#株価データの読み込み
_time,_open,_max,_min,_close,_volume,_keisu,_shihon = md.readfile(filepath)
try:
iday = _time.index(START_TEST_DAY)
except:
print 'can not find START_TEST_DAY'
continue
#model_1
output_list = []
predict_list = []
train, test = md.getTeacherDataMultiTech_label(f,START_TEST_DAY,NEXT_DAY,input_num,stride=1,u_vol=True,u_ema=True)
if (train == -1) or (test == -1):
print 'skip',f
continue
for row in test:
inputlist = row[:-output_num-2]
output = row[-output_num-2]
output_list.append(output)
inputlist = np.array([inputlist]).astype(np.float32)
y = model_1.predict(xp.asarray(inputlist),1)
predict_list.append(y.data.argmax())
if y.data.argmax() == 0:#buy
point_1.append(1)
elif y.data.argmax() == 1:#sell
point_1.append(-1)
stocks = []
money = 1000000#所持金
filepath = "./stockdata/%s" % f
#株価データの読み込み
_time,_open,_max,_min,_close,_volume,_keisu,_shihon = md.readfile(filepath)
try:
iday = _time.index(START_TEST_DAY)
except:
print 'can not find START_TEST_DAY'
continue
train, test = md.getTeacherDataMultiTech_label(f,START_TEST_DAY,NEXT_DAY,input_num,stride=1,u_vol=u_vol,u_ema=u_ema,u_rsi=u_rsi,u_macd=u_macd,u_stoch=u_stoch,u_wil=u_wil)
if (train == -1) or (test == -1):
print 'skip',f
continue
for row in test:
inputlist = row[:-3]
output = row[-3]
inputlist = np.array([inputlist]).astype(np.float32)
y = model.predict(xp.asarray(inputlist),1)
if y.data.argmax() == 0:#buy
point.append(1)
elif y.data.argmax() == 1:#sell
point.append(-1)
elif y.data.argmax() == 2:#no_ope
point.append(0)
