code: def test_pairwise_x_and_y_error_shape(make_data):
      data, _ = make_data()
      t = ClinicalKernelTransform()
      t.fit(data)
  
      with pytest.raises(
          ValueError, match="X and Y have different number of features"
      ):
          t.pairwise_kernel(data.iloc[0, :], data.iloc[1, :2])
  
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 14 for calling the TestClinicalKernel obj's underlying member method code with example usage: obj.test_pairwise_x_and_y_error_shape(make_data) without return types