W3Schools Tryit Editor

Python

Java

class Graph:
    def __init__(self, size):
        self.adj_matrix = [[0] * size for _ in range(size)]
        self.size = size
        self.vertex_data = [''] * size

def add_edge(self, u, v, weight):
        if 0 <= u < self.size and 0 <= v < self.size:
            self.adj_matrix[u][v] = weight
            self.adj_matrix[v][u] = weight  # For undirected graph

def add_vertex_data(self, vertex, data):
        if 0 <= vertex < self.size:
            self.vertex_data[vertex] = data

def dijkstra(self, start_vertex_data):
        start_vertex = self.vertex_data.index(start_vertex_data)
        distances = [float('inf')] * self.size
        distances[start_vertex] = 0
        visited = [False] * self.size

for _ in range(self.size):
            min_distance = float('inf')
            u = None
            for i in range(self.size):
                if not visited[i] and distances[i] < min_distance:
                    min_distance = distances[i]
                    u = i

if u is None:
                break

visited[u] = True

for v in range(self.size):
                if self.adj_matrix[u][v] != 0 and not visited[v]:
                    alt = distances[u] + self.adj_matrix[u][v]
                    if alt < distances[v]:
                        distances[v] = alt

return distances

g = Graph(7)

g.add_vertex_data(0, 'A')
g.add_vertex_data(1, 'B')
g.add_vertex_data(2, 'C')
g.add_vertex_data(3, 'D')
g.add_vertex_data(4, 'E')
g.add_vertex_data(5, 'F')
g.add_vertex_data(6, 'G')

g.add_edge(3, 0, 4)  # D - A, weight 5
g.add_edge(3, 4, 2)  # D - E, weight 2
g.add_edge(0, 2, 3)  # A - C, weight 3
g.add_edge(0, 4, 4)  # A - E, weight 4
g.add_edge(4, 2, 4)  # E - C, weight 4
g.add_edge(4, 6, 5)  # E - G, weight 5
g.add_edge(2, 5, 5)  # C - F, weight 5
g.add_edge(2, 1, 2)  # C - B, weight 2
g.add_edge(1, 5, 2)  # B - F, weight 2
g.add_edge(6, 5, 5)  # G - F, weight 5

# Dijkstra's algorithm from D to all vertices
print("Dijkstra's Algorithm starting from vertex D:\n")
distances = g.dijkstra('D')
for i, d in enumerate(distances):
    print(f"Shortest distance from D to {g.vertex_data[i]}: {d}")

#Python

​x
 
class Graph:    def __init__(self, size):        self.adj_matrix = [[0] * size for _ in range(size)]        self.size = size        self.vertex_data = [''] * size​    def add_edge(self, u, v, weight):        if 0 <= u < self.size and 0 <= v < self.size:            self.adj_matrix[u][v] = weight            self.adj_matrix[v][u] = weight  # For undirected graph​    def add_vertex_data(self, vertex, data):        if 0 <= vertex < self.size:            self.vertex_data[vertex] = data​    def dijkstra(self, start_vertex_data):        start_vertex = self.vertex_data.index(start_vertex_data)        distances = [float('inf')] * self.size        distances[start_vertex] = 0        visited = [False] * self.size​        for _ in range(self.size):            min_distance = float('inf')            u = None            for i in range(self.size):                if not visited[i] and distances[i] < min_distance:                    min_distance = distances[i]                    u = i​            if u is None:                break​            visited[u] = True​            for v in range(self.size):                if self.adj_matrix[u][v] != 0 and not visited[v]:                    alt = distances[u] + self.adj_matrix[u][v]                    if alt < distances[v]:                        distances[v] = alt​        return distances​g = Graph(7)​g.add_vertex_data(0, 'A')