KAMA classmethod - Need to handle Efficiency Ratio calculation when volatility is zero

[edgetrader]

Possible to have nan values in the pd.Series output from def ER() classmethod when volatility is zero. Once there are nan values, smoothing_constant will have nan values. Maybe should consider dropping records with nan smoothing_constant or force the smoothing_constant to zero?

    @classmethod
    def ER(cls, ohlc: DataFrame, period: int = 10, column: str = "close") -> Series:
        """The Kaufman Efficiency indicator is an oscillator indicator that oscillates between +100 and -100, where zero is the center point.
         +100 is upward forex trending market and -100 is downwards trending markets."""

        change = ohlc[column].diff(period).abs()
        volatility = ohlc[column].diff().abs().rolling(window=period).sum()

        return pd.Series(change / volatility, name="{0} period ER".format(period))

    @classmethod
    def KAMA(
        cls,
        ohlc: DataFrame,
        er: int = 10,
        ema_fast: int = 2,
        ema_slow: int = 30,
        period: int = 20,
        column: str = "close",
    ) -> Series:
        """Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility.
        Its main advantage is that it takes into consideration not just the direction, but the market volatility as well."""

        er = cls.ER(ohlc, er)
        fast_alpha = 2 / (ema_fast + 1)
        slow_alpha = 2 / (ema_slow + 1)
        sc = pd.Series(
            (er * (fast_alpha - slow_alpha) + slow_alpha) ** 2,
            name="smoothing_constant",
        )  ## smoothing constant

        ... ...

[0xDub]

+1

I copied finta locally and made the adjustment:
sc = pd.Series( (er * (fast_alpha - slow_alpha) + slow_alpha) ** 2, name="smoothing_constant", ).fillna(0) ## smoothing constant

".fillna(0)" added to the end of pd.Series(), it's no longer throwing NaN values