code: def default_smoother(x, s_arg=None):
      """ """
      #    _x = x.copy()
      #    _x.sort()
      _x = np.sort(x)
      n = x.shape[0]
      # taken form smooth.spline in R
  
      # if n < 50:
      if n < 500:
          nknots = n
      else:
          a1 = np.log(50) / np.log(2)
          a2 = np.log(100) / np.log(2)
          a3 = np.log(140) / np.log(2)
          a4 = np.log(200) / np.log(2)
          if n < 200:
              nknots = 2 ** (a1 + (a2 - a1) * (n - 50) / 150.0)
          elif n < 800:
              nknots = 2 ** (a2 + (a3 - a2) * (n - 200) / 600.0)
          elif n < 3200:
              nknots = 2 ** (a3 + (a4 - a3) * (n - 800) / 2400.0)
          else:
              nknots = 200 + (n - 3200.0) ** 0.2
      knots = _x[np.linspace(0, n - 1, nknots).astype(np.int32)]
  
      # s = SmoothingSpline(knots, x=x.copy())
      # when I set order=2, I get nans in the GAM prediction
      if s_arg is None:
          order = 3  # what about knots? need smoother *args or **kwds
      else:
          order = s_arg
      s = PolySmoother(
          order, x=x.copy()
      )  # TODO: change order, why copy?
      #    s.gram(d=2)
      #    s.target_df = 5
      return s
  
imports: import numpy
  from statsmodels.genmod import families
  from statsmodels.sandbox.nonparametric.smoothers import PolySmoother
  from statsmodels.genmod.generalized_linear_model import GLM
  from statsmodels.tools.sm_exceptions import IterationLimitWarning, iteration_limit_doc
  import warnings
label_desc: Use image node_id 1 for calling a global function with example usage: default_smoother(x, s_arg) and returns: s