code: def test_does_impute(self, calculate_relevance_table_mock):
      df = pd.DataFrame(
          [[1, 1, 1], [2, 1, 1]], columns=["id", "time", "value"]
      )
      X = pd.DataFrame(index=[1])
      y = pd.Series([0, 1])
      fc_parameters = {"autocorrelation": [{"lag": 2}]}
  
      calculate_relevance_table_mock.return_value = pd.DataFrame(
          columns=["feature", "p_value", "relevant"]
      )
      augmenter = RelevantFeatureAugmenter(
          column_id="id",
          column_sort="time",
          default_fc_parameters=fc_parameters,
      )
      augmenter.set_timeseries_container(df)
      with warning_free():
          augmenter.fit(X, y)
  
      assert calculate_relevance_table_mock.call_count == 1
      assert (
          not calculate_relevance_table_mock.call_args[0][0]
          .isnull()
          .any()
          .any()
      )
  
imports: import mock
  import numpy
  import pandas
  from sklearn import model_selection
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.pipeline import Pipeline
  from tests.fixtures import DataTestCase, warning_free
  from tsfresh.feature_extraction import MinimalFCParameters
  from tsfresh.transformers.relevant_feature_augmenter import RelevantFeatureAugmenter
label_desc: Use image node_id 7 for calling the RelevantFeatureAugmenterTestCase obj's underlying member method code with example usage: obj.test_does_impute(calculate_relevance_table_mock) without return types