code: def test_polynomial_reproduction(self, xp, scp):
      # If the observed data comes from a polynomial, then the interpolant
      # should be able to reproduce the polynomial exactly, provided that
      # `degree` is sufficiently high.
      rng = _np.random.RandomState(0)
      seq = Halton(2, scramble=False, seed=rng)
      degree = 3
  
      x = xp.asarray(seq.random(50))
      xitp = xp.asarray(seq.random(50))
  
      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)
  
      poly_coeffs = rng.normal(0.0, 1.0, P.shape[1])
      poly_coeffs = xp.asarray(poly_coeffs)
  
      y = P.dot(poly_coeffs)
      yitp1 = Pitp.dot(poly_coeffs)
      yitp2 = self.build(scp, x, y, degree=degree)(xitp)
  
      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 4 for calling the _TestRBFInterpolator obj's underlying member method code with example usage: obj.test_polynomial_reproduction(xp, scp) and returns: yitp1,  yitp2