code: def omega_ratio(returns, annual_return_threshhold=0.0):
      """
      Determines the Omega ratio of a strategy.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
          - See full explanation in :func:`~pyfolio.timeseries.cum_returns`.
      annual_return_threshold : float, optional
          Minimum acceptable return of the investor. Annual threshold over which
          returns are considered positive or negative. It is converted to a
          value appropriate for the period of the returns for this ratio.
          E.g. An annual minimum acceptable return of 100 translates to a daily
          minimum acceptable return of 0.01848.
              (1 + 100) ** (1. / 252) - 1 = 0.01848
          Daily returns must exceed this value to be considered positive. The
          daily return yields the desired annual return when compounded over
          the average number of business days in a year.
              (1 + 0.01848) ** 252 - 1 = 99.93
          - Defaults to 0.0
  
  
      Returns
      -------
      float
          Omega ratio.
  
      Note
      -----
      See https://en.wikipedia.org/wiki/Omega_ratio for more details.
      """
  
      return ep.omega_ratio(
          returns, required_return=annual_return_threshhold
      )
  
imports: from __future__ import division
  from collections import OrderedDict
  from functools import partial
  import empyrical
  import numpy
  import pandas
  import scipy
  import scipy.stats
  from sklearn import linear_model
  from .deprecate import deprecated
  from .interesting_periods import PERIODS
  from .txn import get_turnover
  from .utils import APPROX_BDAYS_PER_MONTH, APPROX_BDAYS_PER_YEAR
  from .utils import DAILY
label_desc: Use image node_id 6 for calling a global function with example usage: omega_ratio(returns, annual_return_threshhold) and returns: ep