docstr: Test EM algorithm on naive Bayes structure with additional parents
docstr_tok: ["Test","EM","algorithm","on","naive","Bayes","structure","with","additional","parents"]
code: def test_get_default_priors(self):
      """Test EM algorithm on naive Bayes structure with additional parents"""
      _, sm, node_states, _ = naive_bayes_plus_parents(
          p_c=0.6, parents=3, percentage_not_missing=0.02
      )
      default_priors = EMSingleLatentVariable.get_default_priors(
          sm, node_states, "z"
      )
      assert default_priors.keys() == {"c_0", "c_1", "c_2", "z"}
  
      for k in default_priors:
          assert np.all(default_priors[k] == 0)
  
imports: from collections import Counter
  from typing import Any, AnyStr, Dict, Iterable, List, Set, Tuple, Union
  import numpy
  import pandas
  import pytest
  from causalnex.estimator.em import EMSingleLatentVariable
  from causalnex.network import BayesianNetwork
  from causalnex.structure.structuremodel import StructureModel
  from causalnex.utils.data_utils import states_to_df
label_desc: Use image node_id 1 for calling the TestPriors obj's underlying member method code with example usage: obj.test_get_default_priors() without return types