Adjacency Matrix

adjacency matrix is way of representing graph as matrix of booleans (0's and 1's)
finite graph can be represented in form of a square matrix, where boolean value of matrix indicates if there is a direct path between two vertices

example graph: see examples/06_GRAPH_BASED_DSA/_images/basic-undirected-graph

represented as matrix:

// Graph adjacency matrix

    0   1   2   3
  -----------------
0 | 0 | 1 | 1 | 1 |
  -----------------
1 | 1 | 0 | 1 | 0 |
  -----------------
2 | 1 | 1 | 0 | 0 |
  -----------------
3 | 1 | 0 | 0 | 0 |
  -----------------

see examples/06_GRAPH_BASED_DSA/_images/adjacency-matrix/adjacency-matrix_graph-representation_1

each cell represented as A[i][j], where i and j are vertices
value of A[i][j] is either 1 or 0 depending on whether there is an edge from vertex i to vertex j

Pros of Adjacency Matrix

basic operations such as adding edge, removing edge, checking existence of edge from vertex i to vertex j are extremly time efficient (constant time operations)
if graph is dense and number of edges is large, adjacency matrix should be first choice
- even if graph and adjacency matrix are sparse, can be represented using data structures for sparse matrices
biggest advantage comes from use of matrices
- recent advances in hardware enable performing expensive matrix operations on GPU
by performing operations on adjacency matrix, can get important insights into nature of graph and relationship between its vertices

Cons of Adjacency Matrix

VxV space requirement of adjacency matrix makes it a memory hog
- graphs "out in the wild" usually don't have too many connections, which is major reason why adjacency lists are usually better
operations like inEdges and outEdges are expensive when using adjacency matrix representation

Implementations

Python

class Graph(object):

    # Initialize the matrix
    def __init__(self, size):
        self.adjMatrix = []
        for i in range(size):
            self.adjMatrix.append([0 for i in range(size)])
        self.size = size

    # Add edges
    def add_edge(self, v1, v2):
        if v1 == v2:
            print("Same vertex %d and %d" % (v1, v2))
        self.adjMatrix[v1][v2] = 1
        self.adjMatrix[v2][v1] = 1

    # Remove edges
    def remove_edge(self, v1, v2):
        if self.adjMatrix[v1][v2] == 0:
            print("No edge between %d and %d" % (v1, v2))
            return
        self.adjMatrix[v1][v2] = 0
        self.adjMatrix[v2][v1] = 0

    def __len__(self):
        return self.size

    # Print the matrix
    def print_matrix(self):
        for row in self.adjMatrix:
            for val in row:
                print('{:4}'.format(val)),
            print


def main():
    g = Graph(5)
    g.add_edge(0, 1)
    g.add_edge(0, 2)
    g.add_edge(1, 2)
    g.add_edge(2, 0)
    g.add_edge(2, 3)

    g.print_matrix()


if __name__ == '__main__':
    main()

C++

#include <iostream>
using namespace std;

class Graph {
   private:
  bool** adjMatrix;
  int numVertices;

   public:
  // Initialize the matrix to zero
  Graph(int numVertices) {
    this->numVertices = numVertices;
    adjMatrix = new bool*[numVertices];
    for (int i = 0; i < numVertices; i++) {
      adjMatrix[i] = new bool[numVertices];
      for (int j = 0; j < numVertices; j++)
        adjMatrix[i][j] = false;
    }
  }

  // Add edges
  void addEdge(int i, int j) {
    adjMatrix[i][j] = true;
    adjMatrix[j][i] = true;
  }

  // Remove edges
  void removeEdge(int i, int j) {
    adjMatrix[i][j] = false;
    adjMatrix[j][i] = false;
  }

  // Print the martix
  void toString() {
    for (int i = 0; i < numVertices; i++) {
      cout << i << " : ";
      for (int j = 0; j < numVertices; j++)
        cout << adjMatrix[i][j] << " ";
      cout << "\n";
    }
  }

  ~Graph() {
    for (int i = 0; i < numVertices; i++)
      delete[] adjMatrix[i];
    delete[] adjMatrix;
  }
};

int main() {
  Graph g(4);

  g.addEdge(0, 1);
  g.addEdge(0, 2);
  g.addEdge(1, 2);
  g.addEdge(2, 0);
  g.addEdge(2, 3);

  g.toString();
}

Java

public class Graph {
  private boolean adjMatrix[][];
  private int numVertices;

  // Initialize the matrix
  public Graph(int numVertices) {
    this.numVertices = numVertices;
    adjMatrix = new boolean[numVertices][numVertices];
  }

  // Add edges
  public void addEdge(int i, int j) {
    adjMatrix[i][j] = true;
    adjMatrix[j][i] = true;
  }

  // Remove edges
  public void removeEdge(int i, int j) {
    adjMatrix[i][j] = false;
    adjMatrix[j][i] = false;
  }

  // Print the matrix
  public String toString() {
    StringBuilder s = new StringBuilder();
    for (int i = 0; i < numVertices; i++) {
      s.append(i + ": ");
      for (boolean j : adjMatrix[i]) {
        s.append((j ? 1 : 0) + " ");
      }
      s.append("\n");
    }
    return s.toString();
  }

  public static void main(String args[]) {
    Graph g = new Graph(4);

    g.addEdge(0, 1);
    g.addEdge(0, 2);
    g.addEdge(1, 2);
    g.addEdge(2, 0);
    g.addEdge(2, 3);

    System.out.print(g.toString());
  }
}

Adjacency Matrix Applications

creating routing table in networks
navigation tasks

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