code: def test_robust_gap_features_multi_output(dummy_data):
      def mean_std(x: np.ndarray):
          return np.mean(x), np.std(x)
  
      feats = MultipleFeatureDescriptors(
          functions=make_robust(
              FuncWrapper(mean_std, output_names=["mean", "std"]),
              min_nb_samples=2,
          ),
          series_names="EDA",
          windows="10s",
          strides="5s",
      )
      feature_collection = FeatureCollection(feats)
  
      eda_data = dummy_data["EDA"].dropna()
      eda_data[2 : 1 + 25 * 4] = None  # Leave gap of 25 s
      eda_data = eda_data.dropna()
      assert not eda_data.isna().any()
      assert (
          eda_data.index[1:] - eda_data.index[:-1]
      ).max() == pd.Timedelta("25 s")
  
      res_df = feature_collection.calculate(
          eda_data, return_df=True, approve_sparsity=True
      )
      assert res_df.isna()[1:4].all().all()
      assert not res_df[4:].isna().any().any()
  
file_path: tsflex/tests/test_features_utils.py
imports: import numpy
  import pandas
  import pytest
  from tsflex.features import FeatureCollection, FuncWrapper, MultipleFeatureDescriptors
  from tsflex.features.utils import make_robust
  from .utils import dummy_data
label_desc: Use image node_id 4 for calling a global function with example usage: test_robust_gap_features_multi_output(dummy_data) and returns: np,  np