docs: def fisher_angular_deviation(dec=None, inc=None, di_block=None, confidence=95):
      '''
      The angle from the true mean within which a chosen percentage of directions
      lie can be calculated from the Fisher distribution. This function uses the
      calculated Fisher concentration parameter to estimate this angle from
      directional data. The 63 percent confidence interval is often called the
      angular standard deviation.
  
      Parameters
      ----------
      dec : list of declinations or longitudes
      inc : list of inclinations or latitudes
      di_block : a nested list of [dec,inc,1.0]
          A di_block can be provided instead of dec, inc lists in which case it
          will be used. Either dec, inc lists or a di_block need to be provided.
      confidence : 50 percent, 63 percent or 95 percent
  
      Returns
      -------
      theta : critical angle of interest from the mean which contains the
          percentage of directions specified by the confidence parameter
      '''
      if di_block is None:
          di_block = make_di_block(dec, inc)
          mean = pmag.fisher_mean(di_block)
      else:
          mean = pmag.fisher_mean(di_block)
      if confidence == 50:
          theta = old_div(67.5, np.sqrt(mean['k']))
      if confidence == 63:
          theta = old_div(81, np.sqrt(mean['k']))
      if confidence == 95:
          theta = old_div(140, np.sqrt(mean['k']))
      return theta