predictlist = []
outputlist = []
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(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[:-output_num-2]
output = row[-output_num-2]
inputlist = np.array([inputlist]).astype(np.float32)
y = model.predict(xp.asarray(inputlist))
outputlist.append(output)
predictlist.append(y.data[0,0])
for row in test:
inputlist = row[:-output_num-2]
output = row[-output_num-2]
inputlist = np.array([inputlist]).astype(np.float32)
y = model_3.predict(xp.asarray(inputlist))
if y.data.argmax() == output:
rec_3.append(1)
elif y.data.argmax() != output:
rec_3.append(0)
elif args.mode == 1:
print 'regression'
#model_1
train, test = md.getTeacherDataMultiTech(file,START_TEST_DAY,NEXT_DAY,args.input_num,stride=1,u_vol=True,u_ema=True)
for row in test:
inputlist = row[:-output_num-2]
output = row[-output_num-2]
inputlist = np.array([inputlist]).astype(np.float32)
y = model_1.predict(xp.asarray(inputlist))
rec_1.append((output - y.data[0,0])*(output - y.data[0,0]))
#model_2
train, test = md.getTeacherDataMultiTech(file,START_TEST_DAY,NEXT_DAY,args.input_num,stride=1,u_vol=True,u_rsi=True,u_stoch=True)
for row in test:
inputlist = row[:-output_num-2]
output = row[-output_num-2]
inputlist = np.array([inputlist]).astype(np.float32)