Merge pull request #356 from freqtrade/stash86-patch-1

the zema written here is actually DEMA

technical/indicators/indicators.py

@@ -8,7 +8,7 @@
 from numpy.core.records import ndarray
 from pandas import DataFrame, Series
 
-from .overlap_studies import sma, vwma, zema
+from .overlap_studies import sma, vwma
 
 ########################################
 #
@@ -1134,7 +1134,6 @@ def PMAX(dataframe, period=10, multiplier=3, length=12, MAtype=1, src=1):  # noq
     # MAtype==6 --> TEMA
     # MAtype==7 --> WMA
     # MAtype==8 --> VWMA
-    # MAtype==9 --> zema
     if src == 1:
         masrc = df["close"]
     elif src == 2:
@@ -1157,8 +1156,6 @@ def PMAX(dataframe, period=10, multiplier=3, length=12, MAtype=1, src=1):  # noq
         df[mavalue] = ta.WMA(df, timeperiod=length)
     elif MAtype == 8:
         df[mavalue] = vwma(df, length)
-    elif MAtype == 9:
-        df[mavalue] = zema(df, period=length)
     # Compute basic upper and lower bands
     df["basic_ub"] = df[mavalue] + (multiplier * df[atr])
     df["basic_lb"] = df[mavalue] - (multiplier * df[atr])

technical/indicators/overlap_studies.py

@@ -34,6 +34,10 @@ def bollinger_bands(
 
 
 # DEMA                 Double Exponential Moving Average
+def dema(dataframe, period, field="close"):
+    import talib.abstract as ta
+
+    return ta.DEMA(dataframe, timeperiod=period, price=field)
 
 
 # EMA                  Exponential Moving Average
@@ -88,19 +92,3 @@ def hull_moving_average(dataframe, period, field="close") -> ndarray:
 
 def vwma(df, window, price="close"):
     return (df[price] * df["volume"]).rolling(window).sum() / df.volume.rolling(window).sum()
-
-
-def zema(dataframe, period, field="close"):
-    """
-    zero lag ema
-    :param dataframe:
-    :param period:
-    :param field:
-    :return:
-    """
-    dataframe = dataframe.copy()
-    dataframe["ema1"] = ema(dataframe, period, field)
-    dataframe["ema2"] = ema(dataframe, period, "ema1")
-    dataframe["d"] = dataframe["ema1"] - dataframe["ema2"]
-    dataframe["zema"] = dataframe["ema1"] + dataframe["d"]
-    return dataframe["zema"]

tests/test_indicators_generic.py

@@ -33,6 +33,7 @@
         (ti.sma, [10]),
         (ti.stc, []),
         (ti.td_sequential, []),
+        (ti.dema, [10]),
         (ti.tema, [10]),
         # (ti.tv_hma, []),
         (ti.tv_wma, []),
@@ -42,7 +43,6 @@
         (ti.vwma, [10]),
         (ti.vwmacd, []),
         (ti.williams_percent, []),
-        (ti.zema, [10]),
     ],
 )
 def test_indicators_generic_interface(function, args, testdata_1m_btc):