code: def test_score_samples(self):
      # ``StubHMM` ignores the values in ```X``, so we just pass in an
      # array of the appropriate shape.
      log_prob, posteriors = self.hmm.score_samples(self.log_frameprob)
      assert_allclose(posteriors.sum(axis=1), np.ones(len(posteriors)))
      ref_log_prob = -3.3725
      assert round(log_prob, 4) == ref_log_prob
      refposteriors = np.array(
          [
              [0.8673, 0.1327],
              [0.8204, 0.1796],
              [0.3075, 0.6925],
              [0.8204, 0.1796],
              [0.8673, 0.1327],
          ]
      )
      assert_allclose(posteriors, refposteriors, atol=1e-4)
  
imports: import numpy
  from numpy.testing import assert_allclose
  import pytest
  from scipy import special
  from hmmlearn.base import BaseHMM, ConvergenceMonitor
  from hmmlearn import _hmmc
label_desc: Use image node_id 7 for calling the TestBaseAgainstWikipedia obj's underlying member method code with example usage: obj.test_score_samples() without return types