children array
let siblingCount = treeMap.get(parent).length - 1;
return siblingCount;
} // Example usage of the function to find the number of siblings for a given node let node = 4; console.log(`The number of siblings for node ${node} is: ${findSiblingCount(node, treeMap)}`);
// This code is contributed by Amit Mangal. |
// Import required namespaces using System;
using System.Collections.Generic;
class Program
{ // Function to find the number of siblings of a given node in a tree
static int FindSiblingCount( int node, Dictionary< int , List< int >> treeMap)
{
// Find the parent of the given node
int parent = treeMap.ContainsKey(node) ? treeMap[node][0] : -1;
// If the node does not have a parent, return 0
if (parent == -1)
{
return 0;
}
// Find the number of siblings of the node
int siblingCount = treeMap[parent].Count - 1;
return siblingCount;
}
static void Main( string [] args)
{
// Create the tree as a dictionary
Dictionary< int , List< int >> treeMap = new Dictionary< int , List< int >>();
treeMap[0] = new List< int > { -1, 1, 2, 3 };
treeMap[1] = new List< int > { 0, 4, 5 };
treeMap[2] = new List< int > { 0, 6 };
treeMap[3] = new List< int > { 0 };
treeMap[4] = new List< int > { 1 };
treeMap[5] = new List< int > { 1 };
treeMap[6] = new List< int > { 2 };
// Define the node to find the number of siblings for
int node = 4;
// Print the result
Console.WriteLine( "The number of siblings for node " + node + " is: " + FindSiblingCount(node, treeMap));
}
} // This code is contributed by Amit Mangal |
The number of siblings for node 4 is: 2
Explanation:
In this implementation, the findSiblingCount function takes a node and the tree represented as a hash map as inputs and returns the number of siblings the node has. If the node is not found in the tree map, it returns 0 as the node has no siblings. If the node is found, the function looks up the parent of the node in the tree map and returns the number of children the parent has minus 1, which represents the number of siblings the node has.
Time and Space complexities for above program:
The time complexity of the above code is O(1) because the findSiblingCount function takes constant time to find the number of siblings of a given node. This is because the hash map is used to store the parent of each node, so looking up the parent of a given node takes constant time. The same holds true for counting the number of children the parent has.
The space complexity of the above code is O(n), where n is the number of nodes in the n-ary tree. This is because the hash map is used to store the parent of each node and the children of each parent, so the space required is proportional to the number of nodes in the tree.
Note: The space complexity assumes that the hash map is used to represent the tree and the number of children each node has is constant, so the space used is linear in the number of nodes. If the number of children each node has is not constant, the space complexity would be higher.