code: def get_mcgrory_titterington():
      m1 = hmm.GaussianHMM(4, init_params="")
      m1.n_features = 4
      m1.startprob_ = np.array([1 / 4.0, 1 / 4.0, 1 / 4.0, 1 / 4.0])
      m1.transmat_ = np.array(
          [
              [0.2, 0.2, 0.3, 0.3],
              [0.3, 0.2, 0.2, 0.3],
              [0.2, 0.3, 0.3, 0.2],
              [0.3, 0.3, 0.2, 0.2],
          ]
      )
      m1.means_ = np.array([[-1.5], [0], [1.5], [3.0]])
      m1.covars_ = np.sqrt([[0.25], [0.25], [0.25], [0.25]])
      return m1
  
imports: import numpy
  import pytest
  from sklearn.utils import check_random_state
  from hmmlearn import hmm, vhmm
  from .None import assert_log_likelihood_increasing, compare_variational_and_em_models, make_covar_matrix, normalized, vi_uniform_startprob_and_transmat
label_desc: Use image node_id 1 for calling a global function with example usage: get_mcgrory_titterington() and returns: m1