2018-02-13 15:47:26 +00:00
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from math import exp, pi, sqrt, cos
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2018-02-14 08:17:43 +00:00
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import numpy
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import talib as ta
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2018-02-13 09:37:59 +00:00
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from pandas import Series
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def went_up(series: Series) -> Series:
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return series > series.shift(1)
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def went_down(series: Series) -> Series:
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return series < series.shift(1)
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2018-02-13 15:47:26 +00:00
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def ehlers_super_smoother(series: Series, smoothing: float = 6):
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magic = pi * sqrt(2) / smoothing
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a1 = exp(-magic)
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coeff2 = 2 * a1 * cos(magic)
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coeff3 = -a1 * a1
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coeff1 = (1 - coeff2 - coeff3) / 2
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filtered = series.copy()
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for i in range(2, len(series)):
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filtered.iloc[i] = coeff1 * (series.iloc[i] + series.iloc[i-1]) + \
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coeff2 * filtered.iloc[i-1] + coeff3 * filtered.iloc[i-2]
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return filtered
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2018-02-14 08:17:43 +00:00
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def fishers_inverse(series: Series, smoothing: float = 0):
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""" Does a smoothed fishers inverse transformation.
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Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
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v1 = 0.1 * (series - 50)
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if smoothing > 0:
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v2 = ta.WMA(v1.values, timeperiod=smoothing)
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else:
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v2 = v1
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return (numpy.exp(2 * v2)-1) / (numpy.exp(2 * v2) + 1)
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