code: def test_LearnerSCCS_fit(self):
      seed = 42
      n_lags = np.repeat(2, 2).astype("uint64")
      sim = SimuSCCS(
          n_cases=800,
          n_intervals=10,
          n_features=2,
          n_lags=n_lags,
          verbose=False,
          seed=seed,
          exposure_type="multiple_exposures",
      )
      features, _, labels, censoring, coeffs = sim.simulate()
      lrn = ConvSCCS(
          n_lags=n_lags,
          penalized_features=[],
          tol=0,
          max_iter=10,
          random_state=seed,
      )
      estimated_coeffs, _ = lrn.fit(features, labels, censoring)
      np.testing.assert_almost_equal(
          np.hstack(estimated_coeffs), np.hstack(coeffs), decimal=1
      )
  
file_path: tick/tick/survival/tests/convolutional_sccs_test.py
imports: import unittest
  import numpy
  from tick.survival import SimuSCCS, ConvSCCS
  from scipy.sparse import csr_matrix
  from tick.survival.sccs import *
label_desc: Use image node_id 4 for calling the Test obj's underlying member method code with example usage: obj.test_LearnerSCCS_fit() without return types