code: def alpha_beta_aligned(returns,
                         factor_returns,
                         risk_free=0.0,
                         period=DAILY,
                         annualization=None,
                         out=None):
      
      if out is None:
          out = np.empty(returns.shape[1:] + (2,), dtype='float64')
  
      b = beta_aligned(returns, factor_returns, risk_free, out=out[..., 1])
      alpha_aligned(
          returns,
          factor_returns,
          risk_free,
          period,
          annualization,
          out=out[..., 0],
          _beta=b,
      )
  
      return out
docs: Calculates annualized alpha and beta.
  
      If they are pd.Series, expects returns and factor_returns have already
      been aligned on their labels.  If np.ndarray, these arguments should have
      the same shape.
  
      Parameters
      ----------
      returns : pd.Series or np.ndarray
          Daily returns of the strategy, noncumulative.
          - See full explanation in :func:`~empyrical.stats.cum_returns`.
      factor_returns : pd.Series or np.ndarray
           Daily noncumulative returns of the factor to which beta is
           computed. Usually a benchmark such as the market.
           - This is in the same style as returns.
      risk_free : int, float, optional
          Constant risk-free return throughout the period. For example, the
          interest rate on a three month us treasury bill.
      period : str, optional
          Defines the periodicity of the 'returns' data for purposes of
          annualizing. Value ignored if `annualization` parameter is specified.
          Defaults are::
  
              'monthly':12
              'weekly': 52
              'daily': 252
  
      annualization : int, optional
          Used to suppress default values available in `period` to convert
          returns into annual returns. Value should be the annual frequency of
          `returns`.
      out : array-like, optional
          Array to use as output buffer.
          If not passed, a new array will be created.
  
      Returns
      -------
      alpha : float
      beta : float