def di_boot(DIs, nb=5000):
    """
     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
    """
#
# 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