code: def di_boot(DIs, nb=5000):
      
  #
  # now do bootstrap to collect BDIs  bootstrap means
  #
      BDIs = []  # number of bootstraps, list of bootstrap directions
  #
  
      for k in range(nb):  # repeat nb times
          #        if k%50==0:print k,' out of ',nb
          pDIs = pseudo(DIs)  # get a pseudosample
          bfpars = fisher_mean(pDIs)  # get bootstrap mean bootstrap sample
          BDIs.append([bfpars['dec'], bfpars['inc']])
      return BDIs
docs: returns bootstrap means  for Directional data
       Parameters
       _________________
       DIs : nested list of Dec,Inc pairs
       nb : number of bootstrap pseudosamples
  
       Returns
      -------
       BDIs:   nested list of bootstrapped mean Dec,Inc pairs