code: def alpha_beta(
      returns,
      factor_returns,
      risk_free=0.0,
      period=DAILY,
      annualization=None,
      out=None,
  ):
      """Calculates annualized alpha and beta.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
          - See full explanation in :func:`~empyrical.stats.cum_returns`.
      factor_returns : pd.Series
           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
      """
      returns, factor_returns = _aligned_series(returns, factor_returns)
  
      return alpha_beta_aligned(
          returns,
          factor_returns,
          risk_free=risk_free,
          period=period,
          annualization=annualization,
          out=out,
      )
  
imports: from __future__ import division
  import math
  import pandas
  import numpy
  from math import pow
  from scipy import stats, optimize
  from six import iteritems
  from sys import float_info
  from .utils import nanmean, nanstd, nanmin, up, down, roll, rolling_window
  from .periods import ANNUALIZATION_FACTORS, APPROX_BDAYS_PER_YEAR
  from .periods import DAILY, WEEKLY, MONTHLY, QUARTERLY, YEARLY
label_desc: Use image node_id 22 for calling a global function with example usage: alpha_beta(returns, factor_returns, risk_free, period, annualization, out) and returns: alpha_beta_aligned