We are given an infinite two dimensional plane made of hexagons connected together. We can visualize this plane as a honeycomb. Element X is present on one of the cells / hexagon.
We are given N steps, the task is to calculate number of such hexagonal paths possible in which element X has to perform a walk of N steps and return back to the original hexagon, where
Examples:
Input : 1 Output : Number of walks possible is/are 0 Explanation : 0 because using just one step we can move to any of the adjacent cells but we cannot trace back to the original hexagon. Input : 2 Output : Number of walks possible is/are 6 Input : 4 Output : Number of walks possible is/are 90
Approach :
- A hexagonal walk can be defined as walking through adjacent hexagons and returning to the original cell. We know the fact that a hexagon contains six sides i.e. a hexagon is surrounded by six hexagons. Now, we have to count number of ways we take N steps and come back to the original hexagon.
- Now, let us suppose the original hexagon (where element X was initially present) to be the origin. We need all possible ways we can take (N-k) steps such that we have some steps which would trace back to our original hexagon. We can visualize this hexagon and it’s related coordinate system from the picture below.
- Now, let’s assume, our element X was present at 0:0 of the given picture. Thus, we can travel in six possible directions from a hexagon. Now, using the directions above we memorize all possible movements such that we trace back to the original 0:0 index. For memorizing we use a 3D array and we preprocess our answer for a given number of steps and then query accordingly.
Below is the implementation of above approach :
C++
// C++ implementation of counting // number of possible hexagonal walks #include <iostream> using namespace std; int depth = 16; int ways[16][16][16]; int stepNum; void preprocess( int list[]) { // We initialize our origin with 1 ways[0][8][8] = 1; // For each N = 1 to 14, we traverse in all possible // direction. Using this 3D array we calculate the // number of ways at each step and the total ways // for a given step shall be found at // ways[step number][8][8] because all the steps // after that will be used to trace back to the // original point index 0:0 according to the image. for ( int N = 1; N <= 14; N++) { for ( int i = 1; i <= depth; i++) { for ( int j = 1; j <= depth; j++) { ways[N][i][j] = ways[N - 1][i][j + 1] + ways[N - 1][i][j - 1] + ways[N - 1][i + 1][j] + ways[N - 1][i - 1][j] + ways[N - 1][i + 1][j - 1] + ways[N - 1][i - 1][j + 1]; } } // This array stores the number of ways // possible for a given step list[N] = ways[N][8][8]; } } // Driver function int main() { int list[15]; // Preprocessing all possible ways preprocess(list); int steps = 4; cout << "Number of walks possible is/are " << list[steps] << endl; return 0; } |
Java
// Java implementation of counting // number of possible hexagonal walks import java.util.*; class GFG { static int depth = 14 ; static int ways[][][] = new int [ 16 ][ 16 ][ 16 ]; static int stepNum; static void preprocess( int list[]) { // We initialize our origin with 1 ways[ 0 ][ 8 ][ 8 ] = 1 ; // For each N = 1 to 14, we traverse in // all possible direction. Using this 3D // array we calculate the number of ways // at each step and the total ways for a // given step shall be found at ways[step // number][8][8] because all the steps // after that will be used to trace back // to the original point index 0:0 // according to the image. for ( int N = 1 ; N <= 14 ; N++) { for ( int i = 1 ; i < depth; i++) { for ( int j = 1 ; j < depth; j++) { ways[N][i][j] = ways[N - 1 ][i][j + 1 ] + ways[N - 1 ][i][j - 1 ] + ways[N - 1 ][i + 1 ][j] + ways[N - 1 ][i - 1 ][j] + ways[N - 1 ][i + 1 ][j - 1 ] + ways[N - 1 ][i - 1 ][j + 1 ]; } } // This array stores the number of // ways possible for a given step list[N] = ways[N][ 8 ][ 8 ]; } } /* Driver program to test above function */ public static void main(String[] args) { int list[] = new int [ 15 ]; // Preprocessing all possible ways preprocess(list); int steps = 4 ; System.out.println( "Number of walks" + " possible is/are " + list[steps] ); } } |
Python3
# Python 3 implementation of counting # number of possible hexagonal walks depth = 16 ways = [[[ 0 for i in range ( 17 )] for i in range ( 17 )] for i in range ( 17 )] def preprocess( list , steps): # We initialize our origin with 1 ways[ 0 ][ 8 ][ 8 ] = 1 # For each N = 1 to 14, we traverse in # all possible direction. Using this 3D # array we calculate the number of ways # at each step and the total ways for a # given step shall be found at ways[step # number][8][8] because all the steps after # that will be used to trace back to the # original point index 0:0 according to the image. for N in range ( 1 , 16 , 1 ): for i in range ( 1 , depth, 1 ): for j in range ( 1 , depth, 1 ): ways[N][i][j] = (ways[N - 1 ][i][j + 1 ] + ways[N - 1 ][i][j - 1 ] + ways[N - 1 ][i + 1 ][j] + ways[N - 1 ][i - 1 ][j] + ways[N - 1 ][i + 1 ][j - 1 ] + ways[N - 1 ][i - 1 ][j + 1 ]) # This array stores the number of ways # possible for a given step list [N] = ways[N][ 8 ][ 8 ] print ( "Number of walks possible is/are" , list [steps]) # Driver Code if __name__ = = '__main__' : list = [ 0 for i in range ( 16 )] steps = 4 # Preprocessing all possible ways preprocess( list , steps) # This code is contributed by # Surendra_Gangwar |
C#
// C# implementation of counting // number of possible hexagonal walks using System; class GFG { static int depth = 14; static int [, ,]ways = new int [16,16,16]; // static int stepNum; static void preprocess( int []list) { // We initialize our origin with 1 ways[0,8,8] = 1; // For each N = 1 to 14, we traverse in // all possible direction. Using this 3D // array we calculate the number of ways // at each step and the total ways for a // given step shall be found at ways[step // number][8][8] because all the steps // after that will be used to trace back // to the original point index 0:0 // according to the image. for ( int N = 1; N <= 14; N++) { for ( int i = 1; i < depth; i++) { for ( int j = 1; j < depth; j++) { ways[N,i,j] = ways[N - 1,i,j + 1] + ways[N - 1,i,j - 1] + ways[N - 1,i + 1,j] + ways[N - 1,i - 1,j] + ways[N - 1,i + 1,j - 1] + ways[N - 1,i - 1,j + 1]; } } // This array stores the number of // ways possible for a given step list[N] = ways[N,8,8]; } } /* Driver program to test above function */ public static void Main() { int []list = new int [15]; // Preprocessing all possible ways preprocess(list); int steps = 4; Console.WriteLine( "Number of walks" + " possible is/are " + list[steps] ); } } // This code is contributed by anuj_67. |
Javascript
<script> // Javascript implementation of counting // number of possible hexagonal walks let depth = 14; let ways = new Array(16); for (let i = 0; i < 16; i++) { ways[i] = new Array(16); for (let j = 0; j < 16; j++) { ways[i][j] = new Array(16); for (let k = 0; k < 16; k++) { ways[i][j][k] = 0; } } } let stepNum; function preprocess(list) { // We initialize our origin with 1 ways[0][8][8] = 1; // For each N = 1 to 14, we traverse in // all possible direction. Using this 3D // array we calculate the number of ways // at each step and the total ways for a // given step shall be found at ways[step // number][8][8] because all the steps // after that will be used to trace back // to the original point index 0:0 // according to the image. for (let N = 1; N <= 14; N++) { for (let i = 1; i < depth; i++) { for (let j = 1; j < depth; j++) { ways[N][i][j] = ways[N - 1][i][j + 1] + ways[N - 1][i][j - 1] + ways[N - 1][i + 1][j] + ways[N - 1][i - 1][j] + ways[N - 1][i + 1][j - 1] + ways[N - 1][i - 1][j + 1]; } } // This array stores the number of // ways possible for a given step list[N] = ways[N][8][8]; } } let list = new Array(15); list.fill(0); // Preprocessing all possible ways preprocess(list); let steps = 4; document.write( "Number of walks" + " possible is/are " + list[steps] ); </script> |
Number of walks possible is/are 90
The time complexity of the above code is and the space complexity is also similar due to the 3D array used.
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