def test_evaluate_empty_board(self):
'''Evaluate empty board.
set fields of board:
[ ][ ][ ]
[ ][ ][ ]
[ ][ ][ ]
'''
self.assertEqual(
evaluate(self.board, player=Field.CIRCLE, opponent=Field.CROSS), 0)
self.assertEqual(
evaluate(self.board, player=Field.CROSS, opponent=Field.CIRCLE), 0)
def test_evaluate_not_win_and_not_draw(self):
'''Evaluate not win game and not draw game - continue game.
set fields of board:
[X][ ][ ]
[ ][O][ ]
[ ][ ][ ]
'''
self.board[0] = Field.CROSS
self.board[4] = Field.CIRCLE
self.assertEqual(
evaluate(self.board, player=Field.CIRCLE, opponent=Field.CROSS), 0)
self.assertEqual(
evaluate(self.board, player=Field.CROSS, opponent=Field.CIRCLE), 0)
def test_evaluate_win_in_second_row(self):
'''Win player in second row.
set fields of board:
[O][O][X]
[X][X][X]
[ ][O][ ]
'''
self.board[0] = Field.CIRCLE
self.board[1] = Field.CIRCLE
self.board[2] = Field.CROSS
self.board[3] = Field.CROSS
self.board[4] = Field.CROSS
self.board[5] = Field.CROSS
self.board[7] = Field.CIRCLE
self.assertEqual(
evaluate(self.board, player=Field.CROSS, opponent=Field.CIRCLE),
10)
self.assertEqual(
evaluate(self.board, player=Field.CIRCLE, opponent=Field.CROSS),
-10)
def test_evaluate_win_in_third_column(self):
'''Win player in third column.
set fields of board:
[X][O][X]
[O][O][X]
[ ][ ][X]
'''
self.board[0] = Field.CIRCLE
self.board[1] = Field.CROSS
self.board[2] = Field.CROSS
self.board[3] = Field.CIRCLE
self.board[4] = Field.CIRCLE
self.board[5] = Field.CROSS
self.board[8] = Field.CROSS
self.assertEqual(
evaluate(self.board, player=Field.CROSS, opponent=Field.CIRCLE),
10)
self.assertEqual(
evaluate(self.board, player=Field.CIRCLE, opponent=Field.CROSS),
-10)
def test_evaluate_draw_game(self):
'''Evauate draw game.
set fields of board:
[X][O][X]
[O][X][X]
[O][X][O]
'''
self.board[0] = Field.CROSS
self.board[1] = Field.CIRCLE
self.board[2] = Field.CROSS
self.board[3] = Field.CIRCLE
self.board[4] = Field.CROSS
self.board[5] = Field.CROSS
self.board[6] = Field.CIRCLE
self.board[7] = Field.CROSS
self.board[8] = Field.CIRCLE
self.assertEqual(
evaluate(self.board, player=Field.CIRCLE, opponent=Field.CROSS), 0)
self.assertEqual(
evaluate(self.board, player=Field.CROSS, opponent=Field.CIRCLE), 0)
def ai_route(moves):
if moves == 'o':
brd = board.Board('5')
elif moves == 'x':
brd = board.Board('')
else:
player = board.Board(moves)
if player.who_won() != None:
brd = player
else:
res = ai.evaluate(player)
brd = player.make_move(res[2])
return render(brd)
def ai_route(moves):
if moves == 'o':
brd = board.Board('5')
elif moves == 'x':
brd = board.Board('')
else:
player = board.Board(moves)
if player.who_won()!=None:
brd = player
else:
res = ai.evaluate(player)
brd = player.make_move(res[2])
return render(brd)
def ai_eval(chromo):
return ai.evaluate(chromo, NETWORK_ARCH)
def main():
global NETWORK_ARCH
global NUM_VALS
parser = ArgumentParser('Genetic')
parser.add_argument('--pop', type=int, default=50, help='Population size')
parser.add_argument(
'--keep',
type=int,
default=10,
help='Number of chromosomes to keep between generations')
parser.add_argument('--probm',
type=float,
default=0.5,
help='Probability to mutate a chromosome')
parser.add_argument('--probg',
type=float,
default=0.1,
help='Probability to mutate a gene')
parser.add_argument('--kpoint', type=int, default=2, help='k-point')
parser.add_argument('--no-print',
action='store_true',
help='Prevent printing durring evaluation')
parser.add_argument('--time',
action='store_true',
help='Time each function')
parser.add_argument('--epoch',
type=int,
default=10,
help='Generations per epoch')
parser.add_argument('--max-gen',
type=int,
default=200,
help='Maximum number of generations')
parser.add_argument('--view',
action='store_true',
help='View the best chromosome of the population')
parser.add_argument("--arch",
default=[],
type=int,
nargs='*',
help="Neural network architecture")
args = parser.parse_args()
NETWORK_ARCH = list(args.arch)
NUM_VALS = 0
for i in range(1, len(NETWORK_ARCH)):
NUM_VALS += ((NETWORK_ARCH[i - 1] + 1) * NETWORK_ARCH[i])
if NETWORK_ARCH:
NUM_VALS += (13 * NETWORK_ARCH[0])
NUM_VALS += ((NETWORK_ARCH[-1] + 1) * 4)
else:
NUM_VALS = 52
n_pop = args.pop
n_keep = args.keep
prob_m = args.probm
gene_m = args.probg
k = args.kpoint
times = [0, [], [], [], [], [], []]
times[0], pop = time_exec(args.time, initialize, n_pop)
gen = 0
fitnesses = []
for gen in range(args.max_gen):
tmp, fitness = time_exec(args.time, evaluate, pop)
times[1].append(tmp)
fitnesses.append(max(fitness))
if gen % args.epoch == 0:
if not args.no_print:
if args.view:
print("{} GEN: {:5} FIT: {}".format(
"\n" * 30, gen, max(fitness)))
pop, fitness = sort_by_fitness(pop, fitness)
ai.evaluate(pop[0],
NETWORK_ARCH,
display=True,
sleep=0.05,
avg=1)
else:
print("GEN: {:5} FIT: {}".format(gen, max(fitness)))
pop_copy = [np.copy(chrom) for chrom in pop]
tmp, new_pop = time_exec(args.time, selection, pop_copy, fitness,
n_keep)
times[2].append(tmp)
tmp, new_pop = time_exec(args.time, crossover, new_pop, k)
times[3].append(tmp)
tmp, new_pop = time_exec(args.time, mutate, new_pop, prob_m, gene_m)
times[4].append(tmp)
tmp, pop = time_exec(args.time, replace, pop, fitness, new_pop, n_keep)
times[5].append(tmp)
print("FITNESS: {}".format(max(fitness)))
if (args.time):
print("INIT: {:f}s".format(times[0]))
print("EVAL: {:f}s".format(sum(times[1]) / gen))
print("SELE: {:f}s".format(sum(times[2]) / gen))
print("CROS: {:f}s".format(sum(times[3]) / gen))
print("MUTA: {:f}s".format(sum(times[4]) / gen))
print("REPL: {:f}s".format(sum(times[5]) / gen))
plot.plot_fitness(
"{}-{}-{}-{}-{}-{}.png".format(
'.'.join(['12'] + [str(x) for x in NETWORK_ARCH] + ['4']), n_pop,
args.max_gen, k, prob_m, gene_m), fitnesses)
return 1
elif move == 'd':
return 2
elif move == 'a':
return 3
elif move == 'q':
return -1
elif move == 'r':
print(snake.snake_ray(position, N))
if __name__ == "__main__":
# print("\033[2J\033[H", end='', flush=True)
parser = ArgumentParser()
parser.add_argument("N",
nargs='?',
type=int,
default=20,
help="Size of snake grid")
# parser.add_argument(
# "--K", nargs='?', type=int, default=5, help="Size of snake grid")
args = parser.parse_args()
print(ai.evaluate(np.random.rand(100).tolist(), args.N, False))
# snake.snake(args.N, depthai.depth_ai(args.K), True)
# snake.snake(args.N, user_input, True)
# snake.snake(args.N, user.input_time, True)
# snake.snake(args.N, dumbai.dumb_ai, True)
# snake.snake(args.N, perfectai.perfect_ai, True)