code: def from_nuniq_interval_set(cls, nuniq_is):
          
          nested_is = IntervalSet()
          # Appending a list is faster than appending a numpy array
          # For these algorithms we append a list and create the interval set from the finished list
          rtmp = []
          last_order = 0
          intervals = nuniq_is._intervals
          diff_order = IntervalSet.HPY_MAX_ORDER
          shift_order = 2 * diff_order
          for interval in intervals:
              for j in range(interval[0], interval[1]):
                  order, i_pix = uniq2orderipix(j)
  
                  if order != last_order:
                      nested_is = nested_is.union(IntervalSet(np.asarray(rtmp)))
                      rtmp = []
                      last_order = order
                      diff_order = IntervalSet.HPY_MAX_ORDER - order
                      shift_order = 2 * diff_order
  
                  rtmp.append((i_pix << shift_order, (i_pix + 1) << shift_order))
  
          nested_is = nested_is.union(IntervalSet(np.asarray(rtmp)))
          return nested_is
docs: Convert an IntervalSet containing NUNIQ intervals to an IntervalSet representing HEALPix
          cells following the NESTED numbering scheme.
  
          Parameters
          ----------
          nuniq_is : `IntervalSet`
              IntervalSet object storing HEALPix cells as [ipix + 4*4^(order), ipix+1 + 4*4^(order)[ intervals.
  
          Returns
          -------
          interval : `IntervalSet`
              IntervalSet object storing HEALPix cells as [ipix*4^(29-order), (ipix+1)*4^(29-order)[ intervals.