code: def test_intercept(self, distribution, noise_scale):
      graph = StructureModel()
      graph.add_node("123")
  
      data_noint = generate_binary_data(
          graph,
          100000,
          distribution,
          noise_scale=noise_scale,
          seed=10,
          intercept=False,
      )
      data_intercept = generate_binary_data(
          graph,
          100000,
          distribution,
          noise_scale=noise_scale,
          seed=10,
          intercept=True,
      )
      assert not np.isclose(
          data_noint[:, 0].mean(), data_intercept[:, 0].mean()
      )
  
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 7 for calling the TestGenerateBinaryData obj's underlying member method code with example usage: obj.test_intercept(distribution, noise_scale) without return types