def test_player_move():
board = g.Board()
player = g.Player(board, 1)
board.set_state([1, 0, 1, 0, 2, 0, 0, 0, 0])
player.set_Q(1, 10)
player.epsilon = 0
assert player.move() == 1
def test_player_rewards():
board = g.Board()
player = g.Player(board, 1)
assert player.reward(3) == 0
board.set_state([1, 1, 1, 0, 0, 0, 0, 0, 0])
assert player.reward(3) == 100
board.set_state([2, 2, 2, 0, 0, 0, 0, 0, 0])
assert player.reward(3) == -100
def test_board_set_get():
board = g.Board()
board.set_state(np.array([1, 2, 0, 0, 0, 1, 2, 1, 2]).reshape((3, 3)))
assert np.array_equal(
board.get_state(),
np.array([1, 2, 0, 0, 0, 1, 2, 1, 2]).reshape((3, 3)))
empty = board.get_empty()
assert np.array_equal(empty, np.array([2, 3, 4]))
def test_board_available_states():
board = g.Board()
board.set_state([2, 1, 0, 1, 2, 1, 2, 0, 2])
assert np.array_equal(
board.available_states(1),
np.array([
np.array([2, 1, 1, 1, 2, 1, 2, 0, 2]).reshape(3, 3),
np.array([2, 1, 0, 1, 2, 1, 2, 1, 2]).reshape(3, 3)
]))
def test_player_move():
board = g.Board()
player = g.Player(board, 1)
player.epsilon = 1
board.set_state([2, 1, 2, 1, 2, 1, 2, 0, 2])
assert player.move() == 7
player = g.Player(board, 2)
player.epsilon = 1
board.set_state([2, 1, 2, 1, 2, 1, 2, 0, 2])
assert player.move() == 7
def test_player_bestmove():
board = g.Board()
player = g.Player(board, 1)
board.set_state([2, 1, 2, 1, 2, 1, 2, 0, 2])
player.set_Q(7, 10)
assert np.array_equal(player.eval_board(),
[0., 0., 0., 0., 0., 0., 0., 10., 0.])
board.set_state([0, 1, 2, 1, 2, 1, 2, 0, 2])
player.set_Q(0, 20)
player.set_Q(7, 10)
assert np.array_equal(player.eval_board(),
[20., 0., 0., 0., 0., 0., 0., 10., 0.])
def test_board_cond():
board = g.Board()
board.set_state(np.array([1, 1, 1, 0, 0, 0, 0, 0, 0]).reshape((3, 3)))
cond = board.get_condition()
assert cond == 1
board.set_state(np.array([2, 0, 0, 0, 2, 0, 0, 0, 2]).reshape((3, 3)))
cond = board.get_condition()
assert cond == 2
board.set_state(np.array([2, 1, 0, 1, 0, 1, 2, 0, 0]).reshape((3, 3)))
cond = board.get_condition()
assert cond == 4
board.set_state(np.array([1, 2, 1, 2, 2, 1, 1, 1, 2]).reshape((3, 3)))
cond = board.get_condition()
assert cond == 3
board.set_state(np.array([2, 2, 1, 2, 2, 1, 1, 1, 2]).reshape((3, 3)))
cond = board.get_condition()
assert cond == 2
def test_player_Q():
board = g.Board()
player = g.Player(board, 1)
player.set_Q(1, 56)
assert player.get_Q(1) == 56
def test_board_update():
board = g.Board()
board.update(4, 1)
assert board.get_state()[1, 1] == 1
def test_board_empty():
board = g.Board()
board.set_state(np.array([0, 0, 0, 0, 0, 0, 0, 0, 0]).reshape((3, 3)))
empty = board.get_empty()
assert np.array_equal(empty, np.arange(9))
import deeptactoe
from deeptactoe import game as g
from pprint import pprint as pp
import numpy as np
board = g.Board()
player1 = g.Player(board, 1)
player2 = g.Player(board, 2, beh='human')
player1.epsilon = 1
try:
player1.load_Q()
except:
print("Not possible to load Q matrix. Computer will play at random")
def sanitise(board, move):
if (np.any(np.equal(board.get_empty(), int(move)))):
return False
else:
print("Illegal move!")
return True
def resolution(board):
case = board.get_condition()
if (case == 1):
print("The Computer wins")
elif (case == 2):
print("Human wins")
else:
print("Tie")