new_contents: """Functions for calculating errors by combining different datasets."""
  
  import math
  
  def asymmetric_hessian_error(value_lists):
      """Calculate the asymmetric hessian error from a list of datasets,
      where the first dataset stems from a PDF CV run."""
      lows = []
      highs = []
      transposed_value_lists = zip(*value_lists)
      for values in transposed_value_lists:
          central_value = values[0]
          evs = values[1:]
          error = [0.0, 0.0]
          for i in range(0, len(evs), 2):
              (ev_p, ev_m) = evs[i:i+2]
              error[0] += max(ev_p - central_value, ev_m - central_value, 0)**2
              error[1] += max(central_value - ev_p, central_value - ev_m, 0)**2
          high = central_value + math.sqrt(error[0])
          low = central_value - math.sqrt(error[1])
          highs.append(high)
          lows.append(low)
      return (lows, highs)
  
subject: Add a calc function for asymmetric hessian errors