def get_prediction_data(klines, n):
"""获取用于随机森林的n个输入数据(n为数据长度): n天中每天的特征参数及其涨跌情况"""
close_prices = klines.close[- 30 - n:] # 获取本交易日及以前的收盘价(此时在预定的收盘时间: 认为本交易日已收盘)
# 计算所需指标
sma_data = sma(close_prices, 30, 0.02)[-n:] # SMA指标, 函数默认时间周期参数:30
wma_data = ema2(close_prices, 30)[-n:] # WMA指标
mom_data = trma(close_prices, 30)[-n:] # MOM指标
x_all = list(zip(sma_data, wma_data, mom_data)) # 样本特征组
y_all = list(klines.close.iloc[i] >= klines.close.iloc[i - 1] for i in list(reversed(range(-1, -n - 1, -1)))) # 样本标签组
# x_all: 大前天指标 前天指标 昨天指标 (今天指标)
# y_all: (大前天) 前天 昨天 今天 -明天-
# 准备算法需要用到的数据
x_train = x_all[: -1] # 训练数据: 特征
x_predict = x_all[-1] # 预测数据(用本交易日的指标预测下一交易日的涨跌)
y_train = y_all[1:] # 训练数据: 标签 (去掉第一个数据后让其与指标隔一位对齐(例如: 昨天的特征 -> 对应预测今天的涨跌标签))
return x_train, y_train, x_predict
def ZJFZ_kdj(self, time_system='day'):
'''
ZJFZ
VAR2:=REF(LOW,1);
VAR3:=SMA(ABS(LOW-VAR2),3,1)/SMA(MAX(LOW-VAR2,0),3,1)*100;
VAR4:=EMA(VAR3*10,3);
VAR5:=LLV(LOW,13);
VAR6:=HHV(VAR4,13);
VAR7:=EMA(IF(LOW<=VAR5,(VAR4+VAR6*2)/2,0),3)/618;
VAR8:=IF(VAR7>500,500,VAR7);
STICKLINE(VAR8>-120,0,VAR8,3,1),COLORGRAY;
STICKLINE(VAR8>1 AND "KDJ.J">REF("KDJ.J",1) AND REF("KDJ.J",1)<REF("KDJ.J",2),0,VAR8,3,0),COLORRED;
STICKLINE(VAR8>0.1 AND VAR8<1 AND "KDJ.J">REF("KDJ.J",1) AND REF("KDJ.J",1)<REF("KDJ.J",2),0,VAR8,3,0),COLOR00FFFF;
'''
time1 = time.time()
ans = []
if time_system == 'day':
day = 240
elif time_system == 'week':
day = 1200
for code in tqdm.tqdm(self.stock):
count = 0
if code[0] == '3':
continue
data = self.getdata_day(code, 1200, 260)
if len(data) < 60:
continue
if data['close'][0] < 6:
continue
var2 = tafunc.ref(data['low'], 1)
var3 = tafunc.sma(
tafunc.abs(data['low'] - var2), 3, 1) / tafunc.sma(
tafunc.max(data['low'], var2), 3, 1) * 100
var4 = tafunc.ema(var3 * 10, 3)
var5 = tafunc.llv(data['low'], 13)
var6 = tafunc.hhv(var4, 13)
for i in range(len(data['low'])):
a = data['low'][i]
b = var5[i]
if not np.isnan(b) and a <= b:
var4[i] = (var4[i] + var6[i] * 2) / 2
else:
var4[i] = 0
var7 = tafunc.ema(var4, 3) / 618
kdj = ta.KDJ(data, 9, 3, 3)
j = kdj['j']
gold = tafunc.crossup(kdj['k'], kdj['d'])
j1 = tafunc.ref(j, 1)
for i in range(len(j)):
if np.isnan(j1[i]):
var7[i] = 0
continue
# if all((var7[i] > 0.01 , gold[i] > 0)) or all((var7[i] > 0.01 , j[i] > j1[i])):
if all((var7[i] > 0.01, gold[i] > 0)):
var7[i] = 1
else:
var7[i] = 0
if np.sum(var7[-4:]) > 0:
# print(code)
ans.append(code)
with open('ZJFZ_kdj.txt', "w") as f:
for c in ans:
f.write(c + '\n')
time2 = time.time()
print('ZJFZ_kdj' + '运行时间：', time2 - time1)
return ans