def find_connected_components(G: Graph):
old_representation = G.representation_type
G.change_graph_representation_to("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 + 1)
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)
distance_matrix.append(d_s)
return distance_matrix
def print_distance_matrix(G: Graph):
G.print_graph_representation()
m = calculate_distance_matrix(G)
for i in range(len(m)):
print(m[i])
if __name__ == "__main__":
#examples
graph = _generate_connected_graph(10)
gr_cpy = deepcopy(graph.graph_representation)
add_connection_weights(graph, 1, 10)
print_distance_matrix(graph)
graph_to_draw = Graph("adjacency_matrix", gr_cpy)
plot_graph(graph_to_draw)
def main():
k = randrange(0, 6)
graph = generate_k_regular_graph(k)
print(f"generated {k}_regular graph")
plot_graph(graph)
def generate_graph_from_graphic_string(A):
if not is_graphic_string(A):
raise Exception("To nie jest ciag graficzny")
list.sort(A, reverse=True)
n = len(A)
matrix = [[0 for i in range(n)] for j in range(n)]
mod_A = [[i, A[i]] for i in range(n)]
while sum([n[1] for n in mod_A]):
list.sort(mod_A, key=lambda x: x[1], reverse=True)
for i in range(1, mod_A[0][1] + 1):
mod_A[i][1] = mod_A[i][1] - 1
mod_A[0][1] = mod_A[0][1] - 1
matrix[mod_A[i][0]][mod_A[0][0]] = 1
matrix[mod_A[0][0]][mod_A[i][0]] = 1
graph = Graph.create_graph_representation("adjacency_matrix", matrix)
return graph
if __name__ == "__main__":
A = [4, 2, 2, 3, 2, 1, 4, 2, 2, 2, 2]
B = [4, 4, 3, 1, 2]
graph = generate_graph_from_graphic_string(A)
plot_graph(graph)
randomize_edges(graph, 5)
plot_graph(graph)
def generate_connected_graph(max_vertex_count, min_weight, max_weight): graph = _generate_connected_graph(max_vertex_count) plot_graph(graph) add_connection_weights(graph, min_weight, max_weight) graph.print_graph_representation()