freqtrade_origin/freqtrade/indicator_helpers.py

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from math import cos, exp, pi, sqrt
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import numpy as np
import talib as ta
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from pandas import Series
def went_up(series: Series) -> bool:
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return series > series.shift(1)
def went_down(series: Series) -> bool:
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return series < series.shift(1)
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def ehlers_super_smoother(series: Series, smoothing: float = 6) -> Series:
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magic = pi * sqrt(2) / smoothing
a1 = exp(-magic)
coeff2 = 2 * a1 * cos(magic)
coeff3 = -a1 * a1
coeff1 = (1 - coeff2 - coeff3) / 2
filtered = series.copy()
for i in range(2, len(series)):
filtered.iloc[i] = coeff1 * (series.iloc[i] + series.iloc[i-1]) + \
coeff2 * filtered.iloc[i-1] + coeff3 * filtered.iloc[i-2]
return filtered
def fishers_inverse(series: Series, smoothing: float = 0) -> np.ndarray:
""" Does a smoothed fishers inverse transformation.
Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
v1 = 0.1 * (series - 50)
if smoothing > 0:
v2 = ta.WMA(v1.values, timeperiod=smoothing)
else:
v2 = v1
return (np.exp(2 * v2)-1) / (np.exp(2 * v2) + 1)