Pinescript到Python的获取系列的真实价值是模棱两可的

Question

我正在将Pinescript Indicator转换为python以与大熊猫一起使用：

这是pinescrip代码：

RSI_Period = input(14,title='RSI')
SF = input(5,title='Slow Factor')
QQE=input(4.236)

Wilders_Period = RSI_Period * 2 - 1


Rsi = rsi(close,RSI_Period)
RsiMa = ema(Rsi, SF)
AtrRsi = abs(RsiMa[1] - RsiMa)
MaAtrRsi = ema(AtrRsi, Wilders_Period)
dar = ema(MaAtrRsi,Wilders_Period) * QQE


DeltaFastAtrRsi= dar
RSIndex=RsiMa
newshortband=  RSIndex + DeltaFastAtrRsi
newlongband= RSIndex - DeltaFastAtrRsi
longband=RSIndex[1] > longband[1] and RSIndex > longband[1]?
 max(longband[1],newlongband):newlongband
shortband=RSIndex[1] < shortband[1] and  RSIndex < shortband[1]?
 min(shortband[1], newshortband):newshortband
trend=cross(RSIndex, shortband[1])?1:cross(longband[1], RSIndex)?-1:nz(trend[1],1)
FastAtrRsiTL = trend==1? longband: shortband

plot(FastAtrRsiTL,color=red)
plot(RsiMa,color=yellow)

现在这就是我到目前为止在python中得到的：

RSIPeriod = 14
SF = 5
QQE=4.236
WildersPeriod = RSIPeriod * 2 - 1     

df['RSI'] = ta.RSI(df['Price'], RSIPeriod)
df['RSI_ma'] = ta.EMA(df['RSI'], SF)
df['ATRrsi'] = abs(df['RSI_ma'].shift(1) - df['RSI_ma'])
df['MaATRrsi'] = ta.EMA(df['ATRrsi'], WildersPeriod)
df['dar'] = ta.EMA(df['MaATRrsi'], WildersPeriod) * QQE
df['newshortband'] = df['RSI_ma'] + df['dar']
df['newlongband'] = df['RSI_ma'] - df['dar']
df['longband'] = 0.0
df['longband'] =  np.where( df['RSI_ma'].shift(1) > df['longband'].shift(1) and df['RSI_ma'] > df['longband'].shift(1),
                           max(df['longband'].shift(1) ,df['newlongband']), df['newlongband'])
df['shortband'] = 0.0
df['shortband'] =  np.where( df['RSI_ma'].shift(1) < df['shortband'].shift(1) and df['RSI_ma'] < df['shortband'].shift(1),
                           max(df['shortband'].shift(1) ,df['newshortband']), df['newshortband'])

df['trend'] = np.where(df['RSI_ma'] > df['dar'].shift(1), 1, -1)    
df['FastAtrRsiTL'] = np.where(df['trend'] == 1, df['longband'], df['shortband'])

这是错误： ----> 4 df ['longband'] = np.where（df ['RSI_ma']。shift（1）> df ['longband']。shift（1）和df ['RSI_ma']> df [ 'longband']。shift（1），       5个最大值（df ['longlong']。shift（1），df ['newlongband']），df ['newlongband']）       6 df ['shortband'] = 0.0

〜\ Anaconda3 \ envs \ finance \ lib \ site-packages \ pandas \ core \ generic.py in nonzero （自己）    1571提高ValueError（“ {0}的真值是不明确的。”    1572“使用a.empty，a.bool（），a.item（），a.any（）或a.all（）。” -> 1573 .format（self。 class 。 name ））    1574    1575 bool = nonzero

（非零）

ValueError：系列的真值不明确。使用a.empty，a.bool（），a.item（），a.any（）或a.all（）。