if status == 1:
# print "Player 1 has won"
p1 += 1
elif status == -1:
# print "Player 2 has won"
p2 += 1
elif status == 0:
# print "Game was a draw"
pass
PLAYER *= -1
board_current = game.linear_board()
print board_current[0:3]
print board_current[3:6]
print board_current[6:9]
wins = p1
losses = p2
draws = n - (wins + losses)
return wins, losses, draws
if __name__ == '__main__':
f = open("player_genomes/best_genome.txt", 'rb').read()
data = f.split('\n')[:-1]
w1, w2, w3, nx, n1, n2, ny, fit = parse_genome(data)
nn_p = NeuralNet()
nn_p.load_from_genome(w1, w2, w3, nx, n1, n2, ny, fit)
print play_a_game(nn_p, 1)
'''
[X - X]
[X O -]
[O - O]'''
