code: def test_sparse_infinite_features_product(self):
      expected_output = [
          np.array(
              [
                  [0, 1, 0, 0, 0, 0],
                  [0, 0, 0, 0, 0, 0],
                  [0, 0, 1, 0, 0, 1],
              ],
              dtype="float64",
          ),
          np.array(
              [
                  [1, 1, 0, 1, 0, 0],
                  [0, 0, 1, 0, 1, 1],
                  [0, 0, 0, 0, 0, 0],
              ],
              dtype="float64",
          ),
      ]
      sparse_feat = [csr_matrix(f) for f in self.infinite_exposures]
      feat_prod, _, _ = LongitudinalFeaturesProduct(
          "infinite"
      ).fit_transform(sparse_feat)
      feat_prod = [f.toarray() for f in feat_prod]
      np.testing.assert_equal(feat_prod, expected_output)
  
file_path: tick/tick/preprocessing/tests/longitudinal_features_product_test.py
imports: import numpy
  from scipy.sparse import csr_matrix
  import unittest
  from tick.preprocessing import LongitudinalFeaturesProduct
label_desc: Use image node_id 3 for calling the Test obj's underlying member method code with example usage: obj.test_sparse_infinite_features_product() without return types