def print_dijkstra(G: Graph, s):
old_representation = G.representation_type
graph.change_graph_representation_to(
GraphRepresentationType.ADJACENCY_MATRIX)
p_s, d_s = dijkstra(G, s)
w = G.graph_weights
G.print_graph_representation()
G.print_weights()
print("\nSTART: s =", s)
for v in range(len(p_s)):
path = []
print('d({}) = {:>4} ===> '.format(v, d_s[v]), end='')
currNode = v
path.append(currNode)
while p_s[currNode] != None:
currNode = p_s[currNode]
path.append(currNode)
path = path[::-1] # reversing
print(path)
plot_graph(graph)
G.change_graph_representation_to(old_representation)
def check_if_eulerian(G: Graph):
old_representation_type = G.representation_type
G.change_graph_representation_to(GraphRepresentationType.ADJACENCY_LIST)
old_graph_representation = copy.deepcopy(G.graph_representation)
starting_vertex = 0
path = []
if(len(G.graph_representation) == 1): # graf składa się z jednego wierzchołka
return True, path
else:
for key, l in G.graph_representation.items(): # jezeli jakis wierzcholek jest odosobniony
if(len(l) == 0):
return False, path
last_vertex = choose_edge_and_delete(G, starting_vertex, path)
is_eulerian_graph = last_vertex == starting_vertex and check_if_graph_has_no_edges(G)
G.graph_representation = old_graph_representation
G.change_graph_representation_to(old_representation_type)
return is_eulerian_graph, path
def find_connected_components(G: Graph):
old_representation = G.representation_type
graph.change_graph_representation_to(
GraphRepresentationType.ADJACENCY_LIST)
comp = components(graph)
number_of_connected_components = max(comp)
connected_components_list = []
for i in range(number_of_connected_components):
connected_components_list.append([])
for j in range(len(G.graph_representation)):
if (i + 1 == comp[j]):
connected_components_list[i].append(j)
for i in range(len(connected_components_list)):
temp_str = f"{i + 1}: "
for c in connected_components_list[i]:
temp_str = temp_str + f"{c} "
print(temp_str)
plot_graph(graph, comp)
G.change_graph_representation_to(old_representation)
def swap_two_pairs_of_nodes(graph: Graph):
max_iter = 10000
while True:
a, b = get_random_two_connected_nodes(graph)
c, d = get_random_two_connected_nodes(graph)
matrix = graph.graph_representation
if(a != d and b != c and a != c and b != d and matrix[a][d] == 0 and matrix[b][c] == 0):
matrix[a][b] = matrix[b][a] = matrix[c][d] = matrix[d][c] = 0
matrix[a][d] = matrix[d][a] = matrix[c][b] = matrix[b][c] = 1
graph.change_graph_representation_to(GraphRepresentationType.ADJACENCY_LIST)
checker = HamiltonChecker(graph)
checker.check_hamilton(0)
result = checker.is_hamiltionian()[0]
graph.change_graph_representation_to(GraphRepresentationType.ADJACENCY_MATRIX)
if result == False:
matrix[a][b] = matrix[b][a] = matrix[c][d] = matrix[d][c] = 1
matrix[a][d] = matrix[d][a] = matrix[c][b] = matrix[b][c] = 0
continue
return
max_iter -= 1
if max_iter == 0:
raise Exception("Graph cannot be randomized")
from utils.graph import Graph,GraphRepresentationType
from utils.graphRandomizer import generate_Gnl_graph
if __name__ == "__main__":
with open ('input/input.txt', 'r') as graph_input:
graph_input = graph_input.readlines()
representation_type = check_type_of_input(graph_input)
parsed_graph_input = parse_graph_input(representation_type, graph_input)
graph = Graph(representation_type, parsed_graph_input)
graph.print_graph_representation()
menu = '''
1. Change to ADJACENCY_LIST
2. Change to ADJACENCY_MATRIX
3. Change to INCIDENCE_MATRIX
4. EXIT
Your choice : '''
while True:
print(menu)
choice = int(input())
if 1 <= choice <= 3 :
graph.change_graph_representation_to(GraphRepresentationType(choice))
elif choice == 4:
break
else:
print("Bad input, try again !")
continue
graph.print_graph_representation()
"1. ",
"2. 0 4",
"3. ",
"4. 0 2"]
graph_input = graph_input2
representation_type = check_type_of_input(graph_input)
parsed_graph_input = parse_graph_input(representation_type, graph_input)
graph = Graph(representation_type, parsed_graph_input)
delete_edge(graph, 1, 3)
graph = generate_Gnp_graph(5, 0.5)
graph.change_graph_representation_to(GraphRepresentationType.ADJACENCY_LIST)
graph.print_graph_representation()
if_eulerian = check_if_eulerian(graph)
print(f"Czy graf jest eulerowski: {if_eulerian}")
if(if_eulerian):
plot_graph(graph)
findEulerianGraph = False
if(findEulerianGraph):
