def find_euler_cycle(self, graph: GraphRepresentation) -> list:
graph.convert(GraphRepresentationType.ADJACENCY_MATRIX)
self.adjacency_matrix = deepcopy(graph.math_repr)
self.no_nodes = len(graph.math_repr)
self.depth_first_search(0)
string_repr = "->".join(str(first) for first in self.result)
print(string_repr)
return self.result
def randomize_graph(graph: GraphRepresentation, number_of_randomization: int) -> GraphRepresentation:
"""
randomize_graph method randomizes given graph specific number of times
:param graph: GraphRepresentation type graph
:param number_of_randomization: Int type number of randomization
:return: Randomized graph
:rtype: Adjacency Matrix GraphRepresentation
"""
graph.convert(GraphRepresentationType.ADJACENCY_MATRIX)
adjacency_matrix = graph.math_repr
number_of_nodes = len(adjacency_matrix)
for step in range(number_of_randomization):
while True:
while True:
node_a = randint(0, number_of_nodes - 1)
node_b = randint(0, number_of_nodes - 1)
if ((adjacency_matrix[node_a][node_b] == adjacency_matrix[node_b][node_a]) and (
adjacency_matrix[node_b][node_a] == 1)) and node_a != node_b:
break
while True:
node_c = randint(0, number_of_nodes - 1)
node_d = randint(0, number_of_nodes - 1)
if ((adjacency_matrix[node_c][node_d] == adjacency_matrix[node_d][node_c]) and (
adjacency_matrix[node_c][node_d] == 1)) and node_c != node_d:
break
if (adjacency_matrix[node_a][node_d] == 0) and (
adjacency_matrix[node_b][node_c] == 0) and node_a != node_d and node_b != node_c \
and node_a != node_c:
break
adjacency_matrix[node_a][node_b] = 0
adjacency_matrix[node_b][node_a] = 0
adjacency_matrix[node_c][node_d] = 0
adjacency_matrix[node_d][node_c] = 0
adjacency_matrix[node_a][node_d] = 1
adjacency_matrix[node_d][node_a] = 1
adjacency_matrix[node_b][node_c] = 1
adjacency_matrix[node_c][node_b] = 1
randomized_graph = GraphRepresentation(GraphRepresentationType.ADJACENCY_MATRIX, adjacency_matrix)
return randomized_graph
from core.graph_representation import GraphRepresentationType, GraphRepresentation
if __name__ == "__main__":
matrix = [[0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0],
[1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1],
[0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]]
graph = GraphRepresentation(GraphRepresentationType.ADJACENCY_MATRIX,
matrix)
graph.convert(GraphRepresentationType.ADJACENCY_LIST)
print(graph)
graph.convert(GraphRepresentationType.ADJACENCY_MATRIX)
print(graph)
graph.convert(GraphRepresentationType.INCIDENCE_MATRIX)
print(graph)
from algorithms.graph_randomization import randomize_graph
from core.graph_representation import GraphRepresentationType, GraphRepresentation
if __name__ == "__main__":
adjacency_matrix = [[0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0],
[1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1],
[0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]]
graph = GraphRepresentation(GraphRepresentationType.ADJACENCY_MATRIX,
adjacency_matrix)
graph.convert(GraphRepresentationType.ADJACENCY_LIST)
graph.display()
print(graph)
randomized_graph = randomize_graph(graph, 10)
randomized_graph.convert(GraphRepresentationType.ADJACENCY_LIST)
randomized_graph.display()
print(randomized_graph)
def __init__(self, graph: GraphRepresentation):
graph.convert(GraphRepresentationType.ADJACENCY_MATRIX)
self.adjacency_matrix = graph.math_repr
self.number_of_nodes = len(self.adjacency_matrix)
self.stack = [-1] * self.number_of_nodes
self.stack[0] = 0