code: def distribution(self, start=None, end=None, normalized=True, mask=None):
          
  
          start, end, mask = self._check_boundaries(start, end, mask=mask)
  
          counter = histogram.Histogram()
          for start, end, _ in mask.iterperiods(value=True):
              for t0, t1, value in self.iterperiods(start, end):
                  duration = utils.duration_to_number(
                      t1 - t0,
                      units='seconds',
                  )
                  try:
                      counter[value] += duration
                  except histogram.UnorderableElements as e:
  
                      counter = histogram.Histogram.from_dict(
                          dict(counter), key=hash)
                      counter[value] += duration
  
          # divide by total duration if result needs to be normalized
          if normalized:
              return counter.normalized()
          else:
              return counter
docs: Calculate the distribution of values over the given time range from
          `start` to `end`.
  
          Args:
  
              start (orderable, optional): The lower time bound of
                  when to calculate the distribution. By default, the
                  first time point will be used.
  
              end (orderable, optional): The upper time bound of
                  when to calculate the distribution. By default, the
                  last time point will be used.
  
              normalized (bool): If True, distribution will sum to
                  one. If False and the time values of the TimeSeries
                  are datetimes, the units will be seconds.
  
              mask (:obj:`TimeSeries`, optional): A
                  domain on which to calculate the distribution.
  
          Returns:
  
              :obj:`Histogram` with the results.