def main():
cube = Cube()
print '=========== initial ============'
cube.show()
print cube.calculate_feature_string()
print cube.check()
print ''
command = raw_input("Command: ").upper()
while command != 'Q':
if command not in command_map:
print("Invalid input. Input again.")
continue
cube.transform(command_map[command])
print '=========== %s ============' % command
print ''
cube.show()
print ''
command = raw_input("Command: ").upper()
def test_transform():
result_file = 'tmp_result.txt'
benchmark_file = 'ut_result.txt'
cube = Cube()
with open(result_file, 'w') as result_fp:
cube.show(result_fp)
for command in command_list:
for i in range(0, 4):
result_fp.write('=========== %s ============\n' % command)
cube.transform(command_list[command])
cube.show(result_fp)
benchmark = open(result_file, 'U').readlines()
result = open(benchmark_file, 'U').readlines()
diff = unified_diff(benchmark, result, benchmark_file, result_file)
print 'Diff between benchmark and result.\n'
stdout.writelines(diff)
print '\nTest transform done.'
def test_shuffle():
cube = Cube()
game = Game(cube)
game.shuffle()
step = len(game.shuffle_full_steps)
print '=========== initialized with %s-step shuffle ============' % step
cube.show()
print ''
print 'Feature string is ', cube.calculate_feature_string()
print 'Is standard? ', cube.check()
command = raw_input("Command: ").upper()
while command != 'Q':
if command not in command_map:
print("Invalid input. Input again.")
continue
cube.transform(command_map[command])
print '=========== %s ============' % command
print ''
cube.show()
print ''
command = raw_input("Command: ").upper()
def test_bayesian():
cube = Cube()
cube.transform(F)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[-F + DIRECTION_OFFSET])
cube.transform(B)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[-B + DIRECTION_OFFSET])
cube.transform(-B)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[B + DIRECTION_OFFSET])
cube.transform(R)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[-R + DIRECTION_OFFSET])
cube.transform(L)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[-L + DIRECTION_OFFSET])
cube.transform(B)
bayesian.add_feature_and_decision(cube.feature_string, DIRECTIONS[-B + DIRECTION_OFFSET])
print_possibility()
bayesian.export('bayesiantest.yaml')
bayesian.load('bayesiantest.yaml')
print_possibility()