text: # -*- coding: utf-8 -*-
  """
  Created on Mon Oct 23 16:31:30 2017
  
  @author: ben
  """
  
  import numpy as np
  
  def RDE(x):
      xs=x.copy()
      xs=np.isfinite(xs)   # this changes xs from values to a boolean
      if np.sum(xs)<2 :
          return np.nan
      ind=np.arange(0.5, np.sum(xs))
      LH=np.interp(np.array([0.16, 0.84])*np.sum(xs), ind, np.sort(x[xs]))
      #print('LH =',LH)
      return (LH[1]-LH[0])/2.  # trying to get some kind of a width of the data ~variance
  
  
  #import scipy.stats as stats
  #def RDE(x):
  #    return (stats.scoreatpercentile(x, 84 )-stats.scoreatpercentile(x, 16))/2.