code: def test_smoothing_limit_1d(self, xp, scp):
      # For large smoothing parameters, the interpolant should approach a
      # least squares fit of a polynomial with the specified degree.
      seq = Halton(1, scramble=False, seed=_np.random.RandomState())
  
      degree = 3
      smoothing = 1e8
  
      x = xp.asarray(3 * seq.random(50))
      xitp = xp.asarray(3 * seq.random(50))
  
      y = _1d_test_function(x, xp)
  
      yitp1 = self.build(scp, x, y, degree=degree, smoothing=smoothing)(
          xitp
      )
  
      if xp is _np:
          P = _vandermonde(cp.asarray(x), degree).get()
          Pitp = _vandermonde(cp.asarray(xitp), degree).get()
      else:
          P = _vandermonde(x, degree)
          Pitp = _vandermonde(xitp, degree)
  
      yitp2 = Pitp.dot(xp.linalg.lstsq(P, y, rcond=None)[0])
  
      return yitp1, yitp2
  
imports: import pickle
  import pytest
  import warnings
  import numpy
  from numpy.linalg import LinAlgError
  import cupy
  import cupyx
  from cupy import testing
  import cupyx.scipy.interpolate
  from cupyx.scipy.interpolate._rbfinterp import _AVAILABLE, _SCALE_INVARIANT, _NAME_TO_MIN_DEGREE, NAME_TO_FUNC, _monomial_powers, polynomial_matrix, kernel_matrix
label_desc: Use image node_id 2 for calling the TestRBFInterpolatorNeighborsNone obj's underlying member method code with example usage: obj.test_smoothing_limit_1d(xp, scp) and returns: yitp1,  yitp2