code: def test_seglearn_basic_features(dummy_data):
      base_features = seglearn.feature_functions.base_features
  
      basic_feats = MultipleFeatureDescriptors(
          functions=[
              seglearn_wrapper(f, k) for k, f in base_features().items()
          ],
          series_names=["TMP", "EDA"],
          windows="5min",
          strides="2min",
      )
      feature_collection = FeatureCollection(basic_feats)
  
      res_df = feature_collection.calculate(
          dummy_data, return_df=True, n_jobs=0
      )
      assert res_df.shape[1] == len(base_features()) * 2
      assert res_df.shape[0] > 0
      assert not res_df.isna().any().any()
  
file_path: tsflex/tests/test_features_integration.py
imports: import sys
  import numpy
  import pytest
  import seglearn
  from tsflex.features import FeatureCollection, FuncWrapper, MultipleFeatureDescriptors
  from tsflex.features.integrations import catch22_wrapper, seglearn_feature_dict_wrapper, seglearn_wrapper, tsfel_feature_dict_wrapper, tsfresh_combiner_wrapper, tsfresh_settings_wrapper
  from .utils import dummy_data
label_desc: Use image node_id 1 for calling a global function with example usage: test_seglearn_basic_features(dummy_data) without return types