code: def apply_mask(self, x=None):
          '''
          Returns the outlier mask, an array of indices corresponding to the
          non-outliers.
  
          :param numpy.ndarray x: If specified, returns the masked version of \
                 :py:obj:`x` instead. Default :py:obj:`None`
  
          '''
  
          if x is None:
              return np.delete(np.arange(len(self.time)), self.mask)
          else:
              return np.delete(x, self.mask, axis=0f apply_mask(self, x=None):
          '''
          Returns the outlier mask, an array of indices corresponding to the
          non-outliers.
  
          :param numpy.ndarray x: If specified, returns the masked version of \
                 :py:obj:`x` instead. Default :py:obj:`None`
  
          '''
  
          if x is None:
              return np.delete(np.arange(len(self.time)), self.mask)
          else:
              return np.delete(x, self.mask, axis=0)
docs: Returns the outlier mask, an array of indices corresponding to the
          non-outliers.
  
          :param numpy.ndarray x: If specified, returns the masked version of \
                 :py:obj:`x` instead. Default :py:obj:`None`