code: def test_relevant_extraction(self):
      self.assertGreater(len(self.y), 0)
      self.assertGreater(len(self.df), 0)
      self.assertGreater(len(self.timeseries), 0)
  
      relevant_augmenter = RelevantFeatureAugmenter(
          column_id="id", column_sort="time"
      )
      relevant_augmenter.set_timeseries_container(self.timeseries)
  
      pipe = Pipeline([("relevant_augmenter", relevant_augmenter)])
  
      with warning_free():
          pipe.fit(self.df, self.y)
      extracted_features = pipe.transform(self.df)
  
      some_expected_features = {
          "F_x__abs_energy",
          "F_x__absolute_sum_of_changes",
          "F_x__autocorrelation__lag_1",
          "F_x__binned_entropy__max_bins_10",
          "F_x__count_above_mean",
          "F_x__longest_strike_above_mean",
          "F_x__maximum",
          "F_x__mean_abs_change",
          "F_x__minimum",
          "F_x__quantile__q_0.1",
          "F_x__range_count__max_1__min_-1",
          "F_x__spkt_welch_density__coeff_2",
          "F_x__standard_deviation",
          "F_x__value_count__value_0",
          "F_x__variance",
          "F_x__variance_larger_than_standard_deviation",
      }
  
      self.assertGreaterEqual(
          set(extracted_features.columns), some_expected_features
      )
      self.assertGreater(len(extracted_features), 0)
  
file_path: tsfresh/tests/integrations/test_full_pipeline.py
imports: import os
  import shutil
  import tempfile
  from unittest import TestCase
  import pandas
  from sklearn.pipeline import Pipeline
  from tests.fixtures import warning_free
  from tsfresh.examples.robot_execution_failures import download_robot_execution_failures, load_robot_execution_failures
  from tsfresh.transformers import RelevantFeatureAugmenter
label_desc: Use image node_id 3 for calling the FullPipelineTestCase_robot_failures obj's underlying member method code with example usage: obj.test_relevant_extraction() without return types