docstr: A wrong initialisation could lead to counts always being zero if they dont
  have parents.
docstr_tok: ["A","wrong","initialisation","could","lead","to","counts","always","being","zero","if","they","dont","have","parents","."]
code: def test_zero_lambda(self):
      """
      A wrong initialisation could lead to counts always being zero if they dont
      have parents.
      """
      graph = StructureModel()
      graph.add_nodes_from(list(range(20)))
      df = generate_count_dataframe(graph, 10000)
      assert not np.any(df.mean() == 0)
  
imports: import re
  import string
  from itertools import product
  import numpy
  import pandas
  import pytest
  from scipy import stats
  from sklearn.gaussian_process.kernels import RBF
  from causalnex.structure import StructureModel
  from causalnex.structure.data_generators import gen_stationary_dyn_net_and_df, generate_binary_data, generate_binary_dataframe, generate_categorical_dataframe, generate_continuous_data, generate_continuous_dataframe, generate_count_dataframe, generate_dataframe_dynamic, generate_structure, generate_structure_dynamic
  from tests.structure.data_generators.test_core import calculate_proba
label_desc: Use image node_id 1 for calling the TestGenerateCountData obj's underlying member method code with example usage: obj.test_zero_lambda() without return types