docs: def cv(data, units=False):
      """
      Calculate coefficient of variation (cv) of data. Mean and standard deviation
      are computed across time.
  
  
      Parameters
      ----------
      data : numpy.ndarray
          1st axis unit, 2nd axis time.
      units : bool
          Average `cv`.
  
  
      Returns
      -------
      numpy.ndarray
          If units=False, series of unit `cv`s.
      float
          If units=True, mean `cv` across units.
  
  
      Examples
      --------
      >>> cv(np.array([[1, 2, 3, 4, 5, 6], [11, 2, 3, 3, 4, 5]]))
      array([ 0.48795004,  0.63887656])
  
      >>> cv(np.array([[1, 2, 3, 4, 5, 6], [11, 2, 3, 3, 4, 5]]), units=True)
      0.56341330073710316
  
      """
  
      mu = mean(data, time=True)
      var = variance(data, time=True)
      cv = np.sqrt(var) / mu
      
      if units is True:
          return np.mean(cv)
      else:
          return cv