code: def setUp(self):
      self.features = [
          np.array([[0, 1, 0], [0, 0, 0], [0, 1, 1]], dtype="float64"),
          np.array([[1, 1, 1], [0, 0, 1], [1, 1, 0]], dtype="float64"),
          np.zeros((3, 3), dtype="float64"),
          np.array([[1, 1, 1], [0, 0, 1], [1, 1, 0]], dtype="float64"),
      ]
      self.sparse_features = [csr_matrix(f) for f in self.features]
  
      self.labels = [
          np.array([0, 0, 1], dtype="float64"),
          np.array([1, 0, 0], dtype="float64"),
          np.array([0, 1, 0], dtype="float64"),
          np.zeros((3,), dtype="float64"),
      ]
  
      self.censoring = np.array([2, 3, 3, 1], dtype="uint64")
  
      self.expected_output = (
          self.features[0:2],
          self.labels[0:2],
          self.censoring[0:2],
      )
  
file_path: tick/tick/preprocessing/tests/longitudinal_samples_filter_test.py
imports: import numpy
  from scipy.sparse import csr_matrix
  import unittest
  from tick.preprocessing import LongitudinalSamplesFilter
label_desc: Use image node_id 1 for calling the Test obj's underlying member method code with example usage: obj.setUp() without return types