code: def test_polynomial_and_spline_array_order(est):
      """Test that output array has the given order."""
      X = np.arange(10).reshape(5, 2)
  
      def is_c_contiguous(a):
          return np.isfortran(a.T)
  
      assert is_c_contiguous(est().fit_transform(X))
      assert is_c_contiguous(est(order="C").fit_transform(X))
      assert np.isfortran(est(order="F").fit_transform(X))
  
imports: import sys
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy import sparse
  from scipy.interpolate import BSpline
  from scipy.sparse import random
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import KBinsDiscretizer, PolynomialFeatures, SplineTransformer
  from sklearn.preprocessing._csr_polynomial_expansion import _calc_expanded_nnz, _calc_total_nnz, _get_sizeof_LARGEST_INT_t
  from sklearn.utils._testing import assert_array_almost_equal
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS, parse_version, sp_version
label_desc: Use image node_id 1 for calling a global function with example usage: test_polynomial_and_spline_array_order(est) and returns: np