def test_execute_move_legal(self):
# current player is p1
game = GameWrapper(1)
# place a piece, to flip (3,5)
env_observation, reward, done, game, is_valid = game.execute_move(8 *
3 +
5)
# expection:
# player switched,
# not done game,
# new board observation,
# reward 0.01, +1 new pieces
self.assertTrue(is_valid)
self.assertEqual(game.current_player, GameBoard.PLAYER_2)
self.assertFalse(done)
self.assertEqual(reward, 0.01)
np.testing.assert_array_equal(
env_observation,
np.asarray([
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, -1.0, -1.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
-1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0
]))
def test_execute_move_pass(self):
game = GameWrapper(1)
old_observation = game.reset()
env_observation, reward, done, game, is_valid = game.execute_move(
game.PASS_TURN_ACTION)
self.assertTrue(is_valid)
np.testing.assert_array_equal(env_observation, old_observation * -1)
self.assertEqual(reward, -0.01)
self.assertFalse(done)
def test_execute_move_illegal(self):
game = GameWrapper(1)
old_player = game.current_player
# place at the corner. Not a valid move.
env_observation, reward, done, game, is_valid = game.execute_move(0)
# expecting: player not switched, same board observation, reward -0.01
self.assertFalse(is_valid)
self.assertEqual(old_player, game.current_player)
self.assertEqual(reward, -0.01)
self.assertFalse(done)
np.testing.assert_array_equal(
env_observation,
np.asarray([
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -1.0,
1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0
]))
def test_execute_move_tie_p2(self):
game_env = GameWrapper(1)
game_env.current_player = GameBoard.PLAYER_2
game_env.game_board.board = \
list(map(lambda r: list(map(lambda i: i * -1.0, r)),
[[-1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, ],
[-1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, ],
[-1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, ],
[-1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, ],
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ],
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ],
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ],
[1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, 0.0]]))
# place at the last spot to win
env_observation, reward, done, game_env, is_valid = game_env.execute_move(
63)
# expection:
# player switched to p1,
# game is done
# new board observation,
# reward 0.01, +1 new pieces
self.assertTrue(is_valid)
self.assertEqual(game_env.current_player, GameBoard.PLAYER_2)
self.assertTrue(done)
self.assertEqual(reward, 0)
np.testing.assert_array_equal(
env_observation,
np.asarray([
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
-1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
]))
def test_execute_move_win(self):
game_env = GameWrapper(1)
game_env.game_board.board = [[
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
], [1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, 0.0]]
# place at the last spot to win
env_observation, reward, done, game_env, is_valid = game_env.execute_move(
63)
# expection:
# player switched to p1,
# game is done
# new board observation,
# reward 0.01, +1 new pieces
self.assertTrue(is_valid)
self.assertEqual(game_env.current_player, GameBoard.PLAYER_1)
self.assertTrue(done)
self.assertEqual(reward, 64)
np.testing.assert_array_equal(
env_observation,
np.asarray([
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
]))