def replay(self):
board = Board.load(self.initial_state)
print(board.pprint())
for i, move in enumerate(self.moves):
print('Q', self.q_assessments[i])
board.move(move)
print(board.pprint())
def test_export_parse(self):
board = Board(size=9, win_chain_length=5)
for i in range(10):
board.make_random_move()
parsed_board = Board.load(board.export())
self.assertEqual(board.pprint(lastmove_highlight=False), parsed_board.pprint(lastmove_highlight=False))
self.assertFalse(parsed_board.game_over())
self.assertFalse(parsed_board.game_won())
self.assertTrue(np.equal(parsed_board._matrix, board._matrix).all())
def iterate_on(self, record):
board = Board.load(record.get_initial_state())
q_assessments = record.get_q_assessments()
for i, move in enumerate(record.get_moves()):
if record.get_winning_player() == board.get_player_to_move():
self.make_feature_tensors(board, move, q_assessments[i][0],
q_assessments[i][1])
# learn drawn positions
elif record.get_winning_player() == Player.NONE:
self.make_feature_tensors(board, move, q_assessments[i][0],
q_assessments[i][1])
board.move(move)