How to use the ta.utils.ema function in ta

def _run(self):
        ema1 = ema(self._close, self._n, self._fillna)
        ema2 = ema(ema1, self._n, self._fillna)
        ema3 = ema(ema2, self._n, self._fillna)
        self._trix = (ema3 - ema3.shift(1, fill_value=ema3.mean())) / ema3.shift(1, fill_value=ema3.mean())
        self._trix *= 100

def _run(self):
        amplitude = self._high - self._low
        ema1 = ema(amplitude, self._n, self._fillna)
        ema2 = ema(ema1, self._n, self._fillna)
        mass = ema1 / ema2
        self._mass = mass.rolling(self._n2, min_periods=0).sum()

def _run(self):
        self._emafast = ema(self._close, self._n_fast, self._fillna)
        self._emaslow = ema(self._close, self._n_slow, self._fillna)
        self._macd = self._emafast - self._emaslow
        self._macd_signal = ema(self._macd, self._n_sign, self._fillna)
        self._macd_diff = self._macd - self._macd_signal

def ema_indicator(self) -> pd.Series:
        """Exponential Moving Average (EMA)

        Returns:
            pandas.Series: New feature generated.
        """
        ema_ = ema(self._close, self._n, self._fillna)
        return pd.Series(ema_, name=f'ema_{self._n}')

def _run(self):
        self._emafast = ema(self._close, self._n_fast, self._fillna)
        self._emaslow = ema(self._close, self._n_slow, self._fillna)
        self._macd = self._emafast - self._emaslow
        self._macd_signal = ema(self._macd, self._n_sign, self._fillna)
        self._macd_diff = self._macd - self._macd_signal

def _run(self):
        ema1 = ema(self._close, self._n, self._fillna)
        ema2 = ema(ema1, self._n, self._fillna)
        ema3 = ema(ema2, self._n, self._fillna)
        self._trix = (ema3 - ema3.shift(1, fill_value=ema3.mean())) / ema3.shift(1, fill_value=ema3.mean())
        self._trix *= 100

def _run(self):
        ema1 = ema(self._close, self._n, self._fillna)
        ema2 = ema(ema1, self._n, self._fillna)
        ema3 = ema(ema2, self._n, self._fillna)
        self._trix = (ema3 - ema3.shift(1, fill_value=ema3.mean())) / ema3.shift(1, fill_value=ema3.mean())
        self._trix *= 100