code: def test_pairwise_feature_mismatch(make_data):
      data, _ = make_data()
      t = ClinicalKernelTransform()
      t.fit(data)
  
      with pytest.raises(
          ValueError,
          match=r"Incompatible dimension for X and Y matrices: X.shape\[1\] == 4 while Y.shape\[1\] == 17",
      ):
          pairwise_kernels(
              t.X_fit_,
              np.zeros((2, 17), dtype=float),
              metric=t.pairwise_kernel,
              n_jobs=1,
          )
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal
  import pandas
  import pytest
  from sklearn.base import clone
  from sklearn.metrics.pairwise import pairwise_kernels
  from sksurv.kernels import ClinicalKernelTransform, clinical_kernel
label_desc: Use image node_id 18 for calling the TestClinicalKernel obj's underlying member method code with example usage: obj.test_pairwise_feature_mismatch(make_data) without return types