def MA(security_list, timeperiod=5):
# ????????????
if isinstance(security_list, str):
security_list = [security_list]
# ?? MA
security_data = history(timeperiod * 2, '1d', 'close',
security_list, df=False, skip_paused=True)
ma = {}
for stock in security_list:
ma[stock] = talib.MA(security_data[stock], timeperiod)
return ma
# SMA
python类MA的实例源码
def MA_MONEY(security_list, timeperiod=5):
# ????????????
if isinstance(security_list, str):
security_list = [security_list]
# ?? N ??????
security_data = history(timeperiod * 2, '1d', 'money',
security_list, df=False, skip_paused=True)
mamoney = {}
for stock in security_list:
x = security_data[stock]
mamoney[stock] = talib.MA(security_data[stock], timeperiod)
return mamoney
# ?????
def MA_VOLUME(security_list, timeperiod=5):
# ????????????
if isinstance(security_list, str):
security_list = [security_list]
# ?? N ??????
security_data = history(timeperiod * 2, '1d', 'volume',
security_list, df=False, skip_paused=True)
mavol = {}
for stock in security_list:
x = security_data[stock]
mavol[stock] = talib.MA(security_data[stock], timeperiod)
return mavol
# BIAS
def ma(close, p = 30):
return talib.MA(close, p)
def calculate_indicator(stock_df):
periods = [3, 5, 10, 20, 30, 60]
# MA
for period in periods:
stock_df['MA' + str(period)] = talib.MA(stock_df['close'].values, timeperiod=period)
# EMA
periods = [3, 5, 10, 20, 30, 60]
for period in periods:
stock_df['EMA' + str(period)] = talib.EMA(stock_df['close'].values, timeperiod=period)
# AMTMA
periods = [5, 10, 20]
for period in periods:
stock_df['AMTMA' + str(period)] = talib.MA(stock_df['amount'].values, timeperiod=period)
# ATR
periods = [5, 10, 20]
for period in periods:
stock_df['ATR' + str(period)] = talib.ATR(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# ADX
period = 14
stock_df['ADX' + str(period)] = talib.ADX(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# MACD
stock_df['MACD_DIFF'], stock_df['MACD_DEA'], stock_df['MACD_HIST'] = talib.MACD(
stock_df['close'].values, fastperiod=12, slowperiod=26, signalperiod=9)
# CCI
period = 14
stock_df['CCI' + str(period)] = talib.CCI(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# MFI
period = 14
stock_df['MFI' + str(period)] = talib.MFI(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, stock_df['volume'].values,
timeperiod=period)
# ROCP
periods = [5, 10, 20]
for period in periods:
stock_df['ROCP' + str(period)] = talib.ROCP(stock_df['close'].values, timeperiod=period)
def calculate_indicator(stock_df):
periods = [3, 5, 10, 20, 30, 60]
# MA
for period in periods:
stock_df['MA' + str(period)] = talib.MA(stock_df['close'].values, timeperiod=period)
# EMA
periods = [3, 5, 10, 20, 30, 60]
for period in periods:
stock_df['EMA' + str(period)] = talib.EMA(stock_df['close'].values, timeperiod=period)
# AMTMA
periods = [5, 10, 20]
for period in periods:
stock_df['AMTMA' + str(period)] = talib.MA(stock_df['amount'].values, timeperiod=period)
# ATR
periods = [5, 10, 20]
for period in periods:
stock_df['ATR' + str(period)] = talib.ATR(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# ADX
period = 14
stock_df['ADX' + str(period)] = talib.ADX(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# MACD
stock_df['MACD_DIFF'], stock_df['MACD_DEA'], stock_df['MACD_HIST'] = talib.MACD(
stock_df['close'].values, fastperiod=12, slowperiod=26, signalperiod=9)
# CCI
period = 14
stock_df['CCI' + str(period)] = talib.CCI(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, timeperiod=period)
# MFI
period = 14
stock_df['MFI' + str(period)] = talib.MFI(stock_df['high'].values, stock_df['low'].values,
stock_df['close'].values, stock_df['volume'].values,
timeperiod=period)
# ROCP
periods = [5, 10, 20]
for period in periods:
stock_df['ROCP' + str(period)] = talib.ROCP(stock_df['close'].values, timeperiod=period)
def get_kdj(sorted_data):
close,high,low,ma5,ma10,ma20 = get_case_data(sorted_data)
slowk, slowd = ta.STOCH(high,low,close, fastk_period=9, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)
slowkMA5 = ta.MA(slowk, timeperiod=5, matype=0)
slowkMA10 = ta.MA(slowk, timeperiod=10, matype=0)
slowkMA20 = ta.MA(slowk, timeperiod=20, matype=0)
slowdMA5 = ta.MA(slowd, timeperiod=5, matype=0)
slowdMA10 = ta.MA(slowd, timeperiod=10, matype=0)
slowdMA20 = ta.MA(slowd, timeperiod=20, matype=0)
operator = ''
#1.K???????——???90?????????10??????D??80???????????D??20???????????
if slowk[-1] >= 90:
operator += 'S9'
elif slowk[-1] <= 10:
operator += 'B1'
elif slowd[-1] >=80:
operator += 'S8'
elif slowd[-1] <= 20:
operator += 'B2'
#2.??????K???D??K?????D????????
if slowk[-1] > slowd[-1] and slowk[-2] <= slowd[-2]:
operator += 'BX'
elif slowk[-1] < slowd[-1] and slowk[-2] >= slowd[-2]:
operator += 'SX'
#3.???????????????????????
if ma5[-1] >= ma10[-1] and ma10[-1] >= ma20[-1]: #k???
if (slowkMA5[-1] <= slowkMA10[-1] and slowkMA10[-1] <= slowkMA20[-1]) or (slowdMA5[-1] <= slowdMA10[-1] and slowdMA10[-1] <= slowdMA20[-1]):
operator += 'S><'
elif ma5[-1] <= ma10[-1] and ma10[-1] <= ma20[-1]: #k???
if (slowkMA5[-1] >= slowkMA10[-1] and slowkMA10[-1] >= slowkMA20[-1]) or (slowdMA5[-1] >= slowdMA10[-1] and slowdMA10[-1] >= slowdMA20[-1]):
operator += 'B><'
return operator
def _get_ma_data(self, ori_data, periods):
ret_data = {}
float_data = [float(x) for x in ori_data]
for period in periods:
data = talib.MA(numpy.array(float_data), timeperiod = period)
data_list = data.tolist()
data_list = self._filter_data(data_list)
ret_data["%d" % period] = data_list
return ret_data
update_stock_daily_average_info.py 文件源码
项目：scheduler_frame
作者: f304646673
项目源码
文件源码
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def _get_ma_data(self, ori_data, periods):
ret_data = {}
float_data = [float(x) for x in ori_data]
for period in periods:
data = talib.MA(numpy.array(float_data), timeperiod = period)
data_list = data.tolist()
data_list = self._filter_data(data_list)
ret_data["%d" % period] = data_list
return ret_data
def overlap_process(event):
print(event.widget.get())
overlap = event.widget.get()
upperband, middleband, lowerband = ta.BBANDS(close, timeperiod=5, nbdevup=2, nbdevdn=2, matype=0)
fig, axes = plt.subplots(2, 1, sharex=True)
ax1, ax2 = axes[0], axes[1]
axes[0].plot(close, 'rd-', markersize=3)
axes[0].plot(upperband, 'y-')
axes[0].plot(middleband, 'b-')
axes[0].plot(lowerband, 'y-')
axes[0].set_title(overlap, fontproperties="SimHei")
if overlap == u'???':
pass
elif overlap == u'????????':
real = ta.DEMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'??????? ':
real = ta.EMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'??????——?????':
real = ta.HT_TRENDLINE(close)
axes[1].plot(real, 'r-')
elif overlap == u'???????????':
real = ta.KAMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'?????':
real = ta.MA(close, timeperiod=30, matype=0)
axes[1].plot(real, 'r-')
elif overlap == u'MESA???????':
mama, fama = ta.MAMA(close, fastlimit=0, slowlimit=0)
axes[1].plot(mama, 'r-')
axes[1].plot(fama, 'g-')
elif overlap == u'????????':
real = ta.MAVP(close, periods, minperiod=2, maxperiod=30, matype=0)
axes[1].plot(real, 'r-')
elif overlap == u'???????':
real = ta.SMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'????????(T3)':
real = ta.T3(close, timeperiod=5, vfactor=0)
axes[1].plot(real, 'r-')
elif overlap == u'????????':
real = ta.TEMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'?????? ':
real = ta.TRIMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
elif overlap == u'???????':
real = ta.WMA(close, timeperiod=30)
axes[1].plot(real, 'r-')
plt.show()
# ????
def onFiveBar(self, bar):
"""??5??K?"""
# ?????????????????????????
for orderID in self.orderList:
self.cancelOrder(orderID)
self.orderList = []
# ??K???
self.closeArray[0:self.bufferSize-1] = self.closeArray[1:self.bufferSize]
self.highArray[0:self.bufferSize-1] = self.highArray[1:self.bufferSize]
self.lowArray[0:self.bufferSize-1] = self.lowArray[1:self.bufferSize]
self.closeArray[-1] = bar.close
self.highArray[-1] = bar.high
self.lowArray[-1] = bar.low
self.bufferCount += 1
if self.bufferCount < self.bufferSize:
return
# ??????
self.atrValue = talib.ATR(self.highArray,
self.lowArray,
self.closeArray,
self.kkLength)[-1]
self.kkMid = talib.MA(self.closeArray, self.kkLength)[-1]
self.kkUp = self.kkMid + self.atrValue * self.kkDev
self.kkDown = self.kkMid - self.atrValue * self.kkDev
# ?????????
# ????????OCO????
if self.pos == 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = bar.low
self.sendOcoOrder(self.kkUp, self.kkDown, self.fixedSize)
# ??????
elif self.pos > 0:
self.intraTradeHigh = max(self.intraTradeHigh, bar.high)
self.intraTradeLow = bar.low
orderID = self.sell(self.intraTradeHigh*(1-self.trailingPrcnt/100),
abs(self.pos), True)
self.orderList.append(orderID)
# ??????
elif self.pos < 0:
self.intraTradeHigh = bar.high
self.intraTradeLow = min(self.intraTradeLow, bar.low)
orderID = self.cover(self.intraTradeLow*(1+self.trailingPrcnt/100),
abs(self.pos), True)
self.orderList.append(orderID)
# ????????
self.putEvent()
#----------------------------------------------------------------------
def pre_data(self,stick_code, ktype='D', beginday='',endday=''):
# ktype in ('D','W','M')
# today='2010-01-01'
if '' == beginday:
begindaytmp = datetime.date.today() - datetime.timedelta(days=13)
beginday = begindaytmp.strftime('%Y-%m-%d')
if '' == endday:
endday = datetime.date.today().strftime('%Y-%m-%d')
df =''
print(beginday,endday)
try:
if ktype == 'D':
df = self.get_data(
"select * from t_stick_data_d \
where code = '" + stick_code + "' and date > '"+beginday+"' \
and date <='" + endday + "' order by date asc;") # and date>'2015-05-01'
elif ktype == 'W':
df = self.get_data(
"select * from t_stick_data_w \
where code = '" + stick_code + "' and date > '"+beginday+"' \
and date <='" + endday + "' order by date asc;") # and date>'2015-05-01'
elif ktype == 'M':
df = self.get_data(
"select * from t_stick_data_m \
where code = '" + stick_code + "' and date > '"+beginday+"' \
and date <='" + endday + "' order by date asc;") # and date>'2015-05-01'
except Exception as e:
# print('ERR:',e)
return
df['cci'] = ta.CCI(df['high'].values.astype('double'), df['low'].values.astype('double'),
df['close'].values.astype('double'))
df['diff'], df['dea'], df['macd'] = ta.MACD(df['close'].values.astype('double'), fastperiod=12, slowperiod=26,
signalperiod=9)
df['obv'] = ta.OBV(df['close'].values.astype('double'), df['vol'].values.astype('double'))
df['volma5'] = ta.MA(df['vol'].values.astype('double'), 5);
df['volma20'] = ta.MA(df['vol'].values.astype('double'), 20);
df['MA20'] = ta.MA(df['close'].values.astype('double'), 20)
df['MA60'] = ta.MA(df['close'].values.astype('double'), 60)
df['cwbili'] = 0
df['pricebili'] = 0
return df
# xx=m_db2();
# df=xx.pre_data('000157',ktype='W')
# print(df)
# xx.insert_data('t_stick_data_m_test',df.head(20).as_matrix())
# xx.commit()
def add_MACDEXT(self, fastperiod=12, fastmatype=0,
slowperiod=26, slowmatype=0,
signalperiod=9, signalmatype=0,
types=['line', 'line', 'histogram'],
colors=['primary', 'tertiary', 'fill'],
**kwargs):
"""Moving Average Convergence Divergence with Controllable MA Type.
Note that the first argument of types and colors refers to MACD,
the second argument refers to MACD signal line and the third argument
refers to MACD histogram.
"""
if not self.has_close:
raise Exception()
utils.kwargs_check(kwargs, VALID_TA_KWARGS)
if 'kind' in kwargs:
kwargs['type'] = kwargs['kind']
if 'kinds' in kwargs:
types = kwargs['type']
if 'type' in kwargs:
types = [kwargs['type']] * 3
if 'color' in kwargs:
colors = [kwargs['color']] * 3
name = 'MACDEXT({},{},{})'.format(str(fastperiod),
str(slowperiod),
str(signalperiod))
macd = name
smacd = name + '[Sign]'
hmacd = name + '[Hist]'
self.sec[macd] = dict(type=types[0], color=colors[0])
self.sec[smacd] = dict(type=types[1], color=colors[1], on=macd)
self.sec[hmacd] = dict(type=types[2], color=colors[2], on=macd)
(self.ind[macd],
self.ind[smacd],
self.ind[hmacd]) = talib.MACDEXT(self.df[self.cl].values,
fastperiod, fastmatype,
slowperiod, slowmatype,
signalperiod, signalmatype)
def add_STOCHRSI(self, timeperiod=14,
fastk_period=5, fastd_period=3, fastd_matype=0,
types=['line', 'line'],
colors=['primary', 'tertiary'],
**kwargs):
"""Stochastic Relative Strength Index.
Note that the first argument of types and colors refers to StochRSI %K
while second argument refers to StochRSI %D
(signal line of %K obtained by MA).
"""
if not self.has_close:
raise Exception()
utils.kwargs_check(kwargs, VALID_TA_KWARGS)
if 'kind' in kwargs:
kwargs['type'] = kwargs['kind']
if 'kinds' in kwargs:
types = kwargs['type']
if 'type' in kwargs:
types = [kwargs['type']] * 2
if 'color' in kwargs:
colors = [kwargs['color']] * 2
name = 'STOCHRSI({},{},{})'.format(str(timeperiod),
str(fastk_period),
str(fastd_period))
fastk = name + r'[%k]'
fastd = name + r'[%d]'
self.sec[fastk] = dict(type=types[0], color=colors[0])
self.sec[fastd] = dict(type=types[1], color=colors[1], on=fastk)
self.ind[fastk], self.ind[fastd] = talib.STOCHRSI(self.df[self.cl].values,
timeperiod,
fastk_period,
fastd_period,
fastd_matype)
def get_macd(sorted_data):
close,high,low,ma5,ma10,ma20 = get_case_data(sorted_data)
macd, macdsignal, macdhist = ta.MACD(close, fastperiod=10, slowperiod=22, signalperiod=9)
# macd, macdsignal, macdhist = ta.MACD(close, fastperiod=12, slowperiod=26, signalperiod=9)
SignalMA5 = ta.MA(macdsignal, timeperiod=5, matype=0)
SignalMA10 = ta.MA(macdsignal, timeperiod=10, matype=0)
SignalMA20 = ta.MA(macdsignal, timeperiod=20, matype=0)
#2??? 1.DIFF?DEA????DIFF????DEA?????? 2.DIFF?DEA????DIFF????DEA??????
operator = ''
if macd[-1] > 0 and macdsignal[-1] > 0:
if macd[-1] > macdsignal[-1] and macd[-2] <= macdsignal[-2]:
operator += 'BX' #??
elif macd[-1] < 0 and macdsignal[-1] < 0:
if macd[-1] <= macdsignal[-2]:
operator += 'SX'
#DEA??k????????????
if ma5[-1] >= ma10[-1] and ma10[-1] >= ma20[-1]: #k???
if SignalMA5[-1] <= SignalMA10[-1] and SignalMA10[-1] <= SignalMA20[-1]: #DEA??
operator += 'S><'
if ma5[-1] <= ma10[-1] and ma10[-1] <= ma20[-1]: #k???
if SignalMA5[-1] >= SignalMA10[-1] and SignalMA10[-1] >= SignalMA20[-1]: #DEA??
operator += 'B><'
if macd[-1] > 0 and macdhist[-1] >0:
if macd[-1] > macd[-2] and macdhist[-1] > macdhist[-2]:
operator += 'B^'
elif macd[-1] < 0 and macdhist[-1] < 0:
if macd[-1] < macd[-2] and macdhist[-1] > macdhist[-2]:
operator += 'S^'
#??MACD??????????????
if macdhist[-1] > 0:
for i in range(1,7):
if macdhist[-2] <= 0:
operator += 'Bh'
break
if macdhist[-1] < 0:
for i in range(1,7):
if macdhist[-2] >= 0:
operator += 'Sh'
break
return (operator)
#??KDJ?????????
def Get_MACD(df):
#??12,26,9
macd, macdsignal, macdhist = ta.MACD(np.array(df['close']), fastperiod=12, slowperiod=26, signalperiod=9)
SignalMA5 = ta.MA(macdsignal, timeperiod=5, matype=0)
SignalMA10 = ta.MA(macdsignal, timeperiod=10, matype=0)
SignalMA20 = ta.MA(macdsignal, timeperiod=20, matype=0)
#13-15 DIFF DEA DIFF-DEA
df['macd']=pd.Series(macd,index=df.index) #DIFF
df['macdsignal']=pd.Series(macdsignal,index=df.index)#DEA
df['macdhist']=pd.Series(macdhist,index=df.index)#DIFF-DEA
dflen = df.shape[0]
MAlen = len(SignalMA5)
operate = 0
#2??? 1.DIFF?DEA????DIFF????DEA?????? 2.DIFF?DEA????DIFF????DEA??????
#???
if df.iat[(dflen-1),13]>0:
if df.iat[(dflen-1),14]>0:
if df.iat[(dflen-1),13]>df.iat[(dflen-1),14] and df.iat[(dflen-2),13]<=df.iat[(dflen-2),14]:
operate = operate + 10#??
else:
if df.iat[(dflen-1),14]<0:
if df.iat[(dflen-1),13]<=df.iat[(dflen-2),14]:
operate = operate - 10#??
#3.DEA??K?????????????
if df.iat[(dflen-1),7]>=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]>=df.iat[(dflen-1),9]:#K???
if SignalMA5[MAlen-1]<=SignalMA10[MAlen-1] and SignalMA10[MAlen-1]<=SignalMA20[MAlen-1]: #DEA??
operate = operate - 1
elif df.iat[(dflen-1),7]<=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]<=df.iat[(dflen-1),9]:#K???
if SignalMA5[MAlen-1]>=SignalMA10[MAlen-1] and SignalMA10[MAlen-1]>=SignalMA20[MAlen-1]: #DEA??
operate = operate + 1
#4.??MACD??????????????
if df.iat[(dflen-1),15]>0 and dflen >30 :
for i in range(1,26):
if df.iat[(dflen-1-i),15]<=0:#
operate = operate + 5
break
#?????????
if df.iat[(dflen-1),15]<0 and dflen >30 :
for i in range(1,26):
if df.iat[(dflen-1-i),15]>=0:#
operate = operate - 5
break
return (df,operate)
#??KDJ??????
def Get_KDJ(df):
#??9,3,3
slowk, slowd = ta.STOCH(np.array(df['high']), np.array(df['low']), np.array(df['close']), fastk_period=9, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)
slowkMA5 = ta.MA(slowk, timeperiod=5, matype=0)
slowkMA10 = ta.MA(slowk, timeperiod=10, matype=0)
slowkMA20 = ta.MA(slowk, timeperiod=20, matype=0)
slowdMA5 = ta.MA(slowd, timeperiod=5, matype=0)
slowdMA10 = ta.MA(slowd, timeperiod=10, matype=0)
slowdMA20 = ta.MA(slowd, timeperiod=20, matype=0)
#16-17 K,D
df['slowk']=pd.Series(slowk,index=df.index) #K
df['slowd']=pd.Series(slowd,index=df.index)#D
dflen = df.shape[0]
MAlen = len(slowkMA5)
operate = 0
#1.K???????——???90?????????10??????D??80???????????D??20???????????
if df.iat[(dflen-1),16]>=90:
operate = operate + 3
elif df.iat[(dflen-1),16]<=10:
operate = operate - 3
if df.iat[(dflen-1),17]>=80:
operate = operate + 3
elif df.iat[(dflen-1),17]<=20:
operate = operate - 3
#2.??????K???D??K?????D?????????#???
if df.iat[(dflen-1),16]> df.iat[(dflen-1),17] and df.iat[(dflen-2),16]<=df.iat[(dflen-2),17]:
operate = operate + 10
#??????K??D?K?????D?????????#???
elif df.iat[(dflen-1),16]< df.iat[(dflen-1),17] and df.iat[(dflen-2),16]>=df.iat[(dflen-2),17]:
operate = operate - 10
#3.???????????????????????
if df.iat[(dflen-1),7]>=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]>=df.iat[(dflen-1),9]:#K???
if (slowkMA5[MAlen-1]<=slowkMA10[MAlen-1] and slowkMA10[MAlen-1]<=slowkMA20[MAlen-1]) or \
(slowdMA5[MAlen-1]<=slowdMA10[MAlen-1] and slowdMA10[MAlen-1]<=slowdMA20[MAlen-1]): #K,D??
operate = operate - 1
elif df.iat[(dflen-1),7]<=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]<=df.iat[(dflen-1),9]:#K???
if (slowkMA5[MAlen-1]>=slowkMA10[MAlen-1] and slowkMA10[MAlen-1]>=slowkMA20[MAlen-1]) or \
(slowdMA5[MAlen-1]>=slowdMA10[MAlen-1] and slowdMA10[MAlen-1]>=slowdMA20[MAlen-1]): #K,D??
operate = operate + 1
return (df,operate)
#??RSI??????
def Get_RSI(df):
#??14,5
slowreal = ta.RSI(np.array(df['close']), timeperiod=14)
fastreal = ta.RSI(np.array(df['close']), timeperiod=5)
slowrealMA5 = ta.MA(slowreal, timeperiod=5, matype=0)
slowrealMA10 = ta.MA(slowreal, timeperiod=10, matype=0)
slowrealMA20 = ta.MA(slowreal, timeperiod=20, matype=0)
fastrealMA5 = ta.MA(fastreal, timeperiod=5, matype=0)
fastrealMA10 = ta.MA(fastreal, timeperiod=10, matype=0)
fastrealMA20 = ta.MA(fastreal, timeperiod=20, matype=0)
#18-19 ??real???real
df['slowreal']=pd.Series(slowreal,index=df.index) #??real 18
df['fastreal']=pd.Series(fastreal,index=df.index)#??real 19
dflen = df.shape[0]
MAlen = len(slowrealMA5)
operate = 0
#RSI>80?????RSI<20????
if df.iat[(dflen-1),18]>80 or df.iat[(dflen-1),19]>80:
operate = operate - 2
elif df.iat[(dflen-1),18]<20 or df.iat[(dflen-1),19]<20:
operate = operate + 2
#RSI??50???????????50????????
if (df.iat[(dflen-2),18]<=50 and df.iat[(dflen-1),18]>50) or (df.iat[(dflen-2),19]<=50 and df.iat[(dflen-1),19]>50):
operate = operate + 4
elif (df.iat[(dflen-2),18]>=50 and df.iat[(dflen-1),18]<50) or (df.iat[(dflen-2),19]>=50 and df.iat[(dflen-1),19]<50):
operate = operate - 4
#RSI??????????RSI?????????
if df.iat[(dflen-1),7]>=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]>=df.iat[(dflen-1),9]:#K???
if (slowrealMA5[MAlen-1]<=slowrealMA10[MAlen-1] and slowrealMA10[MAlen-1]<=slowrealMA20[MAlen-1]) or \
(fastrealMA5[MAlen-1]<=fastrealMA10[MAlen-1] and fastrealMA10[MAlen-1]<=fastrealMA20[MAlen-1]): #RSI??
operate = operate - 1
elif df.iat[(dflen-1),7]<=df.iat[(dflen-1),8] and df.iat[(dflen-1),8]<=df.iat[(dflen-1),9]:#K???
if (slowrealMA5[MAlen-1]>=slowrealMA10[MAlen-1] and slowrealMA10[MAlen-1]>=slowrealMA20[MAlen-1]) or \
(fastrealMA5[MAlen-1]>=fastrealMA10[MAlen-1] and fastrealMA10[MAlen-1]>=fastrealMA20[MAlen-1]): #RSI??
operate = operate + 1
#?????????????????????????????????????????????????????????????????
if df.iat[(dflen-1),19]> df.iat[(dflen-1),18] and df.iat[(dflen-2),19]<=df.iat[(dflen-2),18]:
operate = operate + 10
elif df.iat[(dflen-1),19]< df.iat[(dflen-1),18] and df.iat[(dflen-2),19]>=df.iat[(dflen-2),18]:
operate = operate - 10
return (df,operate)
