Example: dijkstra's algorithm
# Providing the graph
n = int(input("Enter the number of vertices of the graph"))
# using adjacency matrix representation
vertices = [[0, 0, 1, 1, 0, 0, 0],
[0, 0, 1, 0, 0, 1, 0],
[1, 1, 0, 1, 1, 0, 0],
[1, 0, 1, 0, 0, 0, 1],
[0, 0, 1, 0, 0, 1, 0],
[0, 1, 0, 0, 1, 0, 1],
[0, 0, 0, 1, 0, 1, 0]]
edges = [[0, 0, 1, 2, 0, 0, 0],
[0, 0, 2, 0, 0, 3, 0],
[1, 2, 0, 1, 3, 0, 0],
[2, 0, 1, 0, 0, 0, 1],
[0, 0, 3, 0, 0, 2, 0],
[0, 3, 0, 0, 2, 0, 1],
[0, 0, 0, 1, 0, 1, 0]]
# Find which vertex is to be visited next
def to_be_visited():
global visited_and_distance
v = -10
for index in range(num_of_vertices):
if visited_and_distance[index][0] == 0 \
and (v < 0 or visited_and_distance[index][1] <=
visited_and_distance[v][1]):
v = index
return v
num_of_vertices = len(vertices[0])
visited_and_distance = [[0, 0]]
for i in range(num_of_vertices-1):
visited_and_distance.append([0, sys.maxsize])
for vertex in range(num_of_vertices):
# Find next vertex to be visited
to_visit = to_be_visited()
for neighbor_index in range(num_of_vertices):
# Updating new distances
if vertices[to_visit][neighbor_index] == 1 and
visited_and_distance[neighbor_index][0] == 0:
new_distance = visited_and_distance[to_visit][1]
+ edges[to_visit][neighbor_index]
if visited_and_distance[neighbor_index][1] > new_distance:
visited_and_distance[neighbor_index][1] = new_distance
visited_and_distance[to_visit][0] = 1
i = 0
# Printing the distance
for distance in visited_and_distance:
print("Distance of ", chr(ord('a') + i),
" from source vertex: ", distance[1])
i = i + 1