def __init__(self, path):
start = time.time()
print('Setting up graph')
g = Graph(path)
print('Graph set up in %s seconds' % (time.time() - start))
algo_list = ['[1]DFS']
algo_keys = [1]
#print(g)
#input_var = input("Which algorithm would you like to test? The available ones are: " + str(algo_list))
#if int(input_var) not in algo_keys:
# print('Wrong input, try again!')
#elif int(input_var) is 1:
# print('DFS!')
start = time.time()
print('beginning DFS...')
solved = dfs(g)
print('DFS finished in %s seconds' % (time.time() - start))
if solved:
pass
#g.maze.paint_solved_path(solved)
#g.maze.save_solved(path)
else:
print('No solution found!')
g.maze.save_solved(path)
def get_set(self, index):
fuzzy_matrix = self.get_fuzzy_matrix(index)
# print "fuzzy_matrix %d " % index
# print fuzzy_matrix
assert fuzzy_matrix.shape[0] == fuzzy_matrix.shape[1]
r = fuzzy_matrix.shape[0]
sets = [] # 分类集合
set_matrix = np.ndarray(shape=fuzzy_matrix.shape, dtype=int)
for i in range(r):
for j in range(r):
if i == j:
set_matrix[i][j] = 1
elif fuzzy_matrix[i][j] < self.threshold[index]:
set_matrix[i][j] = 0
else:
set_matrix[i][j] = 1
# set_matrix中，值为1说明属于一个集合,否则属于不同集合
# print "set matrix = ",set_matrix
# 把set_matrix看成一个邻接矩阵，DFS就可以得到的联通分量的个数，也就是集合的个数
# 以上得到两两的集合，下面合并集合
# set_num 集合的个数
# sets 聚类后的集合
file_object = open('fuzzy_matrix.txt', 'w')
# print "set matrix = "
#print set_matrix
file_object.write(str(fuzzy_matrix.tolist()))
#print "set matrix shape = ",set_matrix.shape
sets = dfs(set_matrix)
return sets
from time import time
from DFS import dfs
from puzzle import Puzzle
initial_state = [2, 8, 3, 1, 6, 4, 7, 0, 5]
Puzzle.num_of_instances = 0
t0 = time()
solution = dfs(initial_state)
t1 = time() - t0
print('Solution:', solution)
print('space:', Puzzle.num_of_instances)
print('time:', t1, "seconds")
print()
from Node import Node
from DFS import dfs
node1 = Node("A")
node2 = Node("B")
node3 = Node("C")
node4 = Node("D")
node5 = Node("E")
node6 = Node("F")
node1.neighbourList.append(node2)
node1.neighbourList.append(node3)
node2.neighbourList.append(node4)
node2.neighbourList.append(node5)
node3.neighbourList.append(node6)
dfs(node1)