code: def data_direct_neighbor_with_censoring(self):
      kind = "next"
      time, status = self.time_and_event
  
      expected = self._create_expected((3, 6))
      expected[0, 0] = -1
      expected[0, 1] = 1
      expected[1, 1] = -1
      expected[1, 2] = 1
      expected[2, 3] = -1
      expected[2, 4] = 1
  
      comparable_pairs = np.array([True, True, False, True, False])
      expected_diff = (time[1:] - time[:-1])[comparable_pairs]
  
      return (
          time,
          status.astype(np.uint8),
          kind,
          expected,
          expected_diff,
      )
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  import pytest
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.preprocessing import scale
  from sksurv.column import encode_categorical
  from sksurv.datasets import load_gbsg2
  from sksurv.exceptions import NoComparablePairException
  from sksurv.svm._minlip import create_difference_matrix
  from sksurv.svm.minlip import HingeLossSurvivalSVM, MinlipSurvivalAnalysis
  from sksurv.testing import FixtureParameterFactory, assert_cindex_almost_equal
  from sksurv.util import Surv
label_desc: Use image node_id 5 for calling the DifferenceMatrixToyDataCases obj's underlying member method code with example usage: obj.data_direct_neighbor_with_censoring() and returns: time,  status,  kind,  expected,  expected_diff