def test_get_state(self):
string = "23041"
conv = NQueensConverter(5)
expected_board = NQueensBoard(5)
expected_board.add_queen_at(XYLocation(0, 2))
expected_board.add_queen_at(XYLocation(1, 3))
expected_board.add_queen_at(XYLocation(2, 0))
expected_board.add_queen_at(XYLocation(3, 4))
expected_board.add_queen_at(XYLocation(4, 1))
self.assertEqual(expected_board, conv.get_state(string))
def test_get_state(self):
string = "23041"
conv = NQueensConverter(5)
expected_board = NQueensBoard(5)
expected_board.add_queen_at(XYLocation(0, 2))
expected_board.add_queen_at(XYLocation(1, 3))
expected_board.add_queen_at(XYLocation(2, 0))
expected_board.add_queen_at(XYLocation(3, 4))
expected_board.add_queen_at(XYLocation(4, 1))
self.assertEqual(expected_board, conv.get_state(string))
def main():
succeeded = 0
for i in range(NUMBER_OF_TASKS):
print("Iteration number " + str(i))
boards = [create_random_board() for i in range(50)]
print("Created boards:")
for board in boards:
print(str(board))
print("\n")
p = GeneticProblem(boards, NQueensGoalTest(), NQueensConverter(SIZE))
ga = GeneticAlgorithm(0.1)
best_state = ga.search(p, AttackingPairHeuristic(), 100)
if ga.failed:
print("Search Failed")
else:
print("Search Succeeded")
succeeded += 1
print("Final state:")
print(str(best_state))
print("\n\n")
print("Succeeded " + str(succeeded) + "/" + str(NUMBER_OF_TASKS))
def test_get_alphabet(self):
conv = NQueensConverter(5)
expected_alphabet = ['0', '1', '2', '3', '4']
self.assertSameElements(set(expected_alphabet),
set(conv.get_alphabet()))
def test_get_length(self):
length = 5
conv = NQueensConverter(length)
self.assertEqual(length, conv.get_individual_length())
def test_get_alphabet(self):
conv = NQueensConverter(5)
expected_alphabet = ['0', '1', '2', '3', '4']
self.assertSameElements(set(expected_alphabet), set(conv.get_alphabet()))
def test_get_length(self):
length = 5
conv = NQueensConverter(length)
self.assertEqual(length, conv.get_individual_length())
