def __init__(self, p1=None, p2=None):
self._board = BoardDrop(ConnectFour._COLUMN, ConnectFour._ROW)
self._p1 = p1 if not p1 is None else Player("Player 1", Token.A)
self._p2 = p2 if not p2 is None else Player("Player 2", Token.B)
self._current_player = self._p1
self._winner_player = None
self._is_over = False
self._history = list()
self._moves = [i for i in range(ConnectFour._COLUMN)]
self._patterns = [np.full(4, token) for token in [Token.A, Token.B]]
def test_pos(self):
p1 = Player("AI_1", Token.A, True)
p2 = Player("AI_2", Token.B, True)
game = ConnectFour(p1=p1, p2=p2)
moves = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 2, 1, 2]
for m in moves:
game.play(m)
self.assertEqual(game.current_player, p1)
depth = 2
ai = Minmax_AB_Parallel(p1, depth)
self.assertEqual(ai.compute(game), 3)
def test_minmax_d1(self):
'''
XX-
OO-
XO-
Simulate max loop and calling min evaluation
'''
ai_player = Player("AI_1", Token.A, True)
game = TicTacToe(p1=ai_player)
depth = 1
minmax = Minmax(ai_player, depth)
game.play(Point(0, 0))
game.play(Point(0, 1))
game.play(Point(1, 0))
game.play(Point(1, 1))
game.play(Point(0, 2))
game.play(Point(1, 2))
game.play(Point(2, 0))
val, _ = minmax._min(game, depth)
self.assertEqual(val, Minmax.WIN_POINT + depth)
game.undo()
game.play(Point(2, 1))
val, _ = minmax._min(game, depth)
self.assertEqual(val, Minmax.DRAW_POINT)
game.undo()
game.play(Point(2, 2))
val, _ = minmax._min(game, depth)
self.assertEqual(val, Minmax.LOOSE_POINT)
game.undo()
def test_evaluate_d1(self):
'''
X|X|X
O|O|-
-|-|-
'''
ai_player = Player("AI_1", Token.A, True)
game = TicTacToe(p1=ai_player)
minmax = Minmax(ai_player, 7)
depth = 10
self.assertEqual(minmax._evaluate(game, depth, Token.A),
Minmax.DRAW_POINT)
self.assertEqual(minmax._evaluate(game, depth, Token.B),
Minmax.DRAW_POINT)
game.play(Point(0, 0))
game.play(Point(0, 1))
game.play(Point(1, 0))
game.play(Point(1, 1))
game.play(Point(2, 0))
self.assertEqual(minmax._evaluate(game, depth, Token.A),
Minmax.WIN_POINT + depth)
self.assertEqual(minmax._evaluate(game, depth, Token.B),
Minmax.LOOSE_POINT - depth)
def test_minmax_d2(self):
'''
O|-|X
X|X|O
O|-|-
'''
ai_player = Player("AI_1", Token.A, True)
game = TicTacToe(p1=ai_player)
depth = 2
minmax = Minmax(ai_player, depth)
game.play(Point(2, 0))
game.play(Point(0, 0))
game.play(Point(0, 1))
game.play(Point(0, 2))
game.play(Point(1, 1))
game.play(Point(2, 1))
game.play(Point(1, 0))
val, _ = minmax._min(game, depth)
self.assertEqual(val, Minmax.DRAW_POINT)
game.undo()
game.play(Point(1, 2))
val, _ = minmax._min(game, depth)
self.assertEqual(val, Minmax.DRAW_POINT)
game.undo()
def __init__(self, p1=None, p2=None, size=9, line_win_size=5):
self._board = Board(size, size)
self._line_win_size = line_win_size
self._p1 = p1 if not p1 is None else Player("Player 1", Token.A)
self._p2 = p2 if not p2 is None else Player("Player 2", Token.B)
assert (not (self._p1.token == self._p2.token))
self._current_player = self._p1
self._winner_player = None
self._is_over = False
self._history = list()
self._moves_remaining = set(
[Point(x, y) for y in range(size) for x in range(size)])
self._patterns = [
np.full(self._line_win_size, token)
for token in [Token.A, Token.B]
]
def test_gomoku(self):
from game.gomoku import Gomoku
n = 2
depth = 4
p1 = Player("AI_1", Token.A, True)
duration = 0
for i in range(n):
game = Gomoku(p1=p1, size=9)
minmax = Minmax_AB_Parallel(p1, depth)
moves = [
Point(4, 4),
Point(3, 3),
Point(4, 3),
Point(3, 4),
Point(3, 2),
Point(4, 5)
]
for m in moves:
game.play(m)
start = time.time()
minmax.compute(game)
duration += time.time() - start
print('Duration {}'.format(duration / n))
r = expected['gomoku']
delta = r * 3 / 100
self.assertAlmostEqual(duration / n, r, delta=delta)
def main():
pr = cProfile.Profile()
pr.enable()
depth = 9
p1 = Player("AI_1", Token.A, True)
game = TicTacToe(p1=p1)
minmax = Minmax_AlphaBeta(p1, depth)
# moves = [Point(4, 4), Point(3, 3), Point(4, 3),
# Point(3, 4), Point(3, 2), Point(4, 5)]
# for m in moves:
# game.play(m)
minmax.compute(game)
pr.disable()
# Construct stats
ps = pstats.Stats(pr)
ps.strip_dirs()
# ps.sort_stats(SortKey.CUMULATIVE)
ps.sort_stats('tottime')
ps.print_stats()
ps.print_callers()
def test_print_and_export(self):
p1 = Player("AI_1", Token.A, True)
minmax = Minmax_AlphaBeta_Tree(p1, 3)
game = ConnectFour(p1=p1)
minmax.compute(game)
# print(minmax)
minmax.to_picture()
def test_export_json(self):
depth = 4
p1 = Player("AI_1", Token.A, True)
minmax = Minmax_AlphaBeta_Tree(p1, depth)
game = ConnectFour(p1=p1)
minmax.compute(game)
minmax.to_json("minmax" + str(depth) + ".json")
def test_deepcopy(self):
name = "Player 1"
token = "X"
p = Player(name, token)
pp = p
cp = copy.deepcopy(p)
self.assertEqual(p.name, cp.name)
self.assertEqual(p.token, cp.token)
self.assertTrue(isinstance(cp, Player))
self.assertFalse(p is cp)
self.assertTrue(p is pp)
# Update attributes values so 'is' return False
p._name = "Human"
p._token = 'o'
self.assertFalse(p.name is cp.name)
self.assertFalse(p.token is cp.token)
def test_deepcopy(self):
depth = 4
p1 = Player("AI_1", Token.A, True)
ai = Minmax_AB_Parallel(p1, depth)
cai = copy.deepcopy(ai)
self.assertFalse(ai is cai)
self.assertFalse(ai._player is cai._player)
ai._depth = 5
self.assertFalse(ai._depth is cai._depth)
self.assertNotEqual(ai._depth, cai._depth)
def test_pos3(self):
'''
0 1 2 3 4 5 6
0|X|X|-|-|-|-|-|
1|X|O|-|-|-|-|-|
2|O|X|-|-|-|-|-|
3|X|O|-|-|-|-|-|
4|O|X|O|-|-|-|-|
5|X|O|O|-|-|-|-|
Player_1(X) to play
'''
p1 = Player("AI_1", Token.A, True)
p2 = Player("AI_2", Token.B, True)
game = ConnectFour(p1=p1, p2=p2)
moves = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 2, 1, 2]
for m in moves:
game.play(m)
depth = 2
ai = Minmax_AB_Parallel(p1, depth)
self.assertEqual(ai.compute(game), 3)
def test_is_leaf(self):
ai_player = Player("AI_1", Token.A, True)
game = TicTacToe(p1=ai_player)
minmax = Minmax(ai_player, 7)
self.assertFalse(minmax._is_leaf(game, 1))
self.assertTrue(minmax._is_leaf(game, 0))
game.play(Point(0, 0))
game.play(Point(0, 1))
game.play(Point(1, 0))
game.play(Point(1, 1))
game.play(Point(2, 0))
self.assertTrue(minmax._is_leaf(game, 1))
self.assertTrue(minmax._is_leaf(game, 0))
def make_player(mode):
p1, p2 = None, None
if mode == 'H_H':
p1 = Player("Human_1", Token.A)
p2 = Player("Human_2", Token.B)
elif mode == 'AI_H':
p1 = Player("AI_1", Token.A, True)
p2 = Player("Human_2", Token.B)
elif mode == 'H_AI':
p1 = Player("Human_1", Token.A)
p2 = Player("AI_2", Token.B, True)
elif mode == 'AI_AI':
p1 = Player("AI_1", Token.A, True)
p2 = Player("AI_2", Token.B, True)
else:
assert (False)
return p1, p2
def test_pos2(self):
'''
0 1 2 3 4 5 6
0|X|-|-|-|-|-|-|
1|O|-|O|-|-|-|-|
2|X|-|X|O|-|-|-|
3|O|O|O|X|X|-|-|
4|O|X|X|X|O|-|-|
5|O|X|O|X|X|-|-|
'''
p2 = Player("AI_2", Token.B, True)
game = ConnectFour(p2=p2)
moves = [
3, 0, 4, 2, 3, 0, 2, 0, 0, 4, 1, 2, 3, 3, 1, 1, 2, 0, 0, 2, 4, 0,
2, 4
]
for move in moves:
game.play(move)
# test p1 win position
import numpy as np
self.assertTrue(
np.array_equal(game._board.get_diag_up(4, 2),
[1, 1, 1, 1, None, None]))
self.assertTrue(game.is_over)
game.undo()
game.undo()
# test p1 win in (1,1)
self.assertEqual(game.current_player, p2)
game.play(1) # O
game.play(1) # X
self.assertTrue(game.is_over)
# p2 turn, should block (4,3)
game.undo()
game.undo()
self.assertEqual(game.current_player, p2)
depth = 2
minmax = Minmax_AB(p2, depth)
self.assertEqual(minmax.compute(game), 4)
def test_tictactoe(self):
from game.tictactoe import TicTacToe
n = 10
depth = 9
duration = 0
p1 = Player("AI_1", Token.A, True)
for i in range(n):
minmax = Minmax_AB_Parallel(p1, depth)
game = TicTacToe(p1=p1)
start = time.time()
minmax.compute(game)
duration += time.time() - start
print("Duration {}".format(duration / n))
r = expected['tictactoe']
delta = r * 3 / 100
self.assertAlmostEqual(duration / n, r, delta=delta)
def test_connect_four(self):
from game.connect_four import ConnectFour
n = 20
depth = 9
p1 = Player("AI_1", Token.A, True)
duration = 0
for i in range(n):
minmax = Minmax_AB_Parallel(p1, depth)
game = ConnectFour(p1=p1)
for m in [3, 4, 3, 4, 3, 4, 0]:
game.play(m)
start = time.time()
minmax.compute(game)
duration += time.time() - start
print("Duration {}".format(duration / n))
r = expected['connect_four']
delta = r * 3 / 100
self.assertAlmostEqual(duration / n, r, delta=delta)
def main():
pr = cProfile.Profile()
depth = 8
p1 = Player("AI_1", Token.A, True)
game = ConnectFour(p1=p1)
# minmax = Minmax_AB(p1, depth)
minmax = Minmax_AB_Parallel(p1, depth)
moves = [0, 1, 0, 1, 5, 6, 5, 6]
for m in moves:
game.play(m)
pr.enable()
minmax.compute(game)
pr.disable()
# Construct stats
ps = pstats.Stats(pr)
ps.strip_dirs()
# ps.sort_stats(SortKey.CUMULATIVE)
ps.sort_stats('tottime')
ps.print_stats()
def test_pos1(self):
'''
0 1 2 3 4 5 6
0|-|-|-|-|-|-|-|
1|-|-|-|-|-|-|-|
2|X|-|O|-|O|-|-|
3|O|-|X|X|X|-|-|
4|O|-|O|X|X|X|O|
5|O|-|O|X|X|X|O|
'''
p2 = Player("AI_2", Token.B, True)
game = ConnectFour(p2=p2)
moves = [3, 0, 4, 2, 5, 6, 4, 0, 3, 0, 0, 2, 2, 2, 5, 6, 4, 4, 3]
for move in moves:
game.play(move)
depth = 1
minmax = Minmax_AB(p2, depth)
self.assertEqual(minmax.compute(game), 0)
depth = 2
minmax = Minmax_AB(p2, depth)
self.assertEqual(minmax.compute(game), 0)
def test_name(self):
name = "Player 1"
token = "X"
player = Player(name, token)
self.assertEqual(player.name, name)
self.assertEqual(player.token, token)
def test_tictactoe(self):
ai_player = Player("AI_1", Token.A, True)
game = TicTacToe(p1=ai_player)
depth = 2
minmax = Minmax_AB_Parallel(ai_player, depth)
minmax.compute(game)
def test_connect_four(self):
ai_player = Player("AI_1", Token.A, True)
game = ConnectFour(p1=ai_player)
depth = 2
minmax = Minmax_AB_Parallel(ai_player, depth)
minmax.compute(game)
def test_gomoku(self):
ai_player = Player("AI_1", Token.A, True)
game = Gomoku(p1=ai_player)
depth = 2
minmax = Minmax_AB_Parallel(ai_player, depth)
minmax.compute(game)
