def est_active(file_list, name):
est = np.zeros((days, 2))
ind = 0
for files in file_list:
for d in range(1, days):
y = estimate(aiwolfpy.read_log(files), d, name)
if y >= 0:
est[d, 0] += y
est[d, 1] += 1
n_est = int(est[1, 1])
if n_est % 100 == 0:
print('est_{}files = {:.2f}[sec]'.format(n_est,
time.time() - start1))
return est
def data_active(file_list, expan):
x, y = xy_init(expan, file_list)
ind = 0
for files in file_list:
gamedf = aiwolfpy.read_log(files)
for i in range(expan):
df = gamedf_expansion(gamedf)
for d in range(1, days):
dx, dy = get_data(df, d)
x[(ind * 60):((ind + 1) * 60), :] = dx
y[(ind * 60):((ind + 1) * 60)] = dy
ind += 1
n_data = int(ind / (days - 1))
if n_data % 100 == 0:
print('get_{}data = {:.2f}[sec]'.format(
n_data,
time.time() - start1))
return x, y
count = 0
model = sklearn.linear_model.LogisticRegression()
wf = open("/home/AIWolfPy/train/train-log2.txt", mode="a")
for k in range(21, 1000):
x_1000 = np.zeros((5460000, 60))
y_1000 = np.zeros(5460000)
ind = 0
for i in range(100):
log_path = "/home/AIWolfPy/pre_logs/gat2017_15/" + "{0:03d}".format(
k) + "/" + "{0:03d}".format(i) + ".log"
for d in range(5):
try:
text_ = aiwolfpy.read_log(log_path)
except:
continue
x, y = game_data_filter(text_, day=d, phase='vote')
x_1000[(ind * 5460):((ind + 1) * 5460), :] = x
y_1000[(ind * 5460):((ind + 1) * 5460)] = y
ind += 1
x, y = game_data_filter(text_, day=d + 1, phase='daily_initialize')
x_1000[(ind * 5460):((ind + 1) * 5460), :] = x
y_1000[(ind * 5460):((ind + 1) * 5460)] = y
ind += 1
model.fit(x_1000, y_1000)
text = "epoch :" + str(count) + " score :" + str(
model.score(x_1000, y_1000))
print(text)
wf = open("/home/AIWolfPy/train/train-log.txt", mode="a")
train_num = len(train_file)
test_num = len(test_file)
days = 3
expan = 30
x_data = np.zeros((60 * days * train_num * expan, predictor.n_para))
y_data = np.zeros(60 * days * train_num * expan)
start1 = time.time()
ind = 0
for files in train_file:
for i in range(expan):
a = random.randint(0, 119)
for d in range(days):
x, y = game_data_filter(aiwolfpy.read_log(files), day=d, pat=a)
x_data[(ind * 60):((ind + 1) * 60), :] = x
y_data[(ind * 60):((ind + 1) * 60)] = y
ind += 1
if (ind / days) % 100 == 0:
print('get_{}data = {}[sec]'.format(int(ind / days),
time.time() - start1))
print("get_train_data = {}[sec]".format(time.time() - start))
train_file = file_list[:500]
test_file = file_list[500:1000]
train_num = len(train_file)
test_num = len(test_file)
times = 10
break
"""
# build data for 100 games
# takes several minutes
x_1000 = np.zeros((5460000, 60))
y_1000 = np.zeros(5460000)
ind = 0
filecount = 0
for i in range(999999):
#log_path = "../log/sample13/AIWolf20191002" + "{0:03d}".format(def_file_no+i) + ".log"
log_path = "../../Server/AIWolf-ver0.5.6/log/sample21/AIWolf20191002" + "{0:03d}".format(
i) + ".log"
for d in range(5):
try:
x, y = game_data_filter(aiwolfpy.read_log(log_path),
day=d,
phase='vote')
x_1000[(ind * 5460):((ind + 1) * 5460), :] = x
y_1000[(ind * 5460):((ind + 1) * 5460)] = y
ind += 1
x, y = game_data_filter(aiwolfpy.read_log(log_path),
day=d + 1,
phase='daily_initialize')
x_1000[(ind * 5460):((ind + 1) * 5460), :] = x
y_1000[(ind * 5460):((ind + 1) * 5460)] = y
ind += 1
if d == 0:
filecount += 1
except FileNotFoundError:
break
