Open In App
Related Articles

Find the number of paths of length K in a directed graph

Improve Article
Improve
Save Article
Save
Like Article
Like

Given a directed, unweighted graph with N vertices and an integer K. The task is to find the number of paths of length K for each pair of vertices (u, v). Paths don’t have to be simple i.e. vertices and edges can be visited any number of times in a single path. 
The graph is represented as adjacency matrix where the value G[i][j] = 1 indicates that there is an edge from vertex i to vertex j and G[i][j] = 0 indicates no edge from i to j.
Examples: 
 

Input: K = 2, 
 

Output: 
1 2 2 
0 1 0 
0 0 1 
Number of paths from 0 to 0 of length k is 1({0->0->0}) 
Number of paths from 0 to 1 of length k are 2({0->0->1}, {0->2->1}) 
Number of paths from 0 to 2 of length k are 2({0->0->2}, {0->1->2}) 
Number of paths from 1 to 1 of length k is 1({1->2->1}) 
Number of paths from 2 to 2 of length k is 1({2->1->2})
Input: K = 3, 
 

Output: 
1 0 0 
0 1 0 
0 0 1 
Number of paths from 0 to 0 of length k is 1({0->1->2->0}) 
Number of paths from 1 to 1 of length k is 1({1->2->0->1}) 
Number of paths from 2 to 2 of length k is 1({2->1->0->2}) 
 

 

Prerequisite: Matrix exponentiation, Matrix multiplication
Approach: It is obvious that given adjacency matrix is the answer to the problem for the case k = 1. It contains the number of paths of length 1 between each pair of vertices. 
Let’s assume that the answer for some k is Matk and the answer for k + 1 is Matk + 1
Matk + 1[i][j] = ?p = 1NMatk[i][p]*G[p][j]
It is easy to see that the formula computes nothing other than the product of the matrices Matk and G i.e. Matk + 1 = Matk * G
Thus, the solution of the problem can be represented as Matk = G * G * … * G(k times) = Gk
Below is the implementation of the above approach: 
 

C++




// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
 
#define N 3
 
// Function to multiply two matrices
void multiply(int a[][N], int b[][N], int res[][N])
{
    int mul[N][N];
    for (int i = 0; i < N; i++) {
        for (int j = 0; j < N; j++) {
            mul[i][j] = 0;
            for (int k = 0; k < N; k++)
                mul[i][j] += a[i][k] * b[k][j];
        }
    }
 
    // Storing the multiplication result in res[][]
    for (int i = 0; i < N; i++)
        for (int j = 0; j < N; j++)
            res[i][j] = mul[i][j];
}
 
// Function to compute G raised to the power n
void power(int G[N][N], int res[N][N], int n)
{
 
    // Base condition
    if (n == 1) {
        for (int i = 0; i < N; i++)
            for (int j = 0; j < N; j++)
                res[i][j] = G[i][j];
        return;
    }
 
    // Recursion call for first half
    power(G, res, n / 2);
 
    // Multiply two halves
    multiply(res, res, res);
 
    // If n is odd
    if (n % 2 != 0)
        multiply(res, G, res);
}
 
// Driver code
int main()
{
    int G[N][N] = { { 1, 1, 1 },
                    { 0, 0, 1 },
                    { 0, 1, 0 } };
 
    int k = 2, res[N][N];
 
    power(G, res, k);
 
    for (int i = 0; i < N; i++) {
        for (int j = 0; j < N; j++)
            cout << res[i][j] << " ";
        cout << "\n";
    }
 
    return 0;
}
// This Code is improved by cidacoder


Java




// Java implementation of the approach
class GFG
{
     
static int N = 3;
 
// Function to multiply two matrices
static void multiply(int a[][], int b[][], int res[][])
{
    int [][]mul = new int[N][N];
    for (int i = 0; i < N; i++)
    {
        for (int j = 0; j < N; j++)
        {
            mul[i][j] = 0;
            for (int k = 0; k < N; k++)
                mul[i][j] += a[i][k] * b[k][j];
        }
    }
 
    // Storing the multiplication result in res[][]
    for (int i = 0; i < N; i++)
        for (int j = 0; j < N; j++)
            res[i][j] = mul[i][j];
}
 
// Function to compute G raised to the power n
static void power(int G[][], int res[][], int n)
{
 
    // Base condition
    if (n == 1) {
        for (int i = 0; i < N; i++)
            for (int j = 0; j < N; j++)
                res[i][j] = G[i][j];
        return;
    }
 
    // Recursion call for first half
    power(G, res, n / 2);
 
    multiply(res, res, res);
 
    // If n is odd
    if (n % 2 != 0)
        multiply(res, G, res);
}
 
// Driver code
public static void main(String[] args)
{
    int G[][] = { { 1, 1, 1 },
                    { 0, 0, 1 },
                    { 0, 1, 0 } };
 
    int k = 2;
    int [][]res = new int[N][N];
 
    power(G, res, k);
 
    for (int i = 0; i < N; i++)
    {
        for (int j = 0; j < N; j++)
            System.out.print(res[i][j] + " ");
        System.out.println("");
    }
}
}
 
// This code is contributed by 29AjayKumar
// This Code is improved by cidacoder


Python3




# Python3 implementation of the approach
 
import numpy as np
 
N = 3
 
# Function to multiply two matrices
def multiply(a, b, res) :
 
    mul = np.zeros((N,N));
     
    for i in range(N) :
        for j in range(N) :
            mul[i][j] = 0;
            for k in range(N) :
                mul[i][j] += a[i][k] * b[k][j];
 
    # Storing the multiplication result in res[][]
    for i in range(N) :
        for j in range(N) :
            res[i][j] = mul[i][j];
 
 
# Function to compute G raised to the power n
def power(G, res, n) :
     
    # Base condition
    if (n == 1) :
        for i in range(N) :
            for j in range(N) :
                res[i][j] = G[i][j];
        return;
 
    # Recursion call for first half
    power(G, res, n // 2);
 
    # Multiply two halves
    multiply(res, res, res);
 
    # If n is odd
    if (n % 2 != 0) :
        multiply(res, G, res);
 
# Driver code
if __name__ == "__main__" :
 
    G = [
        [ 1, 1, 1 ],
        [ 0, 0, 1 ],
        [ 0, 1, 0 ]
        ];
 
    k = 2;
    res = np.zeros((N,N));
 
    power(G, res, k);
 
    for i in range(N) :
        for j in range(N) :
            print(res[i][j],end = " ");
         
        print()
         
# This code is contributed by AnkitRai01
# This Code is improved by cidacoder


C#




// C# implementation of the approach
using System;
 
class GFG
{
     
static int N = 3;
 
// Function to multiply two matrices
static void multiply(int [,]a, int [,]b, int [,]res)
{
    int [,]mul = new int[N,N];
    for (int i = 0; i < N; i++)
    {
        for (int j = 0; j < N; j++)
        {
            mul[i,j] = 0;
            for (int k = 0; k < N; k++)
                mul[i,j] += a[i,k] * b[k,j];
        }
    }
 
    // Storing the multiplication result in res[][]
    for (int i = 0; i < N; i++)
        for (int j = 0; j < N; j++)
            res[i,j] = mul[i,j];
}
 
// Function to compute G raised to the power n
static void power(int [,]G, int [,]res, int n)
{
 
    // Base condition
    if (n == 1) {
        for (int i = 0; i < N; i++)
            for (int j = 0; j < N; j++)
                res[i,j] = G[i,j];
        return;
    }
 
    // Recursion call for first half
    power(G, res, n / 2);
 
    // Multiply two halves
    multiply(res, res, res);
 
    // If n is odd
    if (n % 2 != 0)
        multiply(res, G, res);
}
 
// Driver code
public static void Main()
{
    int [,]G = { { 1, 1, 1 },
                    { 0, 0, 1 },
                    { 0, 1, 0 } };
 
    int k = 2;
    int [,]res = new int[N,N];
 
    power(G, res, k);
 
    for (int i = 0; i < N; i++)
    {
        for (int j = 0; j < N; j++)
            Console.Write(res[i,j] + " ");
        Console.WriteLine("");
    }
}
}
 
// This code is contributed by anuj_67..
// This code is improved by cidacoder


Javascript




<script>
    // Javascript implementation of the approach
     
    let N = 3;
   
    // Function to multiply two matrices
    function multiply(a, b, res)
    {
        let mul = new Array(N);
        for (let i = 0; i < N; i++)
        {
            mul[i] = new Array(N);
            for (let j = 0; j < N; j++)
            {
                mul[i][j] = 0;
                for (let k = 0; k < N; k++)
                    mul[i][j] += a[i][k] * b[k][j];
            }
        }
 
        // Storing the multiplication result in res[][]
        for (let i = 0; i < N; i++)
            for (let j = 0; j < N; j++)
                res[i][j] = mul[i][j];
    }
 
    // Function to compute G raised to the power n
    function power(G, res, n)
    {
 
        // Base condition
        if (n == 1) {
            for (let i = 0; i < N; i++)
                for (let j = 0; j < N; j++)
                    res[i][j] = G[i][j];
            return;
        }
 
        // Recursion call for first half
        power(G, res, parseInt(n / 2, 10));
 
        // Multiply two halves
        multiply(res, res, res);
 
        // If n is odd
        if (n % 2 != 0)
            multiply(res, G, res);
    }
     
    let G = [ [ 1, 1, 1 ],
             [ 0, 0, 1 ],
             [ 0, 1, 0 ] ];
   
    let k = 2;
    let res = new Array(N);
    for (let i = 0; i < N; i++)
    {
        res[i] = new Array(N);
        for (let j = 0; j < N; j++)
        {
            res[i][j] = 0;
        }
    }
   
    power(G, res, k);
   
    for (let i = 0; i < N; i++)
    {
        for (let j = 0; j < N; j++)
            document.write(res[i][j] + " ");
        document.write("</br>");
    }
 
</script>


Output: 

1 2 2 
0 1 0 
0 0 1

 

Time Complexity – 
Since we have to multiply the adjacency matrix log(k) times (using matrix exponentiation), the time complexity of the algorithm is O((|V|^3)*log(k)), where V is the number of vertices, and k is the length of the path.
 


Feeling lost in the world of random DSA topics, wasting time without progress? It's time for a change! Join our DSA course, where we'll guide you on an exciting journey to master DSA efficiently and on schedule.
Ready to dive in? Explore our Free Demo Content and join our DSA course, trusted by over 100,000 geeks!

Last Updated : 19 Jul, 2021
Like Article
Save Article
Previous
Next
Similar Reads
Complete Tutorials