code: def test_robust_gap_features_multi_input(dummy_data):
      def abs_diff_mean(x: np.ndarray, y: np.ndarray):
          abs_diff = np.abs(x - y)
          return np.mean(abs_diff)
  
      feats = MultipleFeatureDescriptors(
          functions=make_robust(abs_diff_mean, min_nb_samples=2),
          series_names=("EDA", "TMP"),
          windows="10s",
          strides="5s",
      )
      feature_collection = FeatureCollection(feats)
  
      eda_tmp_data = dummy_data[["EDA", "TMP"]].dropna()
      eda_tmp_data[2 : 1 + 25 * 4] = None  # Leave gap of 25 s
      eda_tmp_data = eda_tmp_data.dropna()
      assert not eda_tmp_data.isna().any().any()
      assert (
          eda_tmp_data.index[1:] - eda_tmp_data.index[:-1]
      ).max() == pd.Timedelta("25 s")
  
      res_df = feature_collection.calculate(
          eda_tmp_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 3 for calling a global function with example usage: test_robust_gap_features_multi_input(dummy_data) and returns: np