code: def test_tsfel_advanced_features(dummy_data):
      from tsfel.feature_extraction.features import (  # Some temporal features; Some statistical features; Some spectral features
          auc,
          calc_centroid,
          ecdf,
          ecdf_percentile_count,
          entropy,
          fft_mean_coeff,
          fundamental_frequency,
          hist,
          human_range_energy,
          max_power_spectrum,
          mfcc,
          neighbourhood_peaks,
          spectral_centroid,
          spectral_decrease,
          spectral_distance,
          spectral_kurtosis,
          spectral_spread,
          wavelet_abs_mean,
          wavelet_energy,
          wavelet_std,
      )
  
      advanced_feats = MultipleFeatureDescriptors(
          functions=[
              # Temporal
              FuncWrapper(calc_centroid, fs=4),
              FuncWrapper(auc, fs=4),
              FuncWrapper(
                  entropy, prob="kde", output_names="entropy_kde"
              ),
              FuncWrapper(
                  entropy, prob="gauss", output_names="entropy_gauss"
              ),
              FuncWrapper(
                  neighbourhood_peaks,
                  n=5,
                  output_names="neighbourhood_peaks_n=5",
              ),
              # Statistical
              FuncWrapper(
                  hist,
                  nbins=4,
                  output_names=[f"hist{i}" for i in range(1, 5)],
              ),
              FuncWrapper(
                  ecdf, output_names=[f"ecdf{i}" for i in range(1, 11)]
              ),
              FuncWrapper(
                  ecdf_percentile_count,
                  output_names=["ecdf_0.2", "ecdf_0.8"],
              ),
              # Spectral
              FuncWrapper(spectral_distance, fs=4),
              FuncWrapper(fundamental_frequency, fs=4),
              FuncWrapper(max_power_spectrum, fs=4),
              FuncWrapper(spectral_centroid, fs=4),
              FuncWrapper(spectral_decrease, fs=4),
              FuncWrapper(spectral_kurtosis, fs=4),
              FuncWrapper(spectral_spread, fs=4),
              FuncWrapper(human_range_energy, fs=4),
              FuncWrapper(
                  mfcc,
                  fs=4,
                  num_ceps=6,
                  output_names=[f"mfcc{i}" for i in range(1, 7)],
              ),
              FuncWrapper(
                  fft_mean_coeff,
                  fs=4,
                  nfreq=8,
                  output_names=[
                      f"fft_mean_coeff_{i}" for i in range(8)
                  ],
              ),
              FuncWrapper(
                  wavelet_abs_mean,
                  output_names=[
                      f"wavelet_abs_mean_{i}" for i in range(1, 10)
                  ],
              ),
              FuncWrapper(
                  wavelet_std,
                  output_names=[
                      f"wavelet_std_{i}" for i in range(1, 10)
                  ],
              ),
              FuncWrapper(
                  wavelet_energy,
                  widths=np.arange(1, 5),
                  output_names=[
                      f"wavelet_energy_{i}" for i in range(1, 5)
                  ],
              ),
          ],
          series_names=["ACC_x", "EDA"],
          windows="5min",
          strides="10min",
      )
      feature_collection = FeatureCollection(advanced_feats)
  
      res_df = feature_collection.calculate(
          dummy_data.first("15min"), return_df=True
      )
      assert (
          res_df.shape[1]
          == (5 + 4 + 10 + 2 + 8 + 6 + 8 + 9 + 9 + 4) * 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 7 for calling a global function with example usage: test_tsfel_advanced_features(dummy_data) without return types