Update indicators.py

Stell0 · Nov 4, 2024 · eb9c193 · eb9c193
1 parent df7d863
commit eb9c193
Showing 1 changed file with 8 additions and 8 deletions.
diff --git a/src/indicators.py b/src/indicators.py
@@ -9,30 +9,30 @@
 LINEARREG_timeperiod = int(os.environ.get("LINEARREG_timeperiod",10))
 
 def rsi(df,timeperiod=14,label="RSI",):
-    df[label] = ta.RSI(df['Close'], timeperiod=timeperiod)
+    df[label] = ta.RSI(df['Close'].to_numpy(), timeperiod=timeperiod)
     return df
 
 def sma(df,timeperiod=200,label="SMA"):
     df[label] = ta.SMA(df['Close'], timeperiod=timeperiod)
     return df 
 
 def linearreg(df,timeperiod=10):
-    df['LINEARREG'] = ta.LINEARREG(df['Close'], timeperiod=timeperiod) # b+m*(period-1)
-    df['LINEARREG_SLOPE'] = ta.LINEARREG_SLOPE(df['Close'], timeperiod=timeperiod) # m
-    df['LINEARREG_INTERCEPT'] = ta.LINEARREG_INTERCEPT(df['Close'], timeperiod=timeperiod) # b
-    df['LRFORECAST'] = df['LINEARREG_INTERCEPT'] + df['LINEARREG_SLOPE'] * timeperiod
+    df['LINEARREG'] = ta.LINEARREG(df['Close'].to_numpy(), timeperiod=timeperiod) # b+m*(period-1)
+    df['LINEARREG_SLOPE'] = ta.LINEARREG_SLOPE(df['Close'].to_numpy(), timeperiod=timeperiod) # m
+    df['LINEARREG_INTERCEPT'] = ta.LINEARREG_INTERCEPT(df['Close'].to_numpy(), timeperiod=timeperiod) # b
+    df['LRFORECAST'] = df['LINEARREG_INTERCEPT'].to_numpy() + df['LINEARREG_SLOPE'].to_numpy() * timeperiod
     return df
 
 def macd(df,fastperiod=12,slowperiod=26,signalperiod=9):
-	macd, macdsignal, macdhist = ta.MACD(df['Close'], fastperiod=fastperiod, slowperiod=slowperiod, signalperiod=signalperiod)
+	macd, macdsignal, macdhist = ta.MACD(df['Close'].to_numpy(), fastperiod=fastperiod, slowperiod=slowperiod, signalperiod=signalperiod)
 	df['MACD'] = macd
 	df['MACD_SIGNAL'] = macdsignal
 	df['MACD_HIST'] = macdhist
 	return df
 
 def bb(df,timeperiod=20,nbdevup=2,nbdevdn=2,matype=0):
-	upperband, middleband, lowerband = ta.BBANDS(df['Close'], timeperiod=timeperiod, nbdevup=nbdevup, nbdevdn=nbdevdn, matype=matype)
+	upperband, middleband, lowerband = ta.BBANDS(df['Close'].to_numpy(), timeperiod=timeperiod, nbdevup=nbdevup, nbdevdn=nbdevdn, matype=matype)
 	df['BB_UPPER'] = upperband
 	df['BB_MIDDLE'] = middleband
 	df['BB_LOWER'] = lowerband
-	return df
+	return df